Metabolomic Profiling of Biological Reference Materials using a Multiplatform High-Resolution Mass Spectrometric Approach

Reversed-phase liquid chromatography/mass spectrometry approach for (un)targeted analysis of polar to mid-polar metabolites

Herein, we aim to establish a straightforward and versatile reversed-phase liquid chromatography/mass spectrometry (RP-LC/MS) methodology for analyzing a wide range of polar and mid-polar metabolites utilizing a single instrument, column, and mobile phase. We present a comprehensive evaluation of three C18 columns compatible with aqueous solutions using 19 mobile phases in terms of the number of detected metabolites, chromatographic performance, and MS response. The RP-LC/MS platform utilizes the HSS T3 column with a mobile phase consisting of 0.2 % formic acid, acetonitrile, and propan-2-ol, effectively separating polar and mid-polar metabolites through various mobile phase gradients. Our developed method outperforms the conventional hydrophilic interaction liquid chromatography metabolomic method, yielding a higher number of detected metabolites and better chromatographic performance. The RP-LC/MS platform demonstrates excellent intrabatch and interbatch retention time repeatability (<0.8 %). Furthermore, the determined concentrations of metabolites show strong agreement with certified and published concentrations of metabolites in the SRM 1950 plasma sample. We successfully annotate 71 polar metabolites, 36 acylcarnitines, 23 endocannabinoids, 42 oxylipins, and 16 fatty acids in plasma, placenta, and brain samples. The developed RP-LC/MS approach represents a robust and adaptable technique for the targeted or untargeted analysis of polar and mid-polar metabolites employing a single chromatographic column and mobile phase. This is achieved through the simple modification of the gradient program and MS conditions. Consequently, this methodology offers a highly valuable tool for conducting comprehensive, large-scale metabolomic investigations on a variety of biological samples.

Livestock-vector interaction using volatile organic metabolites

Biological interaction between two organisms living together in a given habitat is essential for healthy ecosystem functionality, got complexity, and exerts an arms race between the interacting organisms. Some vectors are exclusively blood feeders, and others supplement their diet with plant nectar. The feeding dynamics may determine their olfactory system complexity. Arthropod vectors that interact with livestock rely mainly on olfaction. Livestock odor profile is a complex trait and depends on host genetics, microbes, diet, and health status, which highlights its dynamic nature. Furthermore, volatile metabolites are shared between host animals, which exert its own challenge for vectors to find their preferred host. Elucidating the underlying host chemodiversity, especially signature scents, neuroethological mechanism of discrimination of preferred/unpreferred host from plethora of coexisting host is crucial to understand evolution and adaptation in vector-livestock interaction.

Multiplatform metabolomic interlaboratory study of a whole human stool candidate reference material from omnivore and vegan donors

INTRODUCTION

Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.

OBJECTIVES

This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.

METHODS

An interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR).

RESULTS

Different laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC-MS), 58% (GC-MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques.

CONCLUSION

This collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies.

Reference Materials for Improving Reliability of Multiomics Profiling

High-throughput technologies for multiomics or molecular phenomics profiling have been extensively adopted in biomedical research and clinical applications, offering a more comprehensive understanding of biological processes and diseases. Omics reference materials play a pivotal role in ensuring the accuracy, reliability, and comparability of laboratory measurements and analyses. However, the current application of omics reference materials has revealed several issues, including inappropriate selection and underutilization, leading to inconsistencies across laboratories. This review aims to address these concerns by emphasizing the importance of well-characterized reference materials at each level of omics, encompassing (epi-)genomics, transcriptomics, proteomics, and metabolomics. By summarizing their characteristics, advantages, and limitations along with appropriate performance metrics pertinent to study purposes, we provide an overview of how omics reference materials can enhance data quality and data integration, thus fostering robust scientific investigations with omics technologies.

Multi-omics analyses reveal rumen microbes and secondary metabolites that are unique to livestock species

Ruminant livestock, including cattle, sheep, goats, and camels, possess a distinctive digestive system with complex microbiota communities critical for feed conversion and secondary metabolite production, including greenhouse gases. Yet, there is limited knowledge regarding the diversity of rumen microbes and metabolites benefiting livestock physiology, productivity, climate impact, and defense mechanisms across ruminant species. In this study, we utilized metataxonomics and metabolomics data from four evolutionarily distinct livestock species, which had fed on diverse plant materials like grass, shrubs, and acacia trees, to uncover the unique signature microbes and secondary metabolites. We established the presence of a distinctive anaerobic fungus called Oontomyces in camels, while cattle exhibited a higher prevalence of unique microbes like Psychrobacter, Anaeromyces, Cyllamyces, and Orpinomyces. Goats hosted Cleistothelebolus, and Liebetanzomyces was unique to sheep. Furthermore, we identified a set of conserved core microbes, including Prevotella, Rickenellaceae, Cladosporium, and Pecoramyces, present in all the ruminants, irrespective of host genetics and dietary composition. This underscores their indispensable role in maintaining crucial physiological functions. Regarding secondary metabolites, camel's rumen is rich in organic acids, goat's rumen is rich in alcohols and hydrocarbons, sheep's rumen is rich in indoles, and cattle's rumen is rich in sesquiterpenes. Additionally, linalool propionate and terpinolene were uniquely found in sheep rumen, while valencene was exclusive to cattle. This may suggest the existence of species-specific microbes and metabolites that require host rumen-microbes' environment balance. These results have implications for manipulating the rumen environment to target specific microbes and secondary metabolite networks, thereby enhancing livestock productivity, resilience, reducing susceptibility to vectors, and environmentally preferred livestock husbandry.IMPORTANCERumen fermentation, which depends on feed components and rumen microbes, plays a crucial role in feed conversion and the production of various metabolites important for the physiological functions, health, and environmental smartness of ruminant livestock, in addition to providing food for humans. However, given the complexity and variation of the rumen ecosystem and feed of these various livestock species, combined with inter-individual differences between gut microbial communities, how they influence the rumen secondary metabolites remains elusive. Using metagenomics and metabolomics approaches, we show that each livestock species has a signature microbe(s) and secondary metabolites. These findings may contribute toward understanding the rumen ecosystem, microbiome and metabolite networks, which may provide a gateway to manipulating rumen ecosystem pathways toward making livestock production efficient, sustainable, and environmentally friendly.

Quartet metabolite reference materials for inter-laboratory proficiency test and data integration of metabolomics profiling

BACKGROUND

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets.

RESULTS

As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols.

CONCLUSIONS

Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.

Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

Saliva Metabolomic Profile in Dental Medicine Research: A Narrative Review

Metabolomic research tends to increase in popularity over the years, leading to the identification of new biomarkers related to specific health disorders. Saliva is one of the most newly introduced and systematically developed biofluids in the human body that can serve as an informative substance in the metabolomic profiling armamentarium. This review aims to analyze the current knowledge regarding the human salivary metabolome, its alterations due to physiological, environmental and external factors, as well as the limitations and drawbacks presented in the most recent research conducted, focusing on pre—analytical and analytical workflows. Furthermore, the use of the saliva metabolomic profile as a promising biomarker for several oral pathologies, such as oral cancer and periodontitis will be investigated.

What if using certified reference materials (CRMs) was a requirement to publish in analytical/bioanalytical chemistry journals?

Certified reference materials (CRMs) are routinely used by analytical chemists to validate new analytical methods and to demonstrate the quality of their quantitative measurements. Even though CRMs for trace element and trace organic analysis have been available and widely used for over 50 years, the majority of papers published in analytical chemistry journals do not mention the use of CRMs. What if analytical/bioanalytical chemistry journals required the use of CRMs to publish a paper? This feature article attempts to address this question by providing examples of recent papers that have made exceptional use of CRMs to validate new analytical methods and to describe novel, alternative uses of CRMs that provide new characterization of the CRM. The potential benefits of using a CRM even when it does not have certified values for the analytes of interest are presented.

Salivary Metabolomics for Oral Cancer Detection: A Narrative Review

The development of low- or non-invasive screening tests for cancer is crucial for early detection. Saliva is an ideal biofluid containing informative components for monitoring oral and systemic diseases. Metabolomics has frequently been used to identify and quantify numerous metabolites in saliva samples, serving as novel biomarkers associated with various conditions, including cancers. This review summarizes the recent applications of salivary metabolomics in biomarker discovery in oral cancers. We discussed the prevalence, epidemiologic characteristics, and risk factors of oral cancers, as well as the currently available screening programs, in India and Japan. These data imply that the development of biomarkers by itself is inadequate in cancer detection. The use of current diagnostic methods and new technologies is necessary for efficient salivary metabolomics analysis. We also discuss the gap between biomarker discovery and nationwide screening for the early detection of oral cancer and its prevention.

The Human Meconium Metabolome and Its Evolution during the First Days of Life

Meconium represents the first newborn stools, formed from the second month of gestation and excreted in the first days after birth. As an accumulative and inert matrix, it accumulates most of the molecules transferred through the placenta from the mother to the fetus during the last 6 months of pregnancy, and those resulting from the metabolic activities of the fetus. To date, only few studies dealing with meconium metabolomics have been published. In this study, we aimed to provide a comprehensive view of the meconium metabolic composition using 33 samples collected longitudinally from 11 healthy newborns and to analyze its evolution during the first 3 days of life. First, a robust and efficient methodology for metabolite extraction was implemented. Data acquisition was performed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), using two complementary LC-HRMS conditions. Data preprocessing and treatment were performed using the Workflow4Metabolomics platform and the metabolite annotation was performed using our in-house database by matching accurate masses, retention times, and MS/MS spectra to those of pure standards. We successfully identified up to 229 metabolites at a high confidence level in human meconium, belonging to diverse chemical classes and from different origins. A progressive evolution of the metabolic profile was statistically evidenced, with sugars, amino acids, and some bacteria-derived metabolites being among the most impacted identified compounds. Our implemented analytical workflow allows a unique and comprehensive description of the meconium metabolome, which is related to factors, such as maternal diet and environment.

Characterization of key lipids for binding and generating aroma compounds in roasted mutton by UPLC-ESI-MS/MS and Orbitrap Exploris GC

Lipids are the key aroma formation substrates and retainers relevant to the flavor quality. The lipids in the roasted mutton were investigated by UPLC-ESI-MS/MS and Orbitrap Exploris GC. The results showed that a total of 2488 lipids from 24 subclasses were identified in the roasted mutton, including 28.21% triglyceride (TG), 14.87% phosphatidylcholine (PC), and 11.03% phosphatidylethanolamine (PE). TG (16:0_18:1_18:1) and TG (18:0_18:0_18:1) might be the predominant lipids for binding aroma compounds. 488 Differential lipids from 20 subclasses were observed based on VIP > 1 and p < 0.05. The 61 out of 488 differential lipids, especially PC and PE, might predominantly contribute to the formation of aroma compounds. A total of 13 aroma compounds were determined as the characteristic odorants in the roasted mutton, including hexanal, heptanal, and 1-octen-3-ol. PC (30: 6) and PC (28: 3) were the potential markers for the discrimination of roasted mutton.