An overview of fecal sample preparation for global metabolic profiling

The effects of galacto-oligosaccharides on faecal parameters in healthy dogs and cats

The aim of this study was to evaluate the effects of galacto-oligosaccharides (GOS) on faecal parameters in healthy dogs and cats. To this end, 20 dogs and 20 Domestic shorthair cats were fed a commercially available adult dog food, or cat food, respectively, with either syrup containing GOS (at 1% w galacto-oligosaccharides/w formulated feed) on top (test group) or no topping (control group) for 56 days in a cross-over design. The study consisted of 2 periods of 24 days adaptation, followed by 4 days of collection of faeces. Faecal samples were tested for moisture, nitrogen, pH, macronutrients, enzymes, and fermentation products. The faecal microbiota were analysed by 16S rDNA profiling. It appeared that GOS have different effects in dogs compared to cats. In dogs, the addition of GOS resulted in increased carbohydrate fermentation (increase of acetic and butyric acid), whereas in cats GOS resulted in increased amino acid fermentation (increase of isovaleric acid). The α-diversity of the canine faecal microbiota was reduced by dietary GOS (Inverse Simpson Index, p = 0.063; Shannon index, p = 0.035) whereas the α-diversity of cat faecal microbiota was unaffected (Inverse Simpson Index, p = 0.539; Shannon index, p = 0.872). Lachnospiraceae spp. and Bifidobacterium spp. positively responded to GOS in both cats and dogs. Lactobacillus spp. and Enterobacteriaceae spp. positively responded to GOS in dogs. In both dogs and cats, GOS may therefore improve stool microbiota and result in the production of specific metabolites that are beneficial to gut health.

Determination of short-chain fatty acids as putative biomarkers of cancer diseases by modern analytical strategies and tools: a review

Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of non-digestible carbohydrates in the gastrointestinal tract. They can be seen as the major flow of carbon from the diet, through the microbiome to the host. SCFAs have been reported as important molecules responsible for the regulation of intestinal homeostasis. Moreover, these molecules have a significant impact on the immune system and are able to affect inflammation, cardiovascular diseases, diabetes type II, or oncological diseases. For this purpose, SCFAs could be used as putative biomarkers of various diseases, including cancer. A potential diagnostic value may be offered by analyzing SCFAs with the use of advanced analytical approaches such as gas chromatography (GC), liquid chromatography (LC), or capillary electrophoresis (CE) coupled with mass spectrometry (MS). The presented review summarizes the importance of analyzing SCFAs from clinical and analytical perspective. Current advances in the analysis of SCFAs focused on sample pretreatment, separation strategy, and detection methods are highlighted. Additionally, it also shows potential areas for the development of future diagnostic tools in oncology and other varieties of diseases based on targeted metabolite profiling.

Application of Benchtop NMR for Metabolomics Study Using Feces of Mice with DSS-Induced Colitis

Nuclear magnetic resonance (NMR)-based metabolomics, which comprehensively measures metabolites in biological systems and investigates their response to various perturbations, is widely used in research to identify biomarkers and investigate the pathogenesis of underlying diseases. However, further applications of high-field superconducting NMR for medical purposes and field research are restricted by its high cost and low accessibility. In this study, we applied a low-field, benchtop NMR spectrometer (60 MHz) employing a permanent magnet to characterize the alterations in the metabolic profile of fecal extracts obtained from dextran sodium sulfate (DSS)-induced ulcerative colitis model mice and compared them with the data acquired from high-field NMR (800 MHz). Nineteen metabolites were assigned to the 60 MHz ¹H NMR spectra. Non-targeted multivariate analysis successfully discriminated the DSS-induced group from the healthy control group and showed high comparability with high-field NMR. In addition, the concentration of acetate, identified as a metabolite with characteristic behavior, could be accurately quantified using a generalized Lorentzian curve fitting method based on the 60 MHz NMR spectra.

Gut microbiome dysbiosis drives metabolic dysfunction in Familial dysautonomia

Familial dysautonomia (FD) is a rare genetic neurologic disorder caused by impaired neuronal development and progressive degeneration of both the peripheral and central nervous systems. FD is monogenic, with >99.4% of patients sharing an identical point mutation in the elongator acetyltransferase complex subunit 1 (ELP1) gene, providing a relatively simple genetic background in which to identify modifiable factors that influence pathology. Gastrointestinal symptoms and metabolic deficits are common among FD patients, which supports the hypothesis that the gut microbiome and metabolome are altered and dysfunctional compared to healthy individuals. Here we show significant differences in gut microbiome composition (16 S rRNA gene sequencing of stool samples) and NMR-based stool and serum metabolomes between a cohort of FD patients (~14% of patients worldwide) and their cohabitating, healthy relatives. We show that key observations in human subjects are recapitulated in a neuron-specific Elp1-deficient mouse model, and that cohousing mutant and littermate control mice ameliorates gut microbiome dysbiosis, improves deficits in gut transit, and reduces disease severity. Our results provide evidence that neurologic deficits in FD alter the structure and function of the gut microbiome, which shifts overall host metabolism to perpetuate further neurodegeneration.

An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and Its Application in Gastrointestinal Disease

Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn's disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC.

Metabolomics in Team-Sport Athletes: Current Knowledge, Challenges, and Future Perspectives

Metabolomics is a promising tool for studying exercise physiology and exercise-associated metabolism. It has recently been defined with the term “sportomics” due to metabolomics’ capability to characterize several metabolites in several biological samples simultaneously. This narrative review on exercise metabolomics provides an initial and brief overview of the different metabolomics technologies, sample collection, and further processing steps employed for sport. It also discusses the data analysis and its biological interpretation. Thus, we do not cover sample collection, preparation, and analysis paragraphs in detail here but outline a general outlook to help the reader to understand the metabolomics studies conducted in team-sports athletes, alongside endeavoring to recognize existing or emergent trends and deal with upcoming directions in the field of exercise metabolomics in a team-sports setting.

Studying the Parkinson's disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development.

Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes

Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host-microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.

Standards for Collection, Preservation, and Transportation of Fecal Samples in TCM Clinical Trials

Background

Unlike chemical drugs with a single or a few kinds of active compounds, traditional Chinese medicines (TCMs)uses herbal formulas composed of numerous kinds of chemical constituents. Therefore, TCM clinical trials require unique and stricter standards for collecting, preserving, and transporting fecal samples than those used for chemical drugs. Unfortunately, there are no special standards for processing fecal samples in TCM clinical trials.

Methods

We invited interdisciplinary experts within TCM clinical trials and gut microbiome research to help formulate this standard. After more than a year’s in-depth discussion and amendments, we achieved a standard via expert interviews, literature research, questionnaire surveys, and public opinion solicitation. This standard has been reviewed and approved by the Standards Office of China of the Association of Chinese medicine.

Results

We established a sample information processing method prior to TCM clinical sample collection, which is adapted to the unique features of TCM. The method formulates detailed processing requirements for TCM information in addition to the factors that may disturb the gut microbiome. We also constructed a set of methods for collecting, preserving, and transporting fecal samples that meet the characteristics of TCM. These methods formulate detailed operating specifications on the collection approaches, storage conditions, transportation requirements, and management of fecal samples.

Conclusions

This standard guides the information processing prior to sample collection and the standard operating procedures for the collection, preservation, and transportation of fecal samples in TCM clinical trials, which also can be used as a reference by clinicians and researchers in modern medicines.

Current development of bioanalytical sample preparation techniques in pharmaceuticals

Sample preparation is considered as the bottleneck step in bioanalysis because each biological matrix has its own unique challenges and complexity. Competent sample preparation to extract the desired analytes and remove redundant components is a crucial step in each bioanalytical approach. The matrix effect is a key hurdle in bioanalytical sample preparation, which has gained extensive consideration. Novel sample preparation techniques have advantages over classical techniques in terms of accuracy, automation, ease of sample preparation, storage, and shipment and have become increasingly popular over the past decade. Our objective is to provide a broad outline of current developments in various bioanalytical sample preparation techniques in chromatographic and spectroscopic examinations. In addition, how these techniques have gained considerable attention over the past decade in bioanalytical research is mentioned with preferred examples. Modern trends in bioanalytical sample preparation techniques, including sorbent-based microextraction techniques, are primarily emphasized.

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Bioanalytical sampling techniques are described with suitable applications in pharmaceuticals.

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The pros and cons of each bioanalytical sampling techniques are described.

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Relevant biological matrices are outlined.

Evaluation of different stool extraction methods for metabolomics measurements in human faecal samples

Background

Metabolomics analysis of human stool samples is of great interest for a broad range of applications in biomedical research including early detection of colorectal neoplasms. However, due to the complexity of metabolites there is no consensus on how to process samples for stool metabolomics measurements to obtain a broad coverage of hydrophilic and hydrophobic substances.

Methods

We used frozen stool samples (50 mg) from healthy study participants. Stool samples were processed after thawing using eight different processing protocols and different solvents (solvents such as phosphate-buffered saline, isopropanol, methanol, ethanol, acetonitrile and solvent mixtures with or without following evaporation and concentration steps). Metabolites were measured afterwards using the MxP Quant 500 kit (Biocrates). The best performing protocol was subsequently applied to compare stool samples of participants with different dietary habits.

Results

In this study, we were able to determine up to 340 metabolites of various chemical classes extracted from stool samples of healthy study participants with eight different protocols. Polar metabolites such as amino acids could be measured with each method while other metabolite classes, particular lipid species (better with isopropanol and ethanol or methanol following a drying step), are more dependent on the solvent or combination of solvents used. Only a small number of triglycerides or acylcarnitines were detected in human faeces. Extraction efficiency was higher for protocols using isopropanol (131 metabolites>limit of detection (LOD)) or those using ethanol or methanol and methyl tert-butyl ether (MTBE) including an evaporation and concentration step (303 and 342 metabolites>LOD, respectively) than for other protocols. We detected significant faecal metabolite differences between vegetarians, semivegetarians and non-vegetarians.

Conclusion

For the evaluation of metabolites in faecal samples, we found protocols using solvents like isopropanol and those using ethanol or methanol, and MTBE including an evaporation and concentration step to be superior regarding the number of detected metabolites of different chemical classes over others tested in this study.

A review and roadmap of the skin, lung and gut microbiota in systemic sclerosis

As our understanding of the genetic underpinnings of SSc increases, questions regarding the environmental trigger(s) that induce and propagate SSc in the genetically predisposed individual emerge. The interplay between the environment, the immune system, and the microbial species that inhabit the patient's skin and gastrointestinal tract is a pathobiological frontier that is largely unexplored in SSc. The purpose of this review is to provide an overview of the methodologies, experimental study results and future roadmap for elucidating the relationship between the SSc host and his/her microbiome.

Practical and Robust NMR-Based Metabolic Phenotyping of Gut Health in Early Life

While substantial efforts have been made to optimize and standardize fecal metabolomics for studies in adults, the development of a standard protocol to analyze infant feces is, however, still lagging behind. Here, we present the development of a hands-on and robust protocol for proton ¹H NMR spectroscopy of infant feces. The influence of extraction solvent, dilution ratio, homogenization method, filtration, and duration of centrifugation on the biochemical composition of infant feces was carefully evaluated using visual inspection of ¹H NMR spectra in combination with multivariate statistical modeling. The optimal metabolomics protocol was subsequently applied on feces from seven infants collected at 8 weeks, 4, and 9 months of age. Interindividual variation was exceeding the variation induced by different fecal sample preparation methods, except for filtration. We recommend extracting fecal samples using water with a dilution ratio of 1:5 feces-to-water to homogenize using bead beating and to remove particulates using centrifugation. Samples collected from infants aged 8 weeks and 4 months showed elevated concentrations of milk oligosaccharide derivatives and lactic acid, whereas short-chain fatty acids (SCFAs) and branched-chain amino acids (BCAAs) were higher in the 9 month samples. The established protocol enables hands-on and robust analyses of the infant gut metabolome. The wide-ranging application of this protocol will facilitate interlaboratory comparison of infants' metabolic profiles and finally aid in a better understanding of infant gut health.

Review on in vivo profiling of drug metabolites with LC-MS/MS in the past decade

Metabolite profiling is an indispensable part of drug discovery and development, enabling a comprehensive understanding of the drug's metabolic behavior. Liquid chromatography-mass spectrometry facilitates metabolite profiling by reducing sample complexity and providing high sensitivity. This review discusses the in vivo metabolite profiling involving LC-MS/MS and the utilization of QTOF, QQQ mass analyzers with a particular emphasis on a mass filter. Further, a summary of sample extraction procedures in biological matrices such as plasma, urine, feces, serum and hair as in vivo samples are outlined. toward the end, we present 15 case studies in biological matrices and their LC-MS/MS conditions to understand the metabolic disposition.

Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies

A number of studies have shown that the microbial communities of the human body are integral for the maintenance of human health. Advances in next-generation sequencing have enabled rapid and large-scale quantification of the composition of microbial communities in health and disease. Microorganisms mediate diverse host responses including metabolic pathways and immune responses. Using a system biology approach to further understand the underlying alterations of the microbiota in physiological and pathological states can help reveal potential novel therapeutic and diagnostic interventions within the field of synthetic biology. Tools such as biosensors, memory arrays, and engineered bacteria can rewire the microbiome environment. In this article, we review the computational tools used to study microbiome communities and the current limitations of these methods. We evaluate how genome-scale metabolic models (GEMs) can advance our understanding of the microbe-microbe and microbe-host interactions. Moreover, we present how synergies between these system biology approaches and synthetic biology can be harnessed in human microbiome studies to improve future therapeutics and diagnostics and highlight important knowledge gaps for future research in these rapidly evolving fields.

Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (¹H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.

Multi-Solvent Extraction Procedure for the Pioneer Fecal Metabolomic Analysis-Identification of Potential Biomarkers in Stable Kidney Transplant Patients

Metabolic alteration plays a functional role in kidney allograft complications. Metabolomics is a promising high-throughput approach in nephrology but is still limited by the lack of overlap in metabolite coverage. We performed an untargeted fecal metabolomic analysis of forty stable kidney allograft recipients and twenty non-transplant controls. First, we applied the ultra-high performance liquid chromatography (UHPLC) analysis coupled with the Diod Array detector. The potential biomarkers were then collected and identified by gas chromatography-mass spectrometry (GCMS). In order to allow for complete coverage of the fecal polar and non-polar metabolites, the performance of five organic solvents with increasing polarity was investigated successively. UHPLC analysis revealed that the fecal metabolite profiles following the five extractions were significantly different between controls and kidney allografts. GC-MS analysis showed that the best predictors’ metabolites belonged mainly to long-chain fatty acids, phenolic compounds, and amino acids. Collectively, our results showed the efficiency of our pioneer method to successfully discriminate stable kidney-transplant recipients from controls. These findings suggest that distinct metabolic profiles mainly affect fatty acid biosynthesis and amino acid metabolism. In such a context, the novel insights into metabolomic investigation may be a valuable tool that could provide useful new relevant biomarkers for preventing kidney transplant complications.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Fitness for purpose of stabilized stool samples for bile acid metabolite analyses

Biobanks and cohort studies are increasingly utilizing chemical stabilizers to collect and store stool samples for downstream DNA-based microbiome analyses. While stabilizers permit ambient-temperature collection and storage of samples for gut microbiome studies, the use of the same sample type for downstream metabolomics assays has not been explored. Microbiome-metabolomics analysis of fecal samples is increasingly getting attention to further elucidate the mechanisms by which the gut microbiota influences the host. In this study, we evaluated fitness-for-purpose of OMNIgene-GUT-collected stool samples for downstream metabolomics assays in the scope of fecal bile acids (BA) quantification. Biocrates Bile Acids Kit was used for the quantification of BA from eight healthy donors' samples collected in (1) OMNIgene-GUT kit and (2) snap frozen in -80 °C in duplicates. A highly selective reversed phase LC-MS/MS analysis method in negative ion multiple reaction monitoring (MRM) detection mode was applied to determine the BA concentrations in each sample.Total fecal BA levels were detectable in OMNIgene-GUT-collected samples (range: 29.9-903.7 pmol/mg). Paired t-test confirmed that there was a significant difference in the total BAs between the OMNIgene-GUT and snap frozen samples (p < 0.05). Extractions from snap frozen samples resulted in higher concentrations of total BAs (range: 243.7-1136.2 pmol/mg). Qualitative differences between individual donors' BA profiles were detectable using the two sample collection methods. No significant difference was found in the relative concentrations of primary (CA, CDCA) or secondary (DCA, LCA, UDCA) unconjugated BAs to the total BA concentrations in OMNIgene-GUT-collected samples as compared with the snap frozen samples (Wilcoxon-Mann-Whitney test, p > 0.05). Passing-Bablok method comparison and correlation analyis showed a high degree of correlation in the relative concentrations of CA, CDCA, DCA and LCA between OMNIgene-GUT and snap frozen samples. For these four bile acids, the two methods are comparable at an acceptability bias of 30%. We conclude that the OMNIgene-GUT-collected stool samples are fit-for-purpose for downstream fecal bile acids analysis.

Detecting the effects of predator-induced stress on the global metabolism of an ungulate prey using fecal metabolomic fingerprinting

Few field tests have assessed the effects of predator-induced stress on prey fitness, particularly in large carnivore-ungulate systems. Because traditional measures of stress present limitations when applied to free-ranging animals, new strategies and systemic methodologies are needed. Recent studies have shown that stress and anxiety related behaviors can influence the metabolic activity of the gut microbiome in mammal hosts, and these metabolic alterations may aid in identification of stress. In this study, we used NMR-based fecal metabolomic fingerprinting to compare the fecal metabolome, a functional readout of the gut microbiome, of cattle herds grazing in low vs. high wolf-impacted areas within three wolf pack territories. Additionally, we evaluated if other factors (e.g., cattle nutritional state, climate, landscape) besides wolf presence were related to the variation in cattle metabolism. By collecting longitudinal fecal samples from GPS-collared cattle, we found relevant metabolic differences between cattle herds in areas where the probability of wolf pack interaction was higher. Moreover, cattle distance to GPS-collared wolves was the factor most correlated with this difference in cattle metabolism, potentially reflecting the variation in wolf predation risk. We further validated our results through a regression model that reconstructed cattle distances to GPS-collared wolves based on the metabolic difference between cattle herds. Although further research is needed to explore if similar patterns also hold at a finer scale, our results suggests that fecal metabolomic fingerprinting is a promising tool for assessing the physiological responses of prey to predation risk. This novel approach will help improve our knowledge of the consequences of predators beyond the direct effect of predation.

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.

FoodOmicsGR_RI. A Consortium for Comprehensive Molecular Characterisation of Food Products

The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of "omics" technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet's effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders.

Alterations of stool metabolome, phenome, and microbiome of the marine fish, red sea bream, Pagrus major, following exposure to phenanthrene: A non-invasive approach for exposure assessment

The present study aimed to assess the impact of phenanthrene (Phe) on fish health by addressing the alteration of fecal characteristics, in lieu of collecting biomarkers that often involves injurious or even fatal sampling of organisms. The marine fish red sea bream, Pagrus major, was exposed to Phe at a concentration of 18 μg/L for 16 days followed by depuration for 13 days. We collected feces from Phe-exposed or control (Phe-free) fish and then analyzed the fecal metabolite profile (metabolome), carbon utilization of microbiota (phenome), and bacterial 16s rRNA gene sequence (microbiome). Along with the increase in physiological stress markers (SOD and EROD) in serum and liver, we noted the possible role of intestine as a Phe reservoir. Furthermore, abnormal fecal appearance (green coloration) and remarkable changes in fecal characteristics were observed. These changes include alterations of cholesterol and putrescine metabolism and the enhanced utilization of putrescine as a carbon source. Phe also altered the microbial community, with an increase in Phe-degrading bacteria such as Pseudomonas. Interestingly, these enteric impairments were ameliorated by depuration. Taken together, our findings suggest that these alterations in feces were associated with adaptive responses to environmentally relevant Phe exposure scenarios, and that stool samples are potential candidates for exposure assessment in fish.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

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.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

Workshop report: Toward the development of a human whole stool reference material for metabolomic and metagenomic gut microbiome measurements

INTRODUCTION

To date, there has been little effort to develop standards for metabolome-based gut microbiome measurements despite the significant efforts toward standard development for DNA-based microbiome measurements.

OBJECTIVES

The National Institute of Standards and Technology (NIST), The BioCollective (TBC), and the North America Branch of the International Life Sciences Institute (ILSI North America) are collaborating to extend NIST's efforts to develop a Human Whole Stool Reference Material for the purpose of method harmonization and eventual quality control.

METHODS

The reference material will be rationally designed for adequate quality assurance and quality control (QA/QC) for underlying measurements in the study of the impact of diet and nutrition on functional aspects of the host gut microbiome and relationships of those functions to health. To identify which metabolites deserve priority in their value assignment, NIST, TBC, and ILSI North America jointly conducted a workshop on September 12, 2019 at the NIST campus in Gaithersburg, Maryland. The objective of the workshop was to identify metabolites for which evidence indicates relevance to health and disease and to decide on the appropriate course of action to develop a fit-for-purpose reference material.

RESULTS

This document represents the consensus opinions of workshop participants and co-authors of this manuscript, and provides additional supporting information. In addition to developing general criteria for metabolite selection and a preliminary list of proposed metabolites, this paper describes some of the strengths and limitations of this initiative given the current state of microbiome research.

CONCLUSIONS

Given the rapidly evolving nature of gut microbiome science and the current state of knowledge, an RM (as opposed to a CRM) measured for multiple metabolites is appropriate at this stage. As the science evolves, the RM can evolve to match the needs of the research community. Ultimately, the stool RM may exist in sequential versions. Beneficial to this evolution will be a clear line of communication between NIST and the stakeholder community to ensure alignment with current scientific understanding and community needs.

[Evaluation of metabolites levels in feces of patients with inflammatory bowel diseases]

Inflammatory bowel diseases (IBD), which include ulcerative colitis (UC) and Crohn's disease (CD), are chronic intestinal inflammatory disorders with an unknown etiology. They are characterized by chronic recurrent inflammation of the intestinal mucosa and lead to a significant decrease in the quality of life and death of patients. IBD are associated with suppression of normal intestinal microflora, including a decrease in bacteria, producers of short chain fatty acids (SCFAs), exhibiting anti-inflammatory and protective properties. Among the various methods of intestinal microflora correction, fecal microbiota transplantation (FMT), which engrafts the fecal microbiota from a healthy donor into a patient recipient, is of a particular interest. As a result, a positive therapeutic effect is observed, accompanied by the restoration of the normal intestinal microflora of the patient. A significant drawback of the method is the lack of standardization. Metabolites produced by intestinal microflora, namely SCFAs, allow objective assessment of the functional state of the intestinal microbiota and, consequently, the success of the FMT procedure. Using gas chromatography and nuclear magnetic resonance spectroscopy techniques, we have analyzed concentrations and molar ratios of SCFAs in fecal samples of 60 healthy donors. Results were in good accord when comparing two methods as well as with published data. Analysis of SCFAs in feces of patients with UC (19 patients) and CD (17 patients) revealed a general decrease in the concentration of fatty acids in the experimental groups with significant fluctuations in the values in experimental groups compared to control group of healthy donors. On the limited group of IBD patients (6 patients with UC and 5 patients with CD) concentration of SCFAs before and within 30 days of observation after FMT was determined. It was shown that FMT had a significant impact on the SCFAs levels within 1 month term; tendency to reach characteristics of healthy donors is unambiguously traced for both diseases.

Neonatal diet alters fecal microbiota and metabolome profiles at different ages in infants fed breast milk or formula

BACKGROUND

Neonatal diet has a large influence on child health and might modulate changes in fecal microbiota and metabolites.

OBJECTIVES

The aim is to investigate fecal microbiota and metabolites at different ages in infants who were breastfed (BF), received dairy-based milk formula (MF), or received soy-based formula (SF).

METHODS

Fecal samples were collected at 3 (n = 16, 12, and 14, respectively), 6 (n = 20, 19, and 15, respectively), 9 (n = 12, 11, and 12, respectively), and 12 mo (n = 14, 14, and 15, respectively) for BF, MF, and SF infants. Infants that breastfed until 9 mo and switched to formula were considered as no longer breastfeeding at 12 mo. Microbiota data were obtained using 16S ribosomal RNA sequencing. Untargeted metabolomics was conducted using a Q-Exactive Hybrid Quadrupole-Orbitrap mass spectrometer. The data were analyzed using R (version 3.6.0) within the RStudio (version 1.1.463) platform.

RESULTS

At 3, 6, and 9 mo of age BF infants had the lowest α-diversity, SF infants had the highest diversity, and MF was intermediate. Bifidobacterium was 2.6- to 5-fold lower in SF relative to BF infants through 1 y of life. An unidentified genus from Ruminococcaceae higher in the SF (2%) than in the MF (0.4%) and BF (0.08%) infants at 3 mo of age was observed. In BF infants higher levels of butyric acid, d-sphingosine, kynurenic acid, indole-3-lactic acid, indole-3-acetic acid, and betaine were observed than in MF and SF infants. At 3 mo Ruminococcaceae was positively correlated to azelaic, gentisic, isocitric, sebacic, and syringic acids. At 6 mo Oscillospira was negatively correlated with 3-hydroxybutyric-acid, hydroxy-hydrocinnamic acid, and betaine whereas Bifidobacterium was negatively associated with 5-hydroxytryptamine. At 12 mo of age, Lachnospiraceae was negatively associated with hydroxyphenyllactic acid.

CONCLUSIONS

Infant diet has a large impact on the fecal microbiome and metabolome in the first year of life.This study was registered at clinicaltrials.gov as NCT00616395.

An LC-QToF MS based method for untargeted metabolomics of human fecal samples

INTRODUCTION

Consensus in sample preparation for untargeted human fecal metabolomics is lacking.

OBJECTIVES

To obtain sample preparation with broad metabolite coverage for high-throughput LC-MS.

METHODS

Extraction solvent, solvent ratio and fresh frozen-vs-lyophilized samples were evaluated by metabolite feature quality.

RESULTS

Methanol at 5 mL per g wet feces provided a wide metabolite coverage with optimal balance between signal intensity and saturation for both fresh frozen and lyophilized samples. Lyophilization did not affect SCFA and is recommended because of convenience in normalizing to dry matter.

CONCLUSION

The suggested sample preparation is simple, efficient and suitable for large-scale human fecal metabolomics.

Fecal Metabolites As Non-Invasive Biomarkers of Gut Diseases

Recent studies have shown the importance of the human intestinal microbiome in maintaining a healthy gastrointestinal tract, as well as in the development of pathological processes. The intestinal microbiome manifests itself primarily as fecal metabolites. In the past decade, there has been growing interest in studying its composition, which for the most part had to do with the possibility of using the metabolomic analysis in clinical diagnosis. In contrast to the comprehensive description of blood serum, urine, saliva, and cerebrospinal fluid metabolites, data on fecal metabolites is sparse. Despite the instrumental and methodological achievements in the metabolomic analysis in general, the analysis of fecal metabolome remains less well developed, mainly because of the inhomogeneity of its composition and the lack of standardized methods for collecting, processing, and analyzing fecal samples. This review summarizes data on methods for studying and describing various groups of fecal metabolites. It also assesses their potential as tools in the diagnosis of gastrointestinal diseases.

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.

Fecal Metabolomics as a Novel Noninvasive Method for Short-Term Stress Monitoring in Beef Cattle

Traditional measures of short-term stress response such as fecal glucocorticoid metabolites (FGM) are widely used in controlled settings to quantify the intensity of stimulation to which cattle are exposed. However, FGMs present several methodological and interpretation pitfalls when applied on animals in free-ranging conditions. In this study, we proposed an NMR-based fecal metabolomics strategy for noninvasive stress detection in beef cattle. Using a longitudinal sample collection, we monitored the changes in the fecal metabolome and FGM concentrations before and after an acute stressful event. Our results showed that while the fecal metabolome changed as a function of stress (p < 0.001), the mean concentrations of FGM did not change (Levene's test: F-ratio: 0.87, p-value: 0.44). Furthermore, we showed that the interanimal variability observed in the stress response was correlated with the individual fecal microbiota. This result was in line with recent findings, indicating the gut microbiome as a crucial mediator of stress response. We conclude that NMR-based fecal metabolomics proved to be a reliable methodology to assess stress response and that its future applicability to studies for stress monitoring in range animals may be more appropriate than FGM analysis.

Assessment of gut microbiota fecal metabolites by chromatographic targeted approaches

Gut microbiota, the specific microbial community of the gastrointestinal tract, by means of the production of microbial metabolites provides the host with several functions affecting metabolic and immunological homeostasis. Insights into the intricate relationships between gut microbiota and the host require not only the understanding of its structure and function but also the measurement of effector molecules acting along the gut microbiota axis. This article reviews the literature on targeted chromatographic approaches in analysis of gut microbiota specific metabolites in feces as the most accessible biological matrix which can directly probe the connection between intestinal bacteria and the (patho)physiology of the holobiont. Together with a discussion on sample collection and preparation, the chromatographic methods targeted to determination of some classes of microbiota-derived metabolites (e.g., short-chain fatty acids, bile acids, low molecular masses amines and polyamines, vitamins, neurotransmitters and related compounds) are discussed and their main characteristics, summarized in Tables.

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 potential of nanoflow liquid chromatography-nano electrospray ionisation-mass spectrometry for global profiling the faecal metabolome

Faeces are comprised of a wide array of metabolites arising from the circulatory system as well as the human microbiome. A global metabolite analysis (metabolomics) of faecal extracts offers the potential to uncover new compounds which may be indicative of the onset of bowel diseases such as colorectal cancer (CRC). To date, faecal metabolomics is still in its infancy and the compounds of low abundance present in faecal extracts poorly characterised. In this study, extracts of faeces from healthy subjects were profiled using a sensitive nanoflow-nanospray LC-MS platform which resulted in highly repeatable peak retention times (<2% CV) and intensities (<15% CV). Analysis of the extracts revealed wide coverage of the faecal metabolome including detection of low abundant signalling compounds such as sex steroids and eicosanoids, alongside highly abundant pharmaceuticals and tetrapyrrole metabolites. A small pilot study investigating differences in metabolomics profiles of faecal samples obtained from 7 CRC, 25 adenomatous polyp and 26 healthy groups revealed that secondary bile acids, conjugated androgens, eicosanoids, phospholipids and an unidentified haem metabolite were potential classes of metabolites that discriminated between the CRC and control sample groups. However, much larger follow up studies are needed to confirm which components of the faecal metabolome are associated with actual CRC disease rather than dietary influences. This study reveals the potential of nanospray-nanoflow LC-MS profiling of faecal samples from large scale cohort studies for uncovering the role of the faecal metabolome in colorectal disease formation.

Urine and fecal samples targeted metabolomics of carobs treated rats

Ceratonia siliqua, known as the carob, is considered to be of high nutritional value and of great economic significance due to its unique composition. The beneficial effects of carob against cancer, metabolic syndrome, diabetes, diarrhea, hyperlipidemia and gastro esophageal reflux disease are only a few of its therapeutic actions. Metabolomics-based analysis provides an ultimate tool, for the deciphering of nutritional intervention derived metabolic alterations. In the present study, 16 male Wistar rats were treated with carob powder for a 15-day period. Fecal and urine samples were collected at 5 time points (0, 1, 5, 10 and 15 days). By the applied HILIC-MS/MS method, 63 and 67 hydrophilic metabolites were detected in the fecal and urine samples, respectively, including amino acids, organic acids, sugars, vitamins and other endogenous compounds. A clear group separation based on fecal metabolome was observed after 1 day and 15 days treatment, while only a mild differentiation at day 1 was observed based on urine metabolome. Twenty-one fecal metabolites were responsible for the separation including amino acids and their derivatives, vitamins and organic acids. However, only 7 metabolites were altered in rat urine samples. Metabolic alterations in fecal samples could be attributed to physiological and biochemical adaptations derived from the nutritional intervention. Fecal targeted metabolomics were proven to be suitable for uplifting and highlighting such alterations.

Efficient Extraction from Mice Feces for NMR Metabolomics Measurements with Special Emphasis on SCFAs

Nuclear magnetic resonance (NMR) spectroscopy is one of the most promising methods for use in metabolomics studies as it is able to perform non targeted measurement of metabolites in a quantitative and non-destructive way. Sample preparation of liquid samples like urine or blood serum is comparatively easy in NMR metabolomics, because mainly buffer and chemical shift reference substance are added. For solid samples like feces suitable extraction protocols need to be defined as initial step, where the exact protocol depends on sample type and features. Focusing on short chain fatty acids (SCFAs) in mice feces, we describe here a set of extraction protocols developed with the aim to suppress changes in metabolite composition within 24 h after extraction. Feces are obtained from mice fed on either standard rodent diet or high fat diet. The protocols presented in this manuscript are straightforward for application, and successfully minimize residual bacterial and enzymatic activities. Additionally, they are able to minimize the lipid background originating from the high fat diet.

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.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

Impact of Sample Storage on the NMR Fecal Water Metabolome

The study of the fecal metabolome is an important area of research to better understand the human gut microbiome and its impact on human health and diseases. However, there is a lack of work in examining the impact of storage and processing conditions on the metabolite levels of fecal water. Furthermore, there is no universal protocol used for the storage of fecal samples and preparation of fecal water. The objective of the current study was to examine the impact of different storage conditions on fecal samples prior to metabolite extraction. Fecal samples obtained from nine healthy individuals were processed under different conditions: (1) fresh samples prepared immediately after collection, (2) fecal samples stored at 4 °C for 24 h prior to processing, and (3) fecal samples stored at -80 °C for 24 h prior to processing. All samples were analyzed using NMR spectroscopy, multivariate statistical analysis, and repeated measures ANOVA. Samples which were frozen at -80 °C prior to extraction of the metabolites exhibited an increase in the number of metabolites including branched-chain amino acids, aromatic amino acids, and tricarboxylic acid cycle intermediates. Storage of fecal samples at 4 °C ensured higher fidelity to freshly processed samples leading to the recommendation that fecal samples should not be frozen prior to extraction of fecal water. Furthermore, the work highlights the need to standardize sample storage of fecal samples to allow for the accurate study of the fecal metabolome.