The maternal serum metabolome by multisegment injection-capillary electrophoresis-mass spectrometry: a high-throughput platform and standardized data workflow for large-scale epidemiological studies

Rapid normalization of vitamin D deficiency in PICU (VITdALIZE-KIDS): study protocol for a phase III, multicenter randomized controlled trial

BACKGROUND

The rate of vitamin D deficiency (VDD) in critically ill children worldwide has been estimated at 50%. These children are at risk of multiple organ dysfunction, chronic morbidity, and decreased health related quality of life (HRQL). Pediatric and adult ICU clinical trials suggest that VDD is associated with worse clinical outcomes, although data from supplementation trials are limited and inconclusive. Our group's phase II multicenter dose evaluation pilot study established the efficacy and safety of an enteral weight-based cholecalciferol loading dose to rapidly restore vitamin D levels in critically ill children.

METHODS

Our aim is to evaluate the impact of this dosing regimen on clinical outcomes. VITdALIZE-KIDS is a pragmatic, phase III, multicenter, double-blind RCT aiming to randomize 766 critically ill children from Canadian PICUs. Participants are randomized using a 1:1 scheme to receive a single dose at enrollment of enteral cholecalciferol (10,000 IU/kg, max 400,000 IU) or placebo. Eligibility criteria include critically ill children aged newborn (> 37 weeks corrected gestational age) to < 18 years who have blood total 25-hydroxyvitamin D < 50 nmol/L. The primary objective is to determine if rapid normalization of vitamin D status improves HRQL at 28 days following enrollment. The secondary objective is to evaluate the impact of rapid normalization of vitamin D status on multiple organ dysfunction. The study includes additional tertiary outcomes including functional status, HRQL and mortality at hospital discharge and 90 days, PICU and hospital length of stay, and adverse events related to vitamin D toxicity. Additionally, we are performing comprehensive vitamin D speciation and non-targeted metabolite profiling as part of a sub-study for the first 100 participants from whom an enrollment and at least one post-intervention blood and urine sample were obtained.

DISCUSSION

The VITdALIZE-KIDS trial is the first phase III, multicenter trial to evaluate whether rapid normalization of vitamin D status could represent a simple, inexpensive, and safe means of improving outcomes following pediatric critical illness. Recruitment was initiated in June 2019 and is expected to continue to March 2026.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT03742505. Study first submitted on November 12, 2018 https://clinicaltrials.gov/study/NCT03742505.

Capillary electrophoresis-mass spectrometry for creatinine analysis in residual clinical plasma samples and comparison with gold standard assay

When hospitalized, infants, particularly preterm, are often subjected to multiple painful needle procedures to collect sufficient blood for metabolic screening or diagnostic purposes using standard clinical tests. For example, at least 100 µL of whole blood is required to perform one creatinine plasma measurement with enzymatic colorimetric assays. As capillary electrophoresis-mass spectrometry (CE-MS) utilizing a sheathless porous tip interface only requires limited amounts of sample for in-depth metabolic profiling studies, the aim of this work was to assess the utility of this method for the determination of creatinine in low amounts of plasma using residual blood samples from adults and infants. By using a starting amount of 5 µL of plasma and an injection volume of only 6.7 nL, a detection limit (S/N = 3) of 30 nM could be obtained for creatinine, and intra- and interday precisions (for peak area ratios) were below 3.2%. To shorten the electrophoretic separation time, a multi-segment injection (MSI) strategy was employed to analyze up to seven samples in one electrophoretic run. The findings obtained by CE-MS for creatinine in pretreated plasma were compared with the values acquired by an enzymatic colorimetric assay typically used in clinical laboratories for this purpose. The comparison revealed that CE-MS could be used in a reliable way for the determination of creatinine in residual plasma samples from infants and adults. Nevertheless, to underscore the clinical efficacy of this method, a subsequent investigation employing an expanded pool of plasma samples is imperative. This will not only enhance the method's diagnostic utility but also contribute to minimizing both the amount and frequency of blood collection required for diagnostic purposes.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Comparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

Multi-biomarker combination detection system for diagnosis and classification of dry eye disease by imaging of a multi-channel metasurface

Dry eye disease (DED) is one of the most common ocular surface diseases, characterized by unstable tear film and ocular inflammation, affecting hundreds of millions of people worldwide. Currently, the clinical diagnosis of DED mainly relies on physical methods such as optical microscopy and ocular surface interferometric imaging, but classifying DED is still difficult. Here, we propose a compact and portable immune detection system based on the direct imaging of a nanophotonic metasurface with gradient geometry, for fast and ultra-sensitive detection of multiple biomarkers (i.e. Matrix metalloproteinase-9 (MMP-9), Lipocalin-1 (LCN-1), Lactoferrin (LTF)) in tears for the diagnosis and classification of DED. This centimeter-scale concentric nanophotonic metasurface, which consists of millions of unique metallic nanostructures, was fabricated through a cost-effective nanoimprint lithography (NIL) process. The immune detection system based on the antibody-modified metasurface shows favorable detection selectivity, an ultra-high sensitivity (3350 pixels/Refractive Index Unit (RIU)) and low limit of detection (LOD) (0.3 ng/mL for MMP-9, 1 ng/mL for LTF, and 0.5 ng/mL for LCN-1). Further clinical sampling and detection results demonstrated that this multi-biomarker detection system enabled accurate determination and symptom classification of DED, manifesting high correlation and consistency with clinical diagnosis results. The advantages such as low sample consumption, one-step detection, simple operation, and simultaneous detection of multiple biomarkers make the platform promising for screening and detecting a broader range of biomarker combinations in clinical practice.

Application of a capillary electrophoresis-mass spectrometry metabolomics workflow in zebrafish larvae reveals new effects of cortisol

In contemporary biomedical research, the zebrafish (Danio rerio) is increasingly considered a model system, as zebrafish embryos and larvae can (potentially) fill the gap between cultured cells and mammalian animal models, because they can be obtained in large numbers, are small and can easily be manipulated genetically. Given that capillary electrophoresis-mass spectrometry (CE-MS) is a useful analytical separation technique for the analysis of polar ionogenic metabolites in biomass-limited samples, the aim of this study was to develop and assess a CE-MS-based analytical workflow for the profiling of (endogenous) metabolites in extracts from individual zebrafish larvae and pools of small numbers of larvae. The developed CE-MS workflow was used to profile metabolites in extracts from pools of 1, 2, 4, 8, 12, 16, 20, and 40 zebrafish larvae. For six selected endogenous metabolites, a linear response (R2  > 0.98) for peak areas was obtained in extracts from these pools. The repeatability was satisfactory, with inter-day relative standard deviation values for peak area of 9.4%-17.7% for biological replicates (n = 3 over 3 days). Furthermore, the method allowed the analysis of over 70 endogenous metabolites in a pool of 12 zebrafish larvae, and 29 endogenous metabolites in an extract from only 1 zebrafish larva. Finally, we applied the optimized CE-MS workflow to identify potential novel targets of the mineralocorticoid receptor in mediating the effects of cortisol.

Expanding Lipidomic Coverage in Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry via a Convenient and Quantitative Methylation Strategy

Orthogonal separation techniques coupled to high-resolution mass spectrometry are required for characterizing the human lipidome, given its inherent chemical and structural complexity. However, electrophoretic separations remain largely unrecognized in contemporary lipidomics research compared to established chromatographic and ion mobility methods. Herein, we introduce a novel derivatization protocol based on 3-methyl-1-p-tolyltriazene (MTT) as a safer alternative to diazomethane for quantitative phospholipid (PL) methylation (∼90%), which enables their rapid analysis by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS). Isobaric interferences and ion suppression effects were minimized by performing an initial reaction using 9-fluorenylmethyoxycarbonyl chloride prior to MTT and a subsequent back extraction in hexane. This charge-switch derivatization strategy expands lipidome coverage when using MSI-NACE-MS under positive ion mode with improved resolution, greater sensitivity, and higher throughput (∼3.5 min/sample), notably for zwitterionic PLs that are analyzed as their cationic phosphate methyl esters. Our method was validated by analyzing methyl-tert-butyl ether extracts of reference human plasma, which enabled a direct comparison of 48 phosphatidylcholine and 27 sphingomyelin species previously reported in an interlaboratory lipidomics harmonization study. The potential for plasma PL quantification by MSI-NACE-MS via a serial dilution of NIST SRM-1950 was also demonstrated based on estimation of relative response factors using their reported consensus concentrations. Moreover, lipid identification was supported by modeling predictable changes in the electrophoretic mobility for cationic PLs in conjunction with MS/MS. Overall, this work offers a practical derivatization protocol to expand lipidome coverage in CE-MS beyond the analysis of hydrophilic/polar metabolites under aqueous buffer conditions.

Urinary Metabolite Profiling to Non-Invasively Monitor the Omega-3 Index: An Exploratory Secondary Analysis of a Randomized Clinical Trial in Young Adults

The Omega-3 Index (O3I) reflects eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in erythrocytes. While the O3I is associated with numerous health outcomes, its widespread use is limited. We investigated whether urinary metabolites could be used to non-invasively monitor the O3I in an exploratory analysis of a previous placebo-controlled, parallel arm randomized clinical trial in males and females (n = 88) who consumed either ~3 g/d olive oil (OO; control), EPA, or DHA for 12 weeks. Fasted blood and first-void urine samples were collected at baseline and following supplementation, and they were analyzed via gas chromatography and multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), respectively. We tentatively identified S-carboxypropylcysteamine (CPCA) as a novel urinary biomarker reflecting O3I status, which increased following both EPA and DHA (p < 0.001), but not OO supplementation, and was positively correlated to the O3I (R = 0.30, p < 0.001). Additionally, an unknown dianion increased following DHA supplementation, but not EPA or OO. In ROC curve analyses, CPCA outperformed all other urinary metabolites in distinguishing both between OO and EPA or DHA supplementation groups (AUC > 80.0%), whereas the unknown dianion performed best in discriminating OO from DHA alone (AUC = 93.6%). Candidate urinary biomarkers of the O3I were identified that lay the foundation for a non-invasive assessment of omega-3 status.

A comparison of hydrophilic interaction liquid chromatography and capillary electrophoresis for the metabolomics analysis of human serum

Cationic, anionic, zwitterionic and, partially polar metabolites are very important constituents of blood serum. Several of these metabolites underpin the core metabolism of cells (e.g., Krebs cycle, urea cycle, proteins synthesis, etc.), while others might be considered ancillary but still important to grasp the status of any organism through blood serum analysis. Due to its wide chemical diversity, modern metabolomics analysis of serum is still struggling to provide a complete and comprehensive picture of the polar metabolome, due to the limitations of each specific analytical method. In this study, two metabolomics-based analytical methods using the most successful techniques for polar compounds separation in human serum samples, namely hydrophilic interaction liquid chromatography (HILIC) and capillary electrophoresis (CE), are evaluated, both coupled to a high-resolution time-of-flight mass spectrometer via electrospray ionization (ESI-Q-TOF-MS). The performance of the two methods have been compared using five terms of comparison, three of which are specific to metabolomics, such as (1) compounds' detectability (2) Pezzatti score (Pezzatti et al. 2018), (3) intra-day precision (repeatability), (4) ease of automatic analysis of the data (through a common deconvolution alignment and extrapolation software, MS-DIAL, and (5) time & cost analysis. From this study, HILIC-MS proved to be a better tool for polar metabolome analysis, while CE-MS helped identify some interesting variables that gave it interest in completing metabolome coverage in metabolomics studies. Finally, in this framework, MS-DIAL demonstrates for the first time its ability to process CE data for metabolomics, although it is not designed for it.

Strategies for capillary electrophoresis: Method development and validation for pharmaceutical and biological applications-Updated and completely revised edition

This review is in support of the development of selective, precise, fast, and validated capillary electrophoresis (CE) methods. It follows up a similar article from 1998, Wätzig H, Degenhardt M, Kunkel A. "Strategies for capillary electrophoresis: method development and validation for pharmaceutical and biological applications," pointing out which fundamentals are still valid and at the same time showing the enormous achievements in the last 25 years. The structures of both reviews are widely similar, in order to facilitate their simultaneous use. Focusing on pharmaceutical and biological applications, the successful use of CE is now demonstrated by more than 600 carefully selected references. Many of those are recent reviews; therefore, a significant overview about the field is provided. There are extra sections about sample pretreatment related to CE and microchip CE, and a completely revised section about method development for protein analytes and biomolecules in general. The general strategies for method development are summed up with regard to selectivity, efficiency, precision, analysis time, limit of detection, sample pretreatment requirements, and validation.

Integrative multiomics analysis of infant gut microbiome and serum metabolome reveals key molecular biomarkers of early onset childhood obesity

Evidence supports a complex interplay of gut microbiome and host metabolism as regulators of obesity. The metabolic phenotype and microbial metabolism of host diet may also contribute to greater obesity risk in children early in life. This study aimed to identify features that discriminated overweight/obese from normal weight infants by integrating gut microbiome and serum metabolome profiles. This prospective analysis included 50 South Asian children living in Canada, selected from the SouTh Asian biRth cohorT (START). Serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry and the relative abundance of bacterial 16S rRNA gene amplicon sequence variant was evaluated at 1 year. Cumulative body mass index (BMI_AUC) and skinfold thickness (SSF_AUC) scores were calculated from birth to 3 years as the total area under the growth curve (AUC). BMI_AUC and/or SSF_AUC >85th percentile was used to define overweight/obesity. Data Integration Analysis for Biomarker discovery using Latent cOmponent (DIABLO) was used to identify discriminant features associated with childhood overweight/obesity. The associations between identified features and anthropometric measures were examined using logistic regression. Circulating metabolites including glutamic acid, acetylcarnitine, carnitine, and threonine were positively, whereas γ-aminobutyric acid (GABA), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were negatively associated with childhood overweight/obesity. The abundance of the Pseudobutyrivibrio and Lactobacillus genera were positively, and Clostridium sensu stricto 1 and Akkermansia were negatively associated with childhood overweight/obesity. Integrative analysis revealed that Akkermansia was positively whereas Lactobacillus was inversely correlated with GABA and SDMA, and Pseudobutyrivibrio was inversely correlated with GABA. This study provides insights into metabolic and microbial signatures which may regulate satiety, energy metabolism, inflammatory processes, and/or gut barrier function, and therefore, obesity trajectories in childhood. Understanding the functional capacity of these molecular features and potentially modifiable risk factors such as dietary exposures early in life may offer a novel approach for preventing childhood obesity.

Early sex-dependent differences in metabolic profiles of overweight and adiposity in young children: a cross-sectional analysis

BACKGROUND

Childhood obesity is a global health concern and can lead to lifetime cardiometabolic disease. New advances in metabolomics can provide biochemical insights into the early development of obesity, so we aimed to characterize serum metabolites associated with overweight and adiposity in early childhood and to stratify associations by sex.

METHODS

Nontargeted metabolite profiling was conducted in the Canadian CHILD birth cohort (discovery cohort) at age 5 years (n = 900) by multisegment injection-capillary electrophoresis-mass spectrometry. Clinical outcome was defined using novel combined measures of overweight (WHO-standardized body mass index ≥ 85th percentile) and/or adiposity (waist circumference ≥ 90th percentile). Associations between circulating metabolites and child overweight/adiposity (binary and continuous outcomes) were determined by multivariable linear and logistic regression, adjusting for covariates and false discovery rate, and by subsequent sex-stratified analysis. Replication was assessed in an independent replication cohort called FAMILY at age 5 years (n = 456).

RESULTS

In the discovery cohort, each standard deviation (SD) increment of branched-chain and aromatic amino acids, glutamic acid, threonine, and oxoproline was associated with 20-28% increased odds of overweight/adiposity, whereas each SD increment of the glutamine/glutamic acid ratio was associated with 20% decreased odds. All associations were significant in females but not in males in sex-stratified analyses, except for oxoproline that was not significant in either subgroup. Similar outcomes were confirmed in the replication cohort, where associations of aromatic amino acids, leucine, glutamic acid, and the glutamine/glutamic acid ratio with childhood overweight/adiposity were independently replicated.

CONCLUSIONS

Our findings show the utility of combining measures of both overweight and adiposity in young children. Childhood overweight/adiposity at age 5 years has a specific serum metabolic phenotype, with the profile being more prominent in females compared to males.

High-throughput capillary electrophoresis analysis of biopharmaceuticals utilizing sequential injections

The complexity of biotherapeutic products implies an ever-increasing list of product quality attributes that need to be monitored and characterized. In addition, the growing interest in implementing process analytical technology in biopharmaceutical production has further increased the testing burden, together with the need for rapid testing that can facilitate real-time or near-real-time decision-making. Capillary electrophoresis (CE) has made a place in biopharmaceutical analysis but is regarded as a low-throughput method, with the instrument dead time constituting more than 80% of the total time of analysis. In this study, the dead time of CE was utilized to analyse 3 mAb samples in a single-CE run. This approach resulted in an up to 77% reduction in the total analysis time and increased the productivity by up to 300%, compared to traditional single CE-ultraviolet runs, without compromising resolution or relative peak areas. Additionally, good method reproducibility was observed. The compatibility of the method has been demonstrated with protein A eluate and cation exchange chromatography fractions. We, thus, propose that sequential injections can be applied for fast and robust CE analysis of biopharmaceuticals.

Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer

Cis-diol metabolic reprogramming evolves during primary liver cancer (PLC) initiation and progression. However, owing to the low concentrations and highly structural heterogeneity of cis-diols in vivo, severe interference from complex biofluids and limited profiling coverage of existing methods, in-depth profiling of cis-diol metabolites and linking their specific changes with PLC remain challenging. Besides, due to the low specificity of widely used protein biomarkers, accurate classification of PLC from hepatitis still represents an unmet need in clinical diagnostics. Herein, to high-coverage profile cis-diols and explore the translational potential of them as biomarkers, a machine learning-empowered boronate affinity extraction-solvent evaporation assisted enrichment-mass spectrometry (MLE-BESE-MS) was developed. A single analytical platform integrated with multiple complementary functions, including pH-controlled boronate affinity extraction, solvent evaporation-assisted enrichment and nanoelectrospray ionization-based cis-diol identification, was constructed, which significantly improved the metabolite coverage. Meanwhile, by virtue of machine learning (principal components analysis, orthogonal partial least-squares discrimination analysis and random forest), collected cis-diols were statistically screened to extract efficient features for precise PLC diagnosis, and the results outperform the routinely used protein biomarker-based methods both in sensitivity (87.5% vs. less than 70%) and specificity (85.7% vs. ca. 80%). This machine learning-empowered integrated MS platform advanced the targeted metabolic analysis for early cancer diagnosis, rendering great promise for clinical translation.

Parenteral BCG vaccine induces lung-resident memory macrophages and trained immunity via the gut-lung axis

Aside from centrally induced trained immunity in the bone marrow (BM) and peripheral blood by parenteral vaccination or infection, evidence indicates that mucosal-resident innate immune memory can develop via a local inflammatory pathway following mucosal exposure. However, whether mucosal-resident innate memory results from integrating distally generated immunological signals following parenteral vaccination/infection is unclear. Here we show that subcutaneous Bacillus Calmette-Guérin (BCG) vaccination can induce memory alveolar macrophages (AMs) and trained immunity in the lung. Although parenteral BCG vaccination trains BM progenitors and circulating monocytes, induction of memory AMs is independent of circulating monocytes. Rather, parenteral BCG vaccination, via mycobacterial dissemination, causes a time-dependent alteration in the intestinal microbiome, barrier function and microbial metabolites, and subsequent changes in circulating and lung metabolites, leading to the induction of memory macrophages and trained immunity in the lung. These data identify an intestinal microbiota-mediated pathway for innate immune memory development at distal mucosal tissues and have implications for the development of next-generation vaccine strategies against respiratory pathogens.

LargeMetabo: an out-of-the-box tool for processing and analyzing large-scale metabolomic data

Large-scale metabolomics is a powerful technique that has attracted widespread attention in biomedical studies focused on identifying biomarkers and interpreting the mechanisms of complex diseases. Despite a rapid increase in the number of large-scale metabolomic studies, the analysis of metabolomic data remains a key challenge. Specifically, diverse unwanted variations and batch effects in processing many samples have a substantial impact on identifying true biological markers, and it is a daunting challenge to annotate a plethora of peaks as metabolites in untargeted mass spectrometry-based metabolomics. Therefore, the development of an out-of-the-box tool is urgently needed to realize data integration and to accurately annotate metabolites with enhanced functions. In this study, the LargeMetabo package based on R code was developed for processing and analyzing large-scale metabolomic data. This package is unique because it is capable of (1) integrating multiple analytical experiments to effectively boost the power of statistical analysis; (2) selecting the appropriate biomarker identification method by intelligent assessment for large-scale metabolic data and (3) providing metabolite annotation and enrichment analysis based on an enhanced metabolite database. The LargeMetabo package can facilitate flexibility and reproducibility in large-scale metabolomics. The package is freely available from https://github.com/LargeMetabo/LargeMetabo.

Metabonomics profile analysis in inflammation-induced preterm birth and the potential role of metabolites in regulating premature cervical ripening

BACKGROUND

Preterm birth (PTB) is the primary cause of infant morbidity and mortality. Moreover, previous studies have established that PTB is related to premature cervical ripening. However, the underlying mechanism remains to be elucidated. This study sought to identify differentially expressed metabolites and investigate their potential biological functions in PTB.

METHODS

Pregnant C57BL/6 J mice were treated with either LPS or normal saline and cervical alterations before labor were detected by staining. Metabolic profiles in the plasma of PTB and control mice were examined through non-targeted metabonomics analyses, quantitative polymerase chain reaction and immunofluorescence staining were performed on human cervical smooth cells.

RESULTS

The study demonstrated that the mRNA and protein levels of α-SMA, SM-22, and calponin in cervical smooth muscle cells of PTB mice were lower while OR was higher at both mRNA and protein levels compared to the CTL group. A total of 181 differentially expressed metabolites were analyzed, among them, 96 were upregulated, while 85 were downregulated in the PTB group. Differentially expressed metabolites may play a role in STAT3, RhoA, mTOR, TGF-β, and NK-κB signaling pathways. Furthermore, when treated with taurine, the levels of α-SMA and SM-22 in human cervical smooth muscle cells were elevated, whereas that of connexin-43 was decreased.

CONCLUSION

Our study highlighted the changes of metabolites in the peripheral blood changed prior to PTB and revealed that these differentially expressed metabolites might participate in the development of premature cervical ripening. Taurine was identified as an important metabolite may modulate human cervical smooth muscle cells. Our study provided new insights into the mechanism underlying premature cervical ripening in PTB.

[Annual review of capillary electrophoresis technology in 2021]

This paper provides an annual review of capillary electrophoresis (CE) technology in 2021. A total of 291 research papers related to CE technology published in 2021 were retrieved from the ISI Web of Science using the keywords, "capillary electrophoresis-mass spectrometry" "capillary isoelectric focusing" "micellar electrokinetic chromatography", or "capillary electrophoresis" (not "capillary electrochromatography" "microchip" and "capillary monolithic column"). In addition, nine research papers related to CE technology in Chinese journals were reviewed: Chinese Journal of Chromatography and Chinese Journal of Analytical Chemistry. This review focused on seven papers published in Coordination Chemistry Reviews, Angewandte Chemie-International Edition, Nature Protocols, TrAC-Trends in Analytical Chemistry, and Signal Transduction and Targeted Therapy with impact factors (IFs) greater than 10.0, as well as 42 papers reported in Analytical Chemistry, Analytica Chimica Acta, Talanta, and Food Chemistry with IFs between 5.0 and 10.0. This review also provides a comprehensive overview of representative CE works in Journal of Chromatography A and Electrophoresis with IFs<5.0, as well as important Chinese journals, Chinese Journal of Chromatography and Chinese Journal of Analytical Chemistry. According to the IF, this paper introduces the representative work of CE-related papers to allow readers to quickly understand the important research progress of CE technology in the past year.

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease.

Enhanced Sample Throughput Capillary Zone Electrophoresis with UV Detection in Hydrodynamically Closed System for Determination of Ibuprofen

A simple analytical approach based on capillary zone electrophoresis with ultraviolet detection and repeated sample injection strategy (applied in a hydrodynamically closed separation system for the first time) was developed for the determination of ibuprofen (IBU) in commercially available pharmaceutical preparations. The proposed method was characterized by significantly increased sample throughput and favorable validation parameters, highly demanded in routine quality control laboratories. The limit of detection was predicted at the concentration level of 0.31 µg/mL. Intra-day precision expressed as the relative standard deviation of IBU concentration ranged from 1.9 to 5.6%, and corresponding intra-day accuracy expressed as the relative error was in the interval of 87.1–106.5%. Inter-day precision was in the range of 2.6–15.0%, and inter-day accuracy was 94.9–102.7%. The developed method was able to quantify IBU in complex pharmaceutical matrices represented by commercially available tablets and oral suspension. The determined contents of IBU in the tested dosage forms were in good agreement with the manufacturer’s declaration. The analytical performance of the developed method was evaluated according to the innovative RGB Additive Color Model strategy. It was demonstrated that the proposed method is characterized by very good analytical performance parameters, safety and eco-friendliness, and practical effectiveness.

Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories

In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories.

Non-esterified fatty acids as biomarkers of diet and glucose homeostasis in pregnancy: The impact of fatty acid reporting methods: NEFA reporting methods affect dietary and cardiometabolic endpoints

BACKGROUND

Sparse data exists on the utility of individual serum non-esterified fatty acids (NEFAs) as clinical and dietary biomarkers and how reporting methods could affect these associations. We investigated the associations of 19 serum NEFAs expressed as µM or mol%, with self-reported dietary intake data, and cardiometabolic health indicators in pregnant women.

METHODS

In this cross-sectional study, 273 pregnant women in their second trimester each completed a semi-quantitative food-frequency questionnaire and provided fasting serum samples. Comprehensive serum NEFA analysis was performed by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry. We evaluated the associations of NEFAs using two different reporting methods, with diet quality, specific foods intake, and measures of adiposity and glucose homeostasis.

RESULTS

Consistently stronger dietary correlations were observed when expressed as mol%. Serum ω-3 NEFAs were associated with diet quality and fish/fish oil daily servings (DHA mol%, r= 0.37; p = 4.8e-10), and odd-chain NEFAs were associated with full-fat dairy intake (15:0 mol%, r = 0.23; p = 9.0e-5). Glucose intolerance was positively associated with odd chain NEFAs as expressed in µM (r = 0.21; p= 0.001) but inversely associated when expressed as mol% (r = -0.31; p= 2.2e-7). In contrast, monounsaturated NEFAs (µM and mol%) had robust positive associations with pre-pregnancy BMI, second trimester skin-fold thickness, glycated hemoglobin, fasting glucose, and glucose intolerance.

CONCLUSIONS

This study demonstrates the utility of specific NEFAs and their sub-classes as viable dietary and clinical biomarkers when reported as their relative proportions. More research is needed to investigate inconsistencies between absolute concentrations and relative proportions when reporting fatty acids.

Nontargeted Serum Lipid Profiling of Nonalcoholic Steatohepatitis by Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry: A Multiplexed Separation Platform for Resolving Ionic Lipids

New methods are needed for global lipid profiling due to the complex chemical structures and diverse physicochemical properties of lipids. Herein we introduce a robust data workflow to unambiguously select lipid features from serum ether extracts by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS). An iterative three-stage screening strategy is developed for nontargeted lipid analyses when using multiplexed electrophoretic separations coupled to an Orbitrap mass analyzer under negative ion mode. This approach enables the credentialing of 270 serum lipid features annotated based on their accurate mass and relative migration time, including 128 ionic lipids reliably measured (median CV ≈ 13%) in most serum samples (>75%) from nonalcoholic steatohepatitis (NASH) patients (n = 85). A mobility map is introduced to classify charged lipid classes over a wide polarity range with selectivity complementary to chromatographic separations, including lysophosphatidic acids, phosphatidylcholines, phosphatidylinositols, phosphatidylethanolamines, and nonesterified fatty acids (NEFAs). Serum lipidome profiles were also used to differentiate high- from low-risk NASH patients using a k-means clustering algorithm, where elevated circulating NEFAs (e.g., palmitic acid) were associated with increased glucose intolerance, more severe liver fibrosis, and greater disease burden. MSI-NACE-MS greatly expands the metabolome coverage of conventional aqueous-based CE-MS protocols and is a promising platform for large-scale lipidomic studies.

Capillary Electrophoresis-Mass Spectrometry with Multisegment Injection and In-Capillary Preconcentration for High-Throughput and Sensitive Determination of Therapeutic Decapeptide Triptorelin in Pharmaceutical and Biological Matrices

A capillary electrophoresis-tandem mass spectrometry method with a multisegment injection and an in-capillary field-enhanced sample stacking for determination of therapeutic peptide triptorelin in pharmaceutical and biological matrices was developed. The CE separation conditions were optimized in order to obtain maximal separation efficiency, analytical signal intensity and stability, and minimal adsorption of the analyzed peptide onto the capillary wall (1 M formic acid-HFo, pH 1.88). The implementation of the field-enhanced sample injection into CE improved the value of limit of detection 50 times while the multisegment injection increased the sample throughput three times in comparison to a conventional CE approach. The proposed method was characterized by favorable performance parameters, such as linearity (r2 ≥ 0.99), limit of detection (5 ng mL-1 in water matrix, 25 ng mL-1 in plasma matrix), precision (relative standard deviation, 1.5-9.4% for intraday and 2.3-11.9% for interday reproducibility), or accuracy (relative errors in the range of 80-109%). The FDA-validated method was successfully applied to the analysis of triptorelin in the commercial drug Diphereline® 0.1 mg (powder for injection) and in spiked human plasma samples. Favorable performance parameters along with proven application potentialities indicate the usefulness of the proposed method for its routine use in drug quality control laboratories and for clinical analysis, such as determination of triptorelin levels in plasma (for pharmacokinetic study).

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

A Cross-Platform Metabolomics Comparison Identifies Serum Metabolite Signatures of Liver Fibrosis Progression in Chronic Hepatitis C Patients

Metabolomics offers new insights into disease mechanisms that is enhanced when adopting orthogonal instrumental platforms to expand metabolome coverage, while also reducing false discoveries by independent replication. Herein, we report the first inter-method comparison when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) and nuclear magnetic resonance (NMR) spectroscopy for characterizing the serum metabolome of patients with liver fibrosis in chronic hepatitis C virus (HCV) infection (n = 20) and non-HCV controls (n = 14). In this study, 60 and 30 serum metabolites were detected frequently (>75%) with good technical precision (median CV < 10%) from serum filtrate samples (n = 34) when using standardized protocols for MSI-CE-MS and NMR, respectively. Also, 20 serum metabolite concentrations were consistently measured by both methods over a 500-fold concentration range with an overall mean bias of 9.5% (n = 660). Multivariate and univariate statistical analyses independently confirmed that serum choline and histidine were consistently elevated (p < 0.05) in HCV patients with late-stage (F2-F4) as compared to early-stage (F0-F1) liver fibrosis. Overall, the ratio of serum choline to uric acid provided optimal differentiation of liver disease severity (AUC = 0.848, p = 0.00766) using a receiver operating characteristic curve, which was positively correlated with liver stiffness measurements by ultrasound imaging (r = 0.606, p = 0.0047). Moreover, serum 5-oxo-proline concentrations were higher in HCV patients as compared to non-HCV controls (F = 4.29, p = 0.0240) after adjustment for covariates (age, sex, BMI), indicative of elevated oxidative stress from glutathione depletion with the onset and progression of liver fibrosis. Both instrumental techniques enable rapid yet reliable quantification of serum metabolites in large-scale metabolomic studies with good overlap for biomarker replication. Advantages of MSI-CE-MS include greater metabolome coverage, lower operating costs, and smaller sample volume requirements, whereas NMR offers a robust platform supported by automated spectral and data processing software.

Urinary Metabolites Enable Differential Diagnosis and Therapeutic Monitoring of Pediatric Inflammatory Bowel Disease

Rates of pediatric Crohn's disease (CD) and ulcerative colitis (UC) are increasing globally. Differentiation of these inflammatory bowel disease (IBD) subtypes however can be challenging when relying on invasive endoscopic approaches. We sought to identify urinary metabolic signatures of pediatric IBD at diagnosis, and during induction treatment. Nontargeted metabolite profiling of urine samples from CD (n = 18) and UC (n = 8) in a pediatric retrospective cohort study was performed using multisegment injection-capillary electrophoresis-mass spectrometry. Over 122 urinary metabolites were reliably measured from pediatric IBD patients, and unknown metabolites were identified by tandem mass spectrometry. Dynamic changes in sum-normalized urinary metabolites were also monitored following exclusive enteral nutrition (EEN) or corticosteroid therapy (CS) in repeat urine samples collected over 8 weeks. Higher urinary excretion of indoxyl sulfate, hydroxyindoxyl sulfate, phenylacetylglutamine, and sialic acid were measured in CD as compared to UC patients, but lower threonine, serine, kynurenine, and hypoxanthine (p < 0.05). Excellent discrimination of CD from UC was achieved based on the urinary serine:indoxylsulfate ratio (AUC = 0.972; p = 3.21 × 10^-5). Urinary octanoyl glucuronide, pantothenic acid, and pyridoxic acid were also identified as specific dietary biomarkers of EEN in pediatric IBD patients who achieved clinical remission. This work may complement or replace existing strategies in the diagnosis and early management of children with IBD.