The human urine metabolome

UPLC-Q-TOF/MS-Based Serum Metabolomics Reveals Potential Anti-tumor Mechanism of Banxia Xiexin Decoction in Colorectal Cancer Mice

OBJECTIVE

To clarify the potential mechanism of Banxia Xiexin Decoction (BXD) on colorectal cancer (CRC) from the perspective of metabolomics.

METHODS

Forty male C57BL/6 mice were randomly divided into normal control (NC), azoxymethane/dextran sulfate sodium (AOM/DSS) model, low-dose BXD (L-BXD), high-dose BXD (H-BXD) and mesalamine (MS) groups according to a random number table, 8 mice in each group. Colorectal cancer model was induced by AOM/DSS. BXD was administered daily at doses of 3.915 (L-BXD) and 15.66 g/kg (H-BXD) by gavage for consecutive 21 days, and 100 mg/kg MS was used as positive control. Following the entire modeling cycle, colon length of mice was measured and quantity of colorectal tumors were counted. The spleen and thymus index were determined by calculating the spleen/thymus weight to body weight. Inflammatory cytokine and changes of serum metabolites were analyzed by enzyme-linked immunosorbent assay kits and ultra performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS), respectively.

RESULTS

Notably, BXD supplementation protected against weight loss, mitigated tumor formation, and diminished histologic damage in mice treated with AOM/DSS (P<0.05 or P<0.01). Moreover, BXD suppressed expression of serum inflammatory enzymes, and improved the spleen and thymus index (P<0.05). Compared with the normal group, 102 kinds of differential metabolites were screened in the AOM/DSS group, including 48 potential biomarkers, involving 18 main metabolic pathways. Totally 18 potential biomarkers related to CRC were identified, and the anti-CRC mechanism of BXD was closely related to D-glutamine and D-glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, nitrogen metabolism and so on.

CONCLUSION

BXD exerts partial protective effects on AOM/DSS-induced CRC by reducing inflammation, protecting organism immunity ability, and regulating amino acid metabolism.

Unique urine and serum metabolomic signature in patients with excessive alcohol use: An exploratory study

BACKGROUND

Excessive alcohol consumption has a multifaceted impact on the body's metabolic pathways and organ systems. The objectives of this study were to characterize global metabolomic changes and identify specific pathways that are altered in individuals with excessive alcohol use.

METHODS

This exploratory study included 22 healthy controls with no known history of excessive alcohol use and 38 patients identified as using alcohol excessively. A Fibrosis-4 score was used to determine the risk of underlying alcohol-associated liver disease among the excessive drinkers.

RESULTS

We found significantly altered urinary and serum metabolites among excessive drinkers, affecting various metabolic pathways including the metabolism of lipids, amino acids and peptides, cofactors and vitamins, carbohydrates, and nucleotides. Levels of two steroid hormones-5alpha-androstan-3beta,17beta-diol disulfate and androstenediol (3beta,17beta) disulfate-were significantly higher in both the serum and urine samples of excessive drinkers. These elevated levels may be associated with a higher risk of liver fibrosis in individuals with excessive alcohol use.

CONCLUSION

Alcohol consumption leads to marked alterations in multiple metabolic pathways, highlighting the systemic impact of alcohol on various tissues and organ systems. These findings provide a foundation for future mechanistic studies aimed at elucidating alcohol-induced changes in these metabolic pathways and their implications.

Metabolic biomarkers in irritable bowel syndrome diagnosis

Irritable bowel syndrome (IBS) is a chronic gastrointestinal (GI) disorder characterized by altered bowel habits and abdominal discomfort during defecation. It significantly impacts life quality and work productivity for those affected. Global data suggests a slightly higher prevalence in females than in males. Today, unambiguous diagnosis of IBS remains challenging due to the absence of a specific biochemical, histopathological, or radiological test. Current diagnosis relies heavily on thorough symptom evaluation. Efforts by the Rome committees have established standardized diagnostic criteria (Rome I-IV), improving consistency and clinical applicability. Recent studies in this framework, seem to have successfully employed metabolomics techniques to identify distinct metabolite profiles in breath and stool samples of IBS patients, differentiating them from healthy controls and those with other functional GI disorders, such as inflammatory bowel disease (IBD). Building on this success, researchers are investigating the presence of similar metabolites in easily accessible biofluids such as urine, potentially offering a less invasive diagnostic approach. Accordingly, this review focuses on key metabolites specifically detected in IBS patients' biological specimens, with a focus on urinary metabolites, using various methods, particularly mass spectrometry (MS)-based techniques, including gas chromatography-MS (GC-MS), liquid chromatography-tandem MS (LC-MS/MS), and capillary electrophoresis-MS (CE-MS) metabolomics assays. These findings may make provision for a new set of non-invasive biomarkers for IBS diagnosis and management.

Selective degradation of endogenous organic metabolites in acidified fresh human urine using sulphate radical-based advanced oxidation

The human urine metabolome is complex, containing a wide range of organic metabolites that affect treatment of urine collected in resource-oriented sanitation systems. In this study, an advanced oxidation process involving heat-activated peroxydisulphate was used to selectively oxidise organic metabolites in urine over urea and chloride. Initial experiments evaluated optimal conditions (peroxydisulphate dose, temperature, time, pH) for activation of peroxydisulphate in unconcentrated, non-hydrolysed synthetic urine and real urine acidified to pH 3.0. Subsequent experiments determined the fate of 268 endogenous organic metabolites (OMs) and removal of COD from unconcentrated and concentrated real urine (80-90% mass reduced by evaporation). The results revealed >90% activation of 60 mM peroxydisulphate in real unconcentrated urine heated to 90 °C for 1 h, resulting in 43% ΣOMs degradation, 22% COD removal and 56% total organic carbon removal, while >94% of total nitrogen and >97% of urea in real unconcentrated urine were recovered. The mechanism of urea degradation was identified to be chemical hydrolysis to ammonia, with the rate constant for this reaction determined to be 1.9 × 10-6 s-1 at pH 3.0 and 90 °C. Treating concentrated real urine resulted in similar removal of COD, ΣOMs degradation and total nitrogen loss as observed for unconcentrated urine, but with significantly higher chloride oxidation and chemical hydrolysis of urea. Targeted metabolomic analysis revealed that peroxydisulphate treatment degraded 157 organic metabolites in urine, of which 67 metabolites were degraded by >80%. The rate constant for the reaction of sulphate radicals with oxidisable endogenous organic metabolites in urine was estimated to exceed 108 M-1 s-1. These metabolites were preferentially oxidised over chloride and urea in acidified, non-hydrolysed urine treated with peroxydisulphate. Overall, the findings support the development of emerging urine recycling technologies, including alkaline/acid dehydration and reverse osmosis, where the presence of endogenous organic urine metabolites significantly influences treatment parameters such as energy demand and product purity.

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

Recent advances and challenges in the analysis of natural toxins

Natural toxins (NTs) are poisonous secondary metabolites produced by living organisms developed to ward off predators. Especially low molecular weight NTs (MW<∼1 kDa), such as mycotoxins, phycotoxins, and plant toxins, are considered an important and growing food safety concern. Therefore, accurate risk assessment of food and feed for the presence of NTs is crucial. Currently, the analysis of NTs is predominantly performed with targeted high pressure liquid chromatography tandem mass spectrometry (HPLC-MS/MS) methods. Although these methods are highly sensitive and accurate, they are relatively expensive and time-consuming, while unknown or unexpected NTs will be missed. To overcome this, novel on-site screening methods and non-targeted HPLC high resolution mass spectrometry (HRMS) methods have been developed. On-site screening methods can give non-specialists the possibility for broad "scanning" of potential geographical regions of interest, while also providing sensitive and specific analysis at the point-of-need. Non-targeted chromatography-HRMS methods can detect unexpected as well as unknown NTs and their metabolites in a lab-based approach. The aim of this chapter is to provide an insight in the recent advances, challenges, and perspectives in the field of NTs analysis both from the on-site and the laboratory perspective.

Tartronic Acid as a Potential Inhibitor of Pathological Calcium Oxalate Crystallization

Kidney stones are a pervasive disease with notoriously high recurrence rates that require more effective treatment strategies. Herein, tartronic acid is introduced as an efficient inhibitor of calcium oxalate monohydrate (COM) crystallization, which is the most prevalent constituent of human kidney stones. A combination of in situ experimental techniques and simulations are employed to compare the inhibitory effects of tartronic acid with those of its molecular analogs. Tartronic acid exhibits an affinity for binding to rapidly growing apical surfaces of COM crystals, thus setting it apart from other inhibitors such as citric acid, the current preventative treatment for kidney stones. Bulk crystallization and in situ atomic force microscopy (AFM) measurements confirm the mechanism by which tartronic acid interacts with COM crystal surfaces and inhibits growth. These findings are consistent with in vivo studies that reveal the efficacy of tartronic acid is similar to that of citric acid in mouse models of hyperoxaluria regarding their inhibitory effect on stone formation and alleviating stone-related physical harm. In summary, these findings highlight the potential of tartronic acid as a promising alternative to citric acid for the management of calcium oxalate nephropathies, offering a new option for clinical intervention in cases of kidney stones.

Slice through the water-Exploring the fundamental challenge of water suppression for benchtop NMR systems

Benchtop NMR provides improved accessibility in terms of cost, space, and technical expertise. In turn, this encourages new users into the field of NMR spectroscopy. Unfortunately, many interesting samples in education and research, from beer to whole blood, contain significant amounts of water that require suppression in 1H NMR in order to recover sample information. However, due to the significant reduction in chemical shift dispersion in benchtop NMR systems, the sample signals are much closer to the water resonance compared to those in a corresponding high-field NMR spectrum. Therefore, simply translating solvent suppression experiments intended for high-field NMR instruments to benchtop NMR systems without careful consideration can be problematic. In this study, the effectiveness of several popular water suppression schemes was evaluated for benchtop NMR applications. Emphasis is placed on pulse sequences with no, or few, adjustable parameters making them easy to implement. These fall into two main categories: (1) those based on Pre-SAT including Pre-SAT, PURGE, NOESY-PR, and g-NOESY-PR and (2) those based on binomial inversion including JRS and W5-WATERGATE. Among these schemes, solvent suppression sequences based on Pre-SAT offer a general approach for easy solvent suppression for samples with higher analyte concentrations (sucrose standard and Redbull™). However, for human urine, binomial-like sequences were required. In summary, it is demonstrated that highly efficient water suppression approaches can be implemented on benchtop NMR systems in a simple manner, despite the limited spectral dispersion, further illustrating the potential for widespread implementation of these approaches in education and research.

Urine metabolic profile in rats with arterial hypertension of different genesis

The diversity of pathogenetic mechanisms underlying arterial hypertension leads to the necessity to devise a personalized approach to the diagnosis and treatment of the disease. Metabolomics is one of the promising methods for personalized medicine, as it provides a comprehensive understanding of the physiological processes occurring in the body. The metabolome is a set of low-molecular substances available for detection in a sample and representing intermediate and final products of cell metabolism. Changes in the content and ratio of metabolites in the sample mark the corresponding pathogenetic mechanisms by highlighting them, which is especially important for such a multifactorial disease as arterial hypertension. To identify metabolomic markers for hypertensive conditions of different origins, three forms of arterial hypertension (AH) were studied: rats with hereditary AH (ISIAH rat strain); rats with AH induced by L-NAME administration (a model of endothelial dysfunction with impaired NO production); rats with AH caused by the administration of deoxycorticosterone in combination with salt loading (hormone-dependent form - DOCA-salt AH). WAG rats were used as normotensive controls. 24-hour urine samples were collected from all animals and analyzed by quantitative NMR spectroscopy for metabolic profiling. Then, potential metabolomic markers for the studied forms of hypertensive conditions were identified using multivariate statistics. Analysis of the data obtained showed that hereditary stress-induced arterial hypertension in ISIAH rats was characterized by a decrease in the following urine metabolites: nicotinamide and 1-methylnicotinamide (markers of inflammatory processes), N- acetylglutamate (nitric oxide cycle), isobutyrate and methyl acetoacetate (gut microbiota). Pharmacologically induced forms of hypertension (the L-NAME and DOCA+NaCl groups) do not share metabolomic markers with hereditary AH. They are differentiated by N,N-dimethylglycine (both groups), choline (the L-NAME group) and 1-methylnicotinamide (the group of rats with DOCA-salt hypertension).

Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation

Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

NMR Precision Metabolomics: Dynamic Peak Sum Thresholding and Navigators for Highly Standardized and Reproducible Metabolite Profiling of Clinical Urine Samples

Metabolomics, especially urine-based studies, offers incredible promise for the discovery and development of clinically impactful biomarkers. However, due to the unique challenges of urine, a highly precise and reproducible workflow for NMR-based urine metabolomics is lacking. Using 1D and 2D non-uniform sampled (NUS) 1H-13C NMR spectroscopy, we systematically explored how changes in hydration or specific gravity (SG) and pH can impact biomarker discovery. Further, we examined additional sources of error in metabolomics studies and identified Navigator molecules that could monitor for those biases. Adjustment of SG to 1.002-1.02 coupled with a dynamic sum-based peak thresholding eliminates false positives associated with urine hydration and reduces variation in chemical shift. We identified Navigator molecules that can effectively monitor for inconsistencies in sample processing, SG, protein contamination, and pH. The workflow described provides quality assurance and quality control tools to generate high-quality urine metabolomics data, which is the first step in biomarker discovery.

Comparison of reversed-phase, hydrophilic interaction, and porous graphitic carbon chromatography columns for an untargeted toxicometabolomics study in pooled human liver microsomes, rat urine, and rat plasma

INTRODUCTION

Untargeted metabolomics studies are expected to cover a wide range of compound classes with high chemical diversity and complexity. Thus, optimizing (pre-)analytical parameters such as the analytical liquid chromatography (LC) column is crucial and the selection of the column depends primarily on the study purpose.

OBJECTIVES

The current investigation aimed to compare six different analytical columns. First, by comparing the chromatographic resolution of selected compounds. Second, on the outcome of an untargeted toxicometabolomics study using pooled human liver microsomes (pHLM), rat plasma, and rat urine as matrices.

METHODS

Separation and analysis were performed using three different reversed-phase (Phenyl-Hexyl, BEH C18, and Gold C18), two hydrophilic interaction chromatography (HILIC) (ammonium-sulfonic acid and sulfobetaine), and one porous graphitic carbon (PGC) columns coupled to high-resolution mass spectrometry (HRMS). Their impact was evaluated based on the column performance and the size of feature count, amongst others.

RESULTS

All three reversed-phase columns showed a similar performance, whereas the PGC column was superior to both HILIC columns at least for polar compounds. Comparing the size of feature count across all datasets, most features were detected using the Phenyl-Hexyl or sulfobetaine column. Considering the matrices, most significant features were detected in urine and pHLM after using the sulfobetaine and in plasma after using the ammonium-sulfonic acid column.

CONCLUSION

The results underline that the outcome of this untargeted toxicometabolomic study LC-HRMS metabolomic study was highly influenced by the analytical column, with the Phenyl-Hexyl or sulfobetaine column being the most suitable. However, column selection may also depend on the investigated compounds as well as on the investigated matrix.

Gut microbiome and metabolome to discover pathogenic bacteria and probiotics in ankylosing spondylitis

Objective

Previous research has partially revealed distinct gut microbiota in ankylosing spondylitis (AS). In this study, we performed non-targeted fecal metabolomics in AS in order to discover the microbiome-metabolome interface in AS. Based on prospective cohort studies, we further explored the impact of the tumor necrosis factor inhibitor (TNFi) on the gut microbiota and metabolites in AS.

Methods

To further understand the gut microbiota and metabolites in AS, along with the influence of TNFi, we initiated a prospective cohort study. Fecal samples were collected from 29 patients with AS before and after TNFi therapy and 31 healthy controls. Metagenomic and metabolomic experiments were performed on the fecal samples; moreover, validation experiments were conducted based on the association between the microbiota and metabolites.

Results

A total of 7,703 species were annotated using the metagenomic sequencing system and by profiling the microbial community taxonomic composition, while 50,046 metabolites were identified using metabolite profiling. Differential microbials and metabolites were discovered between patients with AS and healthy controls. Moreover, TNFi was confirmed to partially restore the gut microbiota and the metabolites. Multi-omics analysis of the microbiota and metabolites was performed to determine the associations between the differential microbes and metabolites, identifying compounds such as oxypurinol and biotin, which were correlated with the inhibition of the pathogenic bacteria Ruminococcus gnavus and the promotion of the probiotic bacteria Bacteroides uniformis. Through experimental studies, the relationship between microbes and metabolites was further confirmed, and the impact of these two types of microbes on the enterocytes and the inflammatory cytokine interleukin-18 (IL-18) was explored.

Conclusion

In summary, multi-omics exploration elucidated the impact of TNFi on the gut microbiota and metabolites and proposed a novel therapeutic perspective: supplementation of compounds to inhibit potential pathogenic bacteria and to promote potential probiotics, therefore controlling inflammation in AS.

Unveiling the potential of SLURP1 protein as a biomarker for prostate cancer screening

Background

Prostate cancer (PCa) develops slowly and lacks obvious symptoms in the early stage, which makes early screening and diagnosis difficult. Urine collection is simple and is an ideal source of biomarkers. In this study, we performed urinary proteomic studies in PCa patients to screen proteins and apply them to the non-invasive early diagnosis of PCa.

Method

Urine samples from PCa patients, benign prostatic hyperplasia (BPH) patients and normal control group were collected. Mass spectrometry was used for proteomic analysis and screening target proteins. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to verify the results. Correlations with clinical indicators were explored, and receiver operating characteristic (ROC) curves were drawn to evaluate the value of target proteins in PCa.

Result

A total of 1065 proteins were identified. Urinary SLURP1 protein was significantly elevated in patients with PCa compared with normal controls and patients with BPH patients. Western blot and ELISA further verified the expression changes of SLURP1. The immunohistochemical staining results revealed a substantial increase in positive SLURP1 expression within PCa tumor tissue. Correlation analysis showed a positive correlation between the expression level of urine SLURP1 protein and serum PSA. ROC curve analysis of the SLURP1 protein in the urine of both normal individuals and PCa patients is determined to be 0.853 (95% CI=0.754 to 0.954).

Conclusion

The concentration of SLURP1 protein in urine of PCa patients is increased, which can serve as a biomarker for screening PCa.

Dysregulations of amino acid metabolism and lipid metabolism in urine of children and adolescents with major depressive disorder: a case-control study

RATIONALE

The mechanisms underlying major depressive disorder (MDD) in children and adolescents are unclear. Metabolomics has been utilized to capture metabolic signatures of various psychiatric disorders; however, urinary metabolic profile of MDD in children and adolescents has not been studied.

OBJECTIVES

We analyzed urinary metabolites in children and adolescents with MDD to identify potential biomarkers and metabolic signatures.

METHODS

Here, liquid chromatography-mass spectrometry was used to profile metabolites in urine samples from 192 subjects, comprising 80 individuals with antidepressant-naïve MDD (AN-MDD), 37 with antidepressant-treated MDD (AT-MDD) and 75 healthy controls (HC). We performed orthogonal partial least squares discriminant analysis to identify differential metabolites and employed logistic regression and receiver operating characteristic analysis to establish a diagnostic panel.

RESULTS

In total, 143 and 71 differential metabolites were identified in AN-MDD and AT-MDD, respectively. These were primarily linked to lipid metabolism, molecular transport, and small molecule biochemistry. AN-MDD additionally exhibited dysregulated amino acid metabolism. Compared to HC, a diagnostic panel of seven metabolites displayed area under the receiver operating characteristic curves of 0.792 for AN-MDD, 0.828 for AT-MDD, and 0.799 for all MDD. Furthermore, the urinary metabolic profiles of children and adolescents with MDD significantly differed from those of adult MDD.

CONCLUSIONS

Our research suggests dysregulated amino acid metabolism and lipid metabolism in the urine of children and adolescents with MDD, similar to results in plasma metabolomics studies. This contributes to the comprehension of mechanisms underlying children and adolescents with MDD.

Biological characteristics of pregnancy in captive Yangtze finless porpoises revealed by urinary metabolomics†

The Yangtze finless porpoises (Neophocaena asiaeorientalis a.) are an endemic and critically endangered species in China. Intensive captive breeding is essential for understanding the biology of critically endangered species, especially their pregnancy characteristics, knowledge of which is crucial for effective breeding management. Urine metabolomics can reveal metabolic differences, arising from physiological changes across pregnancy stages. Therefore, we used the urinary metabolomic technology, to explore urinary metabolite changes in pregnant Yangtze finless porpoises. A total of 2281 metabolites were identified in all samples, which including organic acids and derivatives (24.45%), organoheterocyclic compounds (20.23%), benzenoids (18.05%), organic oxygen compounds (7.73%), and phenylpropanoids and polyketides (6.48%). There were 164, 387, and 522 metabolites demonstrating differential abundance during early pregnancy, mid pregnancy, and late pregnancy, respectively, from the levels observed in nonpregnancy. The levels of pregnenolone, 17α-hydroxyprogesterone, and tetrahydrocortisone were significantly higher during all pregnancy stages, indicating their important roles in fetal development. The differential metabolites between nonpregnancy and pregnancy were mainly associated with amino acid and carbohydrate metabolism. Moreover, metabolic activity varied across pregnancy stages; steroid hormone biosynthesis was predominant in early pregnancy, and amino acid biosynthesis and carbohydrate metabolism were predominant in mid pregnancy and late pregnancy, respectively. Our results provide new insights into metabolic characteristics in the Yangtze finless porpoises' urine during pregnancy, and indicate that the differential levels of urine metabolites can determine pregnancy in Yangtze finless porpoises, providing valuable information for the husbandry and management of pregnant Yangtze finless porpoises in captivity.

A current review of U.S. beef flavor I: Measuring beef flavor

Historically, consumer acceptance of beef was determined by tenderness. Developments in genetics and management over the last couple of decades have improved tenderness to the point that it is secondary to other factors in beef's taste. Flavor, however, is an extraordinarily complex taste attribute dependent on biological sensors in the mouth, sinus cavity, and jaws. The culinary industry has recently focused on innovative ways to give consumers new products satisfying their curiosity about different foods, especially proteins. Competition from plant-based, cell-based, and even other animal-based proteins provides diversity in consumers' ability to select a protein that satisfies their desire to include unique products in their diet. Consequently, the beef industry has focused on flavor for the last 10 to 15 years to determine whether it can provide the guardrails for beef consumption in the future. The U.S. beef industry formed a Flavor Working Group in 2012 composed of the authors listed here to investigate new and innovative ways to manage and measure beef flavor. The results of this working group have resulted in dozens of papers, presentations, abstracts, and symposia. The objective of this manuscript is to summarize the research developed by this working group and by others worldwide that have investigated methodologies that measure beef flavor. This paper will describe the strengths of the research in beef flavor measurement and point out future needs that might be identified as technology advances.

Xenobiotic metabolites modify immune responses of the cervicovaginal epithelium: potential mechanisms underlying barrier disruption

OBJECTIVE

Xenobiotic metabolites are exogenous biochemicals that can adversely impact reproductive health. We previously identified xenobiotics in cervicovaginal fluid during pregnancy in association with short cervix. In other organ systems, xenobiotics can modify epithelial barrier function. We hypothesise that xenobiotics dysregulate epithelial cell and macrophage immune responses as a mechanism to disrupt the cervicovaginal barrier.

DESIGN

In vitro cell culture system.

SETTING

Laboratory within academic institution.

SAMPLE

Vaginal, ectocervical and endocervical epithelial cell lines and primary macrophages.

METHODS

Cells were treated with diethanolamine (2.5 mM), ethyl glucoside (5 mM) or tartrate (2.5 mM) for 24 h.

MAIN OUTCOME MEASURES

Cytokines and matrix metalloproteinases were measured in cell supernatants (n = 3 per condition). One-way analysis of variance (ANOVA) with Dunnett's test for multiple comparisons was performed.

RESULTS

Diethanolamine induces inflammatory cytokines, whereas ethyl glucoside and tartrate generally exert anti-inflammatory effects across all cells. Diethanolamine increases interleukin 6 (IL-6), IL-8, interferon γ-induced protein 10 kDa (IP-10), growth-regulated oncogene (GRO), fractalkine, matrix metalloproteinase 1 (MMP-1), MMP-9 and MMP-10 (p < 0.05 for all), factors involved in acute inflammation and recruitment of monocytes, neutrophils and lymphocytes. Ethyl glucoside and tartrate decrease multiple cytokines, including RANTES and MCP-1 (p < 0.05 for all), which serve as chemotactic factors. Vaginal cells exhibit heightened inflammatory tone compared with cervical cells and macrophages, with a greater number of differentially expressed analytes after xenobiotic exposure.

CONCLUSIONS

Xenobiotic metabolites present in the cervicovaginal space during pregnancy modify immune responses, unveiling potential pathways through which environmental exposures may contribute to the pathogenesis of cervical remodelling preceding preterm birth. Future work identifying xenobiotic sources and routes of exposure offers the potential to modify environmental risks to improve pregnancy outcomes.

Lipin-1 deficiency deteriorates defect of fatty acid β-oxidation and lipid-related kidney damage in diabetic kidney disease

Diabetic lipo-toxicity is a fundamental pathophysiologic mechanism in DM and is now increasingly recognized a key determinant of DKD. Targeting lipid metabolic disorders is an important therapeutic strategy for the treatment of DM and its complications, including DKD. This study aimed to explore the molecular mechanism of lipid metabolic regulation in kidney, especially renal PTECs, and elucidate the role of lipid metabolic related molecule lipin-1 in diabetic lipid-related kidney damage. In this study, lipin-1-deficient db/db mouse model and STZ/HFD-induced T2DM mouse model were used to determine the effect of lipin-1 on DKD development. Then RPTCs and LPIN1 knockdown or overexpressed HK-2 cells induced by PA were used to investigate the mechanism. We found that the expression of lipin-1 increased early and then decreased in kidney during the progression of DKD. Glucose and lipid metabolic disorders and renal insufficiency were found in these 2 types of diabetic mouse models. Interestingly, lipin-1 deficiency might be a pathogenic driver of DKD-to-CKD transition, which could further accelerate the imbalance of renal lipid homeostasis, the dysfunction of mitochondrial and energy metabolism in PTECs. Mechanistically, lipin-1 deficiency resulted in aggravated PTECs injury to tubulointerstitial fibrosis in DKD by downregulating FAO via inhibiting PGC-1α/PPARα mediated Cpt1α/HNF4α signaling and upregulating SREBPs to promote fat synthesis. This study provided new insights into the role of lipin-1 as a regulator for maintaining lipid homeostasis in the kidney, especially PTECs, and its deficiency led to the progression of DKD.

Enhancing a multi-purpose artificial urine for culture and gene expression studies of uropathogenic Escherichia coli strains

AIMS

The main objective of this study was to modify a recently reported multi-purpose artificial urine (MP-AU) for culture and gene expression studies of uropathogenic Escherichia coli (UPEC) strains.

METHODS AND RESULTS

We used liquid chromatography mass spectrometry (LC-MS) to identify and adjust the metabolic profile of MP-AU closer to that of pooled human urine (PHU). Modification in this way facilitated growth of UPEC strains with growth rates similar to those obtained in PHU. Transcriptomic analysis of UPEC strains cultured in enhanced artificial urine (enhanced AU) and PHU showed that the gene expression profiles are similar, with <7% of genes differentially expressed between the two conditions.

CONCLUSIONS

Enhancing an MP-AU with metabolites identified in PHU allows the enhanced AU to be used as a substitute for the culture and in vitro gene expression studies of UPEC strains.

Advancements in CHO metabolomics: techniques, current state and evolving methodologies

Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.

Sex Differences in Branched-chain Amino Acid and Tryptophan Metabolism and Pathogenesis of Youth-onset Type 2 Diabetes

OBJECTIVES

Insulin resistance is associated with elevations in plasma branched-chain amino acids (BCAAs). BCAAs compete with aromatic amino acids including tryptophan for uptake into β cells. To explore relationships between BCAAs and tryptophan metabolism, adiposity, and glucose tolerance, we compared urine metabolites in overweight/obese youth with type 2 diabetes (T2D) with those in nondiabetic overweight/obese and lean youth.

METHODS

Metabolites were measured in 24-hour and first-morning urine samples of 56 nondiabetic adolescents with overweight/obesity, 42 adolescents with T2D, and 43 lean controls, aged 12 to 21 years. Group differences were assessed by Kruskal Wallis or ANOVA.

RESULTS

Groups were comparable for age, pubertal status, and ethnicity. Youth with T2D were predominantly female and had highest percent body fat. BCAAs, branched-chain ketoacids (BCKAs), tryptophan, and kynurenine were higher in urine of subjects with T2D. There were no differences between lean controls and nondiabetic youth with overweight/obesity. T2D was associated with diversion of tryptophan from the serotonin to the kynurenine pathway, with higher urinary kynurenine/serotonin ratio and lower serotonin/tryptophan and 5-HIAA/kynurenine ratios. Urinary BCAAs, BCKAs, tryptophan, and ratios reflecting diversion to the kynurenine pathway correlated positively with metrics of body fat and hemoglobin A1c. Increases in these metabolites in the obese T2D group were more pronounced and statistically significant only in adolescent girls.

CONCLUSION

Increases in urinary BCAAs and BCKAs in adolescent females with T2D are accompanied by diversion of tryptophan metabolism from the serotonin to the kynurenine pathway. These adaptations associate with higher risks of T2D in obese adolescent females than adolescent males.

To what extent does freezing impact the mid-infrared signature of urine? Case of patients attending urology department

Urine is a very interesting and attractive biofluid for biomarker discovery and medical diagnosis research due to its non-invasiveness collection and richness of potential biomarkers. Fourier-Transform Infrared (FTIR) spectroscopy applied on urine samples is a promising tool that could be used as a screening method for various diseases. However, during method development, frozen urine is more accessible, especially for inter-laboratory studies, whereas in routine application fresh urine is more convenient. Here, the objective of our work is to evaluate the freezing impact on mid-infrared signature of urine samples. Therefore, both fresh and frozen urine samples from twenty patients were analysed in a dried form. These samples were collected from patients consulting for cystoscopy examination. Simultaneously, centrifugation was also conducted on 10 of all included patients. Principal component analysis (PCA) revealed that patient inter-variabilities are higher than variability due to the freezing step. Then, Euclidean distance between fresh and frozen urine of each patient highlighted that the impact of freezing is different from one patient to another. Adding the centrifugation step slightly minimized intra-patient variability compared to not centrifugated samples. This study contributes to define experimental conditions for urine analysis development for translational application in biomedical field.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Urine Metabolic Profiling for Rapid Lung Cancer Screening: A Strategy Combining Rh-Doped SrTiO3-Assisted Laser Desorption/Ionization Mass Spectrometry and Machine Learning

Lung cancer ranks among the cancers with the highest global incidence rates and mortality. Swift and extensive screening is crucial for the early-stage diagnosis of lung cancer. Laser desorption/ionization mass spectrometry (LDI-MS) possesses clear advantages over traditional analytical methods for large-scale analysis due to its unique features, such as simple sample processing, rapid speed, and high-throughput performance. As n-type semiconductors, titanate-based perovskite materials can generate charge carriers under ultraviolet light irradiation, providing the capability for use as an LDI-MS substrate. In this study, we employ Rh-doped SrTiO3 (STO/Rh)-assisted LDI-MS combined with machine learning to establish a method for urine-based lung cancer screening. We directly analyzed urine metabolites from lung cancer patients (LCs), pneumonia patients (PNs), and healthy controls (HCs) without employing any pretreatment. Through the integration of machine learning, LCs are successfully distinguished from HCs and PNs, achieving impressive area under the curve (AUC) values of 0.940 for LCs vs HCs and 0.864 for LCs vs PNs. Furthermore, we identified 10 metabolites with significantly altered levels in LCs, leading to the discovery of related pathways through metabolic enrichment analysis. These results suggest the potential of this method for rapidly distinguishing LCs in clinical applications and promoting precision medicine.

Combined functional genomic and metabolomic approaches identify new genes required for growth in human urine by multidrug-resistant Escherichia coli ST131

Urinary tract infections (UTIs) are one of the most common bacterial infections in humans, with ~400 million cases across the globe each year. Uropathogenic Escherichia coli (UPEC) is the major cause of UTI and increasingly associated with antibiotic resistance. This scenario has been worsened by the emergence and spread of pandemic UPEC sequence type 131 (ST131), a multidrug-resistant clone associated with extraordinarily high rates of infection. Here, we employed transposon-directed insertion site sequencing in combination with metabolomic profiling to identify genes and biochemical pathways required for growth and survival of the UPEC ST131 reference strain EC958 in human urine (HU). We identified 24 genes required for growth in HU, which mapped to diverse pathways involving small peptide, amino acid and nucleotide metabolism, the stringent response pathway, and lipopolysaccharide biosynthesis. We also discovered a role for UPEC resistance to fluoride during growth in HU, most likely associated with fluoridation of drinking water. Complementary nuclear magnetic resonance (NMR)-based metabolomics identified changes in a range of HU metabolites following UPEC growth, the most pronounced being L-lactate, which was utilized as a carbon source via the L-lactate dehydrogenase LldD. Using a mouse UTI model with mixed competitive infection experiments, we demonstrated a role for nucleotide metabolism and the stringent response in UPEC colonization of the mouse bladder. Together, our application of two omics technologies combined with different infection-relevant settings has uncovered new factors required for UPEC growth in HU, thus enhancing our understanding of this pivotal step in the UPEC infection pathway.

IMPORTANCE

Uropathogenic Escherichia coli (UPEC) cause ~80% of all urinary tract infections (UTIs), with increasing rates of antibiotic resistance presenting an urgent threat to effective treatment. To cause infection, UPEC must grow efficiently in human urine (HU), necessitating a need to understand mechanisms that promote its adaptation and survival in this nutrient-limited environment. Here, we used a combination of functional genomic and metabolomic techniques and identified roles for the metabolism of small peptides, amino acids, nucleotides, and L-lactate, as well as the stringent response pathway, lipopolysaccharide biosynthesis, and fluoride resistance, for UPEC growth in HU. We further demonstrated that pathways involving nucleotide metabolism and the stringent response are required for UPEC colonization of the mouse bladder. The UPEC genes and metabolic pathways identified in this study represent targets for the development of innovative therapeutics to prevent UPEC growth during human UTI, an urgent need given the rapidly rising rates of global antibiotic resistance.

Metabolic maturation in the infant urine during the first 3 months of life

The infant urine metabolome provides a body metabolic snapshot, and the sample collection can be done without stressing the fragile infant. 424 infant urine samples from 157 infants were sampled longitudinally at 1-, 2-, and 3 months of age. 49 metabolites were detected using proton nuclear magnetic resonance spectroscopy. Data were analyzed with multi- and univariate statistical methods to detect differences related to infant age-stage, gestational age, mother's pre-pregnancy BMI, C-section, infant birth weight, and infant sex. Significant differences were identified between age-stage (pbonferoni < 0.05) in 30% (15/49) of the detected metabolites. Urine creatinine increased significantly from 1 to 3 months. In addition, myo-inositol, taurine, methionine, and glucose seem to have conserved levels within the individual over time. We calculated a urine metabolic maturation age and found that the metabolic age at 3 months is negatively correlated to weight at 1 year. These results demonstrate that the metabolic maturation can be observed in urine metabolome with implications on infant growth and specifically suggesting that the systematic age effect on creatinine promotes caution in using this as normalization of other urine metabolites.

In situ electrochemical regeneration of nanogap hotspots for continuously reusable ultrathin SERS sensors

Surface-enhanced Raman spectroscopy (SERS) harnesses the confinement of light into metallic nanoscale hotspots to achieve highly sensitive label-free molecular detection that can be applied for a broad range of sensing applications. However, challenges related to irreversible analyte binding, substrate reproducibility, fouling, and degradation hinder its widespread adoption. Here we show how in-situ electrochemical regeneration can rapidly and precisely reform the nanogap hotspots to enable the continuous reuse of gold nanoparticle monolayers for SERS. Applying an oxidising potential of +1.5 V (vs Ag/AgCl) for 10 s strips a broad range of adsorbates from the nanogaps and forms a metastable oxide layer of few-monolayer thickness. Subsequent application of a reducing potential of -0.80 V for 5 s in the presence of a nanogap-stabilising molecular scaffold, cucurbit[5]uril, reproducibly regenerates the optimal plasmonic properties with SERS enhancement factors ≈106. The regeneration of the nanogap hotspots allows these SERS substrates to be reused over multiple cycles, demonstrating ≈5% relative standard deviation over at least 30 cycles of analyte detection and regeneration. Such continuous and reliable SERS-based flow analysis accesses diverse applications from environmental monitoring to medical diagnostics.

Urinary metabolite biomarkers of pregnancy complications associated with maternal exposure to particulate matter

Particulate matter 2.5 (PM2.5) is associated with reproductive health and adverse pregnancy outcomes. However, studies evaluating biological markers of PM2.5 are lacking, and identifying biomarkers for estimating prenatal exposure to prevent pregnancy complications is essential. Therefore, we aimed to explore urine metabolites that are easy to measure as biomarkers of exposure. In this matched case-control study based on the PM2.5 exposure, 30 high PM2.5 group (>15 μg/m3) and 30 low PM2.5 group (<15 μg/m3) were selected from air pollution on pregnancy outcome (APPO) cohort study. We used a time-weighted average model to estimate individual PM exposure, which used indoor PM2.5 and outdoor PM2.5 concentrations by atmospheric measurement network based on residential addresses. Clinical characteristics and urine samples were collected from participants during the second trimester of pregnancy. Urine metabolites were quantitatively measured using gas chromatography-mass spectrometry following multistep chemical derivatization. Statistical analyses were conducted using SPSS version 21 and MetaboAnalyst 5.0. Small for gestational age and gestational diabetes (GDM) were significantly increased in the high PM2.5 group, respectively (P = 0.042, and 0.022). Fifteen metabolites showed significant differences between the two groups (P < 0.05). Subsequent pathway enrichment revealed that four pathways, including pentose and glucuronate interconversion with three pentose sugars (ribose, arabinose, and xylose; P < 0.05). The concentration of ribose increased preterm births (PTB) and GDM (P = 0.044 and 0.049, respectively), and the arabinose concentration showed a tendency to increase in PTB (P = 0.044). Therefore, we identified urinary pentose metabolites as biomarkers of PM2.5 and confirmed the possibility of their relationship with pregnancy complications.

Implementation of pure shift 1 H NMR in metabolic phenotyping for structural information recovery of biofluid metabolites with complex spin systems

NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.

Protein lysine four-carbon acylations in health and disease

Lysine acylation, a type of posttranslational protein modification sensitive to cellular metabolic states, influences the functions of target proteins involved in diverse cellular processes. Particularly, lysine butyrylation, crotonylation, β-hydroxybutyrylation, and 2-hydroxyisobutyrylation, four types of four-carbon acylations, are modulated by intracellular concentrations of their respective acyl-CoAs and sensitive to alterations of nutrient metabolism induced by cellular and/or environmental signals. In this review, we discussed the metabolic pathways producing these four-carbon acyl-CoAs, the regulation of lysine acylation and deacylation, and the functions of individual lysine acylation.

Concentration strategies for spiked and naturally present biomarkers in non-invasively collected first-void urine

BACKGROUND

First-void urine (FVU) provides a non-invasive method for collecting a wide range of biomarkers found in genital tract secretions. To optimize biomarker collection in FVU, this study investigated the impact of naturally present and supplemented precipitating agents: uromodulin (UMOD) and polyethylene glycol (PEG), on the concentration of human papillomavirus (HPV) pseudovirions (PsV), cell-free DNA (cfDNA), and cellular genomic DNA (gDNA) through centrifugation.

METHODS

FVU samples from ten healthy female volunteers, along with a control sample, were spiked with seal herpesvirus 1 (PhHV-1) DNA, HPV16 plasmid DNA, and HPV16 PsV with an enhanced green fluorescent protein (EGFP) reporter. The samples were subjected to various concentration protocols involving PEG precipitation, low-speed centrifugation (5 min at 1000×g), and medium-speed centrifugation (1 h at 3000×g). Subsequently, quantitative PCR (qPCR) was used to assess cellular and cell-free glyceraldehyde-3-phosphate dehydrogenase (GAPDH) DNA, cell-free PhHV-1 and HPV16 DNA, and PsV (EGFP) DNA. In addition, UMOD levels were measured.

RESULTS

The findings revealed that PEG significantly increased the concentration of cfDNA and gDNA in the pellet after centrifugation, with the most pronounced effect observed for cfDNA. Moreover, low-speed centrifugation without PEG effectively depleted cellular gDNA while preserving cfDNA in the supernatants. Pseudovirions were consistently pelleted, even with low-speed centrifugation, and a positive but not significant effect of PEG on PsV (EGFP) DNA yield in the pellet was observed. Additionally, a significant correlation was observed between UMOD and GAPDH, HPV16, and PsV (EGFP) DNA quantities in the pellet. Furthermore, large variations among the FVU samples were observed.

CONCLUSIONS

With this study, we provide novel insights into how various biomarker precipitation protocols, including both the properties of FVU and the use of PEG as a precipitating agent, influence the concentration of cfDNA, cellular gDNA, and pseudovirions.

Cancer detection in dogs using rapid Raman molecular urinalysis

Introduction

The presence of cancer in dogs was detected by Raman spectroscopy of urine samples and chemometric analysis of spectroscopic data. The procedure created a multimolecular spectral fingerprint with hundreds of features related directly to the chemical composition of the urine specimen. These were then used to detect the broad presence of cancer in dog urine as well as the specific presence of lymphoma, urothelial carcinoma, osteosarcoma, and mast cell tumor.

Methods

Urine samples were collected via voiding, cystocentesis, or catheterization from 89 dogs with no history or evidence of neoplastic disease, 100 dogs diagnosed with cancer, and 16 dogs diagnosed with non-neoplastic urinary tract or renal disease. Raman spectra were obtained of the unprocessed bulk liquid urine samples and were analyzed by ISREA, principal component analysis (PCA), and discriminant analysis of principal components (DAPC) were applied using the Rametrix®Toolbox software.

Results and discussion

The procedure identified a spectral fingerprint for cancer in canine urine, resulting in a urine screening test with 92.7% overall accuracy for a cancer vs. cancer-free designation. The urine screen performed with 94.0% sensitivity, 90.5% specificity, 94.5% positive predictive value (PPV), 89.6% negative predictive value (NPV), 9.9 positive likelihood ratio (LR+), and 0.067 negative likelihood ratio (LR-). Raman bands responsible for discerning cancer were extracted from the analysis and biomolecular associations were obtained. The urine screen was more effective in distinguishing urothelial carcinoma from the other cancers mentioned above. Detection and classification of cancer in dogs using a simple, non-invasive, rapid urine screen (as compared to liquid biopsies using peripheral blood samples) is a critical advancement in case management and treatment, especially in breeds predisposed to specific types of cancer.

Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers

BACKGROUND

Urinary metabolomics has demonstrated considerable potential to assess kidney function and its metabolic corollaries in health and disease. However, applications in epidemiology remain sparse due to technical challenges.

METHODS

We added 17 metabolites to an open-access urinary nuclear magnetic resonance metabolomics platform, extending the panel to 61 metabolites (n = 994). We also introduced automated quantification for 11 metabolites, extending the panel to 12 metabolites (+creatinine). Epidemiological associations between these 12 metabolites and 49 clinical measures were studied in three independent cohorts (up to 5989 participants). Detailed regression analyses with various confounding factors are presented for body mass index (BMI) and smoking.

RESULTS

Sex-specific population reference concentrations and distributions are provided for 61 urinary metabolites (419 men and 575 women), together with methodological intra-assay metabolite variations as well as the biological intra-individual and epidemiological population variations. For the 12 metabolites, 362 associations were found. These are mostly novel and reflect potential molecular proxies to estimate kidney function, as the associations cannot be simply explained by estimated glomerular filtration rate. Unspecific renal excretion results in leakage of amino acids (and glucose) to urine in all individuals. Seven urinary metabolites associated with smoking, providing questionnaire-independent proxy measures of smoking status in epidemiological studies. Common confounders did not affect metabolite associations with smoking, but insulin had a clear effect on most associations with BMI, including strong effects on 2-hydroxyisobutyrate, valine, alanine, trigonelline and hippurate.

CONCLUSIONS

Urinary metabolomics provides new insight on kidney function and related biomarkers on the renal-cardiometabolic system, supporting large-scale applications in epidemiology.

Gut microbiota-dependent phenylacetylglutamine in cardiovascular disease: current knowledge and new insights

Phenylacetylglutamine (PAGln) is an amino acid derivate that comes from the amino acid phenylalanine. There are increasing studies showing that the level of PAGln is associated with the risk of different cardiovascular diseases. In this review, we discussed the metabolic pathway of PAGln production and the quantitative measurement methods of PAGln. We summarized the epidemiological evidence to show the role of PAGln in diagnostic and prognostic value in several cardiovascular diseases, such as heart failure, coronary heart disease/atherosclerosis, and cardiac arrhythmia. The underlying mechanism of PAGln is now considered to be related to the thrombotic potential of platelets via adrenergic receptors. Besides, other possible mechanisms such as inflammatory response and oxidative stress could also be induced by PAGln. Moreover, since PAGln is produced across different organs including the intestine, liver, and kidney, the cross-talk among multiple organs focused on the function of this uremic toxic metabolite. Finally, the prognostic value of PAGln compared to the classical biomarker was discussed and we also highlighted important gaps in knowledge and areas requiring future investigation of PAGln in cardiovascular diseases.

Unraveling the potential of segment scan mass spectral acquisition for chemical isotope labeling LC-MS-based metabolome analysis: Performance assessment across different types of biological samples

BACKGROUND

Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with high metabolomic coverage and quantification accuracy. In CIL LC-MS, the overall metabolite detection efficiency using Orbitrap MS can be further improved by employing a segment scan method where the full m/z range is divided into multiple segments for spectral acquisition with a significant increase in the in-spectrum dynamic range. Considering the metabolic complexity in different types of biological samples (e.g., feces, urine, serum/plasma, cell/tissue extracts, saliva, etc.), we report the development and evaluation of the segment scan method for metabolome analysis of different sample types.

RESULTS

It was found that sample complexity significantly influenced the performance of the segment scan method. In metabolically complex samples such as feces and urine, the method yielded a substantial increase (up to 94 %) in detected peak pairs or metabolites, compared to conventional full scan. Conversely, less complex samples like saliva exhibited more modest gains (approximately 25 %). Based on the observations, a 120-m/z segment scan method was determined as a routine approach for CIL LC-Orbitrap-MS-based metabolomics with good compatibility with different types of biological samples. For this method, a further investigation on relative quantification accuracy was done. The peak area ratios of 12C-/13-labeled metabolites were slightly reduced with 72%-84 % of peak pairs falling within the ±25 % range of the anticipated peak ratio of 1.0 among different samples, as opposed to 81%-90 % in the full scan, which was attributed to the inclusion of more low-abundance peak pairs within the narrow MS segments. However, the overall peak ratio measurement precision was not significantly affected by the segment scan.

SIGNIFICANCE AND NOVELTY

The segment scan method was found to be useful for CIL LC-Orbitrap-MS-based metabolome analysis of different types of samples with significant improvement in metabolite detectability (25-94 % increase), compared to the conventional full scan method.

Blurred lines: Crossing the boundaries between the chemical exposome and the metabolome

The aetiology of every human disease lies in a combination of genetic and environmental factors, each contributing in varying proportions. While genomics investigates the former, a comparable holistic paradigm was proposed for environmental exposures in 2005, marking the onset of exposome research. Since then, the exposome definition has broadened to include a wide array of physical, chemical, and psychosocial factors that interact with the human body and potentially alter the epigenome, the transcriptome, the proteome, and the metabolome. The chemical exposome, deeply intertwined with the metabolome, includes all small molecules originating from diet as well as pharmaceuticals, personal care and consumer products, or pollutants in air and water. The set of techniques to interrogate these exposures, primarily mass spectrometry and nuclear magnetic resonance spectroscopy, are also extensively used in metabolomics. Recent advances in untargeted metabolomics using high resolution mass spectrometry have paved the way for the development of methods able to provide in depth characterisation of both the internal chemical exposome and the endogenous metabolome simultaneously. Herein we review the available tools, databases, and workflows currently available for such work, and discuss how these can bridge the gap between the study of the metabolome and the exposome.

Augmenting Antimicrobial Resistance Surveillance: Rapid Detection of β-Lactamase-Expressing Drug-Resistant Bacteria through Sensitized Luminescence on a Paper-Supported Hydrogel

The emergence of antimicrobial resistance (AMR) in pathogenic bacteria, expedited by the overuse and misuse of antibiotics, necessitates the development of a rapid and pan-territorially accessible diagnostic protocol for resistant bacterial infections, which would not only enable judicious prescription of drugs, leading to infection control but also augment AMR surveillance. In this study, we introduce for the first time a "turn-on" terbium (Tb3+) photoluminescence assay supported on a paper-based platform for rapid point-of-care (POC) detection of β-lactamase (BL)-producing bacteria. We strategically conjugated biphenyl-4-carboxylic acid (BCA), a potent Tb3+ sensitizer, with cephalosporin to engineer a BL substrate CCS, where the energy transfer to terbium is arrested. However, BL, a major resistance element produced by bacteria resistant to β-lactam antibiotics, triggers a spontaneous release of BCA, empowering terbium sensitization within a supramolecular scaffold supported on paper. The remarkable optical response facilitates quick assessment with a binary answer, and the time-gated signal acquisition ensues improved sensitivity with a detection limit as low as 0.1 mU/mL. Furthermore, to ensure accessibility, particularly in resource-limited areas, we have developed an in loco imaging device as an affordable alternative to high-end instruments. The integration of the assay with the device readily identified the BL-associated drug-resistant strains in the mimic urinary tract infection samples within 2 h, demonstrating its excellent potential for in-field translation. We believe that this rapid paper-based POC assay, coupled with the in loco device, can be deployed anywhere, especially in developing regions, and will enable extensive surveillance on antibiotic-resistant infections.

SAH and SAM/SAH ratio associate with acute kidney injury in critically ill patients: A case-control study

BACKGROUND

Acute kidney injury (AKI) is a serious clinical emergency with an acute onset, rapid progression and poor prognosis, which has high morbidity and mortality in hospitalized patients. DNA methylation plays an important role in the occurrence and progression of kidney disease, and aberrant methylation and certain altered methylation-related metabolites have been reported in AKI patients. However, the specific alterations of methylation-related metabolites in the AKI patients were not investigated clearly.

METHOD

In this study, 61 AKI and 61 matched non-AKI inpatients were recruited after propensity score matching the age and hypertension. And 11 methylation-related metabolites in the plasma and urine of the two groups were quantified by using UHPLC-MS/MS method.

RESULTS

Certain methylation-relate intermediates were up-regulated in the plasma (choline, trimethylamine N-oxide (TMAO), trimethyl lysine (TML), S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH)) and down-regulated in the urine of AKI inpatients (choline, betaine, TMAO, dimethylglycine (DMG), SAM and taurine). The correlation analysis revealed a relatively strong correlation between plasma SAH, SAM/SAH ratio and renal function index (serum creatinine (SCr) and estimated glomerular filtration rate (eGFR), r = 0.523-0.616), and the correlation of urinary intermediates with renal function index was weaker than that in the plasma. Furthermore, receiver operating characteristic (ROC) analysis showed that plasma SAH and urinary SAM/SAH ratio represented the best distinguishing efficiency with AUC 0.844 and 0.794, respectively. Moreover, the findings of binary regression analysis demonstrated plasma choline, TMAO, TML, SAM and SAH were the risk markers of AKI (up-regulation in plasma, OR > 1), urinary choline, betaine, TMAO, DMG and SAM were protective markers of AKI (down-regulation in urine, OR < 1), and SAM/SAH ratio was a protective marker in plasma and urine (down-regulation in both two biofluids, OR = 0.510, 0.383-0.678 in plasma, OR = 0.904, 0.854-0.968 in urine), indicating the increased risk of AKI when combined with the alteration of plasma and urinary levels.

CONCLUSION

The comprehensive analysis of plasma and urine samples from AKI inpatients offers a more extensive assessment of methylated metabolic alterations, suggesting a close relationship between AKI stress and altered methylation ability. The plasma level of SAH and SAM/SAH ratio and urinary SAM/SAH ratio both showed a strong correlation with renal function (SCr and eGFR) and good accuracy for distinguishing AKI in the two biomatrices, which exhibited promising prospects in predicting renal function decline and providing further information for the pathogenesis of AKI.

Increasing coverage of the urinary polar metabolome using ultra high-performance hydrophobic interaction liquid chromatography combined with linear and cyclic travelling wave ion mobility and mass spectrometry

The use of HILIC-based separations for the analysis of polar metabolites in metabolic phenotyping studies is well established. Here, we demonstrate the increased coverage of the polar metabolome obtained by travelling wave (TW) ion mobility (IM) instruments combined with HILIC and mass spectrometry (MS) for metabotyping rat and mouse urine samples. Profiling was performed using either a linear TW IM-MS based instrument with a path length of 40 cm or an instrument with a cyclic travelling wave analyser (cIM) with a path length of 95 cm. Due to the added resolution afforded by using both the linear and cyclic IM geometries with MS detection (IM-MS) significant increases in feature count (m/z-tR pairs) were generally obtained compared to HILIC-MS alone. In addition, the use of both linear and cyclic IM-MS improved the quality of the mass spectra obtained as a result of the separation of co-eluting analytes. As would be expected from the increased path length of the cyclic IM-MS instrument compared to the linear device, the largest gains in feature detection were obtained for the HILIC-cIM-MS combination. By increasing the resolution of coeluting components, the cyclic IM-MS instrumentation also provided the largest improvement in the quality of the mass spectral data obtained. When applied to mouse urines obtained from both control and gefitinib-dosed mice, time-related changes were detected in those obtained from the treated animals that were not seen in the controls. Polar metabolites affected by drug administration included, but were not limited to, hypoxanthine, 1,3-dimethyluracil and acetylcarnitine. The changes seen in the relative concentrations of these endogenous metabolites appeared to be related to drug concentrations in the plasma and urine suggesting a pharmacometabodynamic link.

The Urinary Metabolome of Newborns with Perinatal Complications

Maternal pathological conditions such as infections and chronic diseases, along with unexpected events during labor, can lead to life-threatening perinatal outcomes. These outcomes can have irreversible consequences throughout an individual's entire life. Urinary metabolomics can provide valuable insights into early physiological adaptations in healthy newborns, as well as metabolic disturbances in premature infants or infants with birth complications. In the present study, we measured 180 metabolites and metabolite ratios in the urine of 13 healthy (hospital-discharged) and 38 critically ill newborns (admitted to the neonatal intensive care unit (NICU)). We used an in-house-developed targeted tandem mass spectrometry (MS/MS)-based metabolomic assay (TMIC Mega) combining liquid chromatography (LC-MS/MS) and flow injection analysis (FIA-MS/MS) to quantitatively analyze up to 26 classes of compounds. Average urinary concentrations (and ranges) for 167 different metabolites from 38 critically ill NICU newborns during their first 24 h of life were determined. Similar sets of urinary values were determined for the 13 healthy newborns. These reference data have been uploaded to the Human Metabolome Database. Urinary concentrations and ranges of 37 metabolites are reported for the first time for newborns. Significant differences were found in the urinary levels of 44 metabolites between healthy newborns and those admitted at the NICU. Metabolites such as acylcarnitines, amino acids and derivatives, biogenic amines, sugars, and organic acids are dysregulated in newborns with bronchopulmonary dysplasia (BPD), asphyxia, or newborns exposed to SARS-CoV-2 during the intrauterine period. Urine can serve as a valuable source of information for understanding metabolic alterations associated with life-threatening perinatal outcomes.

Hyperpolarization-Enhanced NMR Spectroscopy of Unaltered Biofluids Using Photo-CIDNP

The direct and unambiguous detection and identification of individual metabolite molecules present in complex biological mixtures constitute a major challenge in (bio)analytical research. In this context, nuclear magnetic resonance (NMR) spectroscopy has proven to be particularly powerful owing to its ability to provide both qualitative and quantitative atomic-level information on multiple analytes simultaneously in a noninvasive manner. Nevertheless, NMR suffers from a low inherent sensitivity and, moreover, lacks selectivity regarding the number of individual analytes to be studied in a mixture of a myriad of structurally and chemically very different molecules, e.g., metabolites in a biofluid. Here, we describe a method that circumvents these shortcomings via performing selective, photochemically induced dynamic nuclear polarization (photo-CIDNP) enhanced NMR spectroscopy on unmodified complex biological mixtures, i.e., human urine and serum, which yields a single, background-free one-dimensional NMR spectrum. In doing this, we demonstrate that photo-CIDNP experiments on unmodified complex mixtures of biological origin are feasible, can be performed straightforwardly in the native aqueous medium at physiological metabolite concentrations, and act as a spectral filter, facilitating the analysis of NMR spectra of complex biofluids. Due to its noninvasive nature, the method is fully compatible with state-of-the-art metabolomic protocols providing direct spectroscopic information on a small, carefully selected subset of clinically relevant metabolites. We anticipate that this approach, which, in addition, can be combined with existing high-throughput/high-sensitivity NMR methodology, holds great promise for further in-depth studies and development for use in metabolomics and many other areas of analytical research.

Simultaneous Analysis of Organic Acids, Glycerol and Phenolic Acids in Wines Using Gas Chromatography-Mass Spectrometry

Fermented beverages, particularly wines, exhibit variable concentrations of organic and phenolic acids, posing challenges in their accurate determination. Traditionally, enzymatic methods or chromatographic analyses, mainly high-performance liquid chromatography (HPLC), have been employed to quantify these compounds individually in the grape must or wine. However, chromatographic analyses face limitations due to the high sugar content in the grape must. Meanwhile, phenolic acids, found in higher quantities in red wines than in white wines, are typically analyzed using HPLC. This study presents a novel method for the quantification of organic acids (OAs), glycerol, and phenolic acids in grape musts and wines. The approach involves liquid-liquid extraction with ethyl acetate, followed by sample derivatization and analysis using gas chromatography-mass spectrometry (GC-MS) in selected ion monitoring (SIM) detection mode. The results indicated successful detection and quantification of all analyzed compounds without the need for sample dilution. However, our results showed that the method of adding external standards was more suitable for quantifying wine compounds, owing to the matrix effect. Furthermore, this method is promising for quantifying other metabolites present in wines, depending on their extractability with ethyl acetate. Fermented beverages, particularly wines, exhibit variable concentrations of organic and phenolic acids, posing challenges in their accurate determination. Traditionally, enzymatic methods or chromatographic analyses, mainly high-performance liquid chromatography (HPLC), have been employed to quantify these compounds individually in the grape must or wine. The approach of this proposed method involves (i) methoximation of wine compounds in a basic medium, (ii) acidification with HCl, (iii) liquid-liquid extraction with ethyl acetate, and (iv) silyl derivatization to analyze samples with gas chromatography-mass spectrometry (GC-MS) in ion monitoring detection mode (SIM). The results indicated successful detection and quantification of all analyzed compounds without the need for sample dilution. However, our results showed that the method of adding external standards was more suitable for quantifying wine compounds, owing to the matrix effect. Furthermore, this method is promising for quantifying other metabolites present in wines, depending on their extractability with ethyl acetate. In other words, the proposed method may be suitable for profiling (targeted) or fingerprinting (untargeted) strategies to quantify wine metabolites or to classify wines according to the type of winemaking process, grape, or fermentation.

Human Urinary Metabolomics as Biomarkers in Tobacco Users: A Systematic Review

Aim

Urine as a biofluid has been rarely used as a diagnostic fluid in oral diseases. The article aims to systematically review the utility of human urinary carcinogen metabolites as an approach for obtaining important information about tobacco and cancer.

Materials and Methods

The following article reviews the use of urine and its metabolites as biomarkers in various lesions of the oral cavity including oral squamous cell carcinoma and as a screening method in evaluating tobacco and its components. A bibliographic comprehensive search was carried out in the main databases: PUBMED, SciELO, Google Scholar, VHL, and LILACS for articles that were published from 1985 to 2020. The inclusion criteria were "urinary metabolites," "oral cancer/HNSCC," "body fluids," "tobacco," and "metabolomics." A total of 55 articles were collected which included laboratory studies, systematic reviews, and literature of urinary metabolites in tobacco users.

Results

Most of the studies carried out show accurate results with high sensitivity of urinary metabolite biomarkers in individuals with tobacco-based habits and lesions caused by them.

Conclusion

The review indicates that urinary metabolite analysis demonstrates its applicability for the diagnosis and prognosis of disease. Urine is a remarkable and useful biofluid for routine testing and provides an excellent resource for the discovery of novel biomarkers, with an advantage over tissue biopsy samples due to the ease and less invasive nature of collection.

A Hypothetical Approach to Concentrate Microorganisms from Human Urine Samples Using Paper-Based Adsorbents for Point-of-Care Molecular Assays

This hypothesis demonstrates that the efficiency of loop-mediated isothermal amplification (LAMP) for nucleic acid detection can be positively influenced by the preconcentration of microbial cells onto hydrophobic paper surfaces. The mechanism of this model is based on the high affinity of microbes towards hydrophobic surfaces. Extensive studies have demonstrated that hydrophobic surfaces exhibit enhanced bacterial and fungal adhesion. By exploiting this inherent affinity of hydrophobic paper substrates, the preconcentration approach enables the adherence of a greater number of target cells, resulting in a higher concentration of target templates for amplification directly from urine samples. In contrast to conventional methods, which often involve complex procedures, this approach offers a simpler, cost-effective, and user-friendly alternative. Moreover, the integration of cell adhesion, LAMP amplification, and signal readout within paper origami-based devices can provide a portable, robust, and highly efficient platform for rapid nucleic acid detection. This innovative hypothesis holds significant potential for point-of-care (POC) diagnostics and field surveillance applications. Further research and development in this field will advance the implementation of this technology, contributing to improved healthcare systems and public health outcomes.

A nonenzymic microfiber optic-biosensor modified phenylboric acid for sensitively and specifically detecting low glucose concentration

A microfiber interferometer coated with sensitive films formed by amide bond between 3-Carboxy-4-fluorophenylboronic acid (FPBA) and polydopamine (PDA) for the detection of trace glucose concentration is designed and demonstrated. Due to a huge evanescent field, this microfiber interferometer has a very sensitive response to the refractive index (RI) of the surrounding environment, which has excellent sensing performance including RI sensitivity response of 1825.83 nm/RIU and low temperature response of -0.04 nm/°C. Due to the good film-forming performance of PDA, whose the amino group coupled with the carboxyl molecule on FPBA to form an amide bond, PDA/FPBA can be attached to the microfiber interferometer for detecting different concentrations of glucose. The concentration range of glucose detection is 0.1-20 mM with a sensitivity of 1.71 nm/mM and a limit of detection of 12.6 ppm. Finally, the sensor is tested in actual samples of human urine to detect different concentrations of glucose and proved to be responsive and reproducible in urine. We can estimate the concentration of glucose in urine by wavelength shift. The sensor has the advantages of simple manufacture, low cost, high sensitivity, and specific recognition glucose in urine. In addition, the success of this sensor shows that the combination of ultrafine fiber and organic chemical materials has broad prospects in the field of optical detection.

Dilute and shoot approach for toxicology testing

Toxicology testing is performed in clinical settings, forensic settings, and for controlling doping. Drug screening is a toxicology test to determine if drugs are present in biological samples. The most common specimen type for drug testing is urine, as drugs and/or their metabolites are often more concentrated in the urine, extending the detection window of drugs. The dilute-and-shoot method is a simple procedure used in toxicology testing, where a sample is diluted before being directly injected into the liquid chromatography-mass spectrometry (LC-MS) system. This method is easy, quick, and cost-saving, and can be used for protein-poor liquid specimens such as urine. Thus, it is reasonable and attractive for busy toxicology laboratories to combine the dilute-and-shoot method with high-resolution hyphenated-MS for urine drug screening. This method has several disadvantages, including a suboptimal detection capability for certain analytes, as well as interference from co-eluting matrix components called matrix effects, in which co-eluting matrix molecules alter the ionization efficiency of the analyte molecules at the ionization source in LC-MS, altering (mostly reducing) the analyte detection capability. The matrix effect testing is essential for the validation of LC-MS-based assays. A reasonable approach to addressing these undesirable effects would be to minimize these components. The most straightforward approach is to reduce the amounts of matrix components by using a higher dilution of the specimen and a lower volume for specimen injection. Optimization of the chromatographic separation is another reasonable approach for reducing co-eluting matrix components with the analyte.

Metabolomic Profiling of Obese Patients with Altered Intestinal Permeability Undergoing a Very Low-Calorie Ketogenic Diet

A healthy intestinal permeability facilitates the selective transport of nutrients, metabolites, water, and bacterial products, involving cellular, neural, hormonal, and immune factors. An altered intestinal permeability indicates pathologic phenotypes and is associated with the exacerbation of obesity and related comorbidities. To investigate the impact of altered permeability in obese patients undergoing a calorie-restrictive dietary regimen (VLCKD), we collected urinary and fecal samples from obese patients with both normal and altered permeability (determined based on the lactulose/mannitol ratio) before and after treatment. The analysis of volatile organic compounds (VOCs) aids in understanding the metabolites produced by the intestinal microbiota in this unique ecological niche. Furthermore, we examined clinical and anthropometric variables from the cohort and compared them to significant VOC panels. Consequently, we identified specific markers in the metabolomics data that differentiated between normal and altered profiles before and after the diet. These markers indicated how the variable contribution specifically accounted for interleukins and lipopolysaccharides (LPS). The targeted metabolomics experiment detected no differences in measured short-chain fatty acids (SCFA). In summary, our study evaluated metabolomic markers capable of distinguishing low-grade inflammation conditions, exacerbated in more advanced stages of obesity with altered intestinal permeability.

High content of low molecular weight organics does not always affect pharmaceutical adsorption on activated carbon: The case of acetate, propionate and ethanol in source-separated urine

Adsorption on activated carbon is a common process to remove pharmaceuticals in wastewater treatment. Activated carbon adsorption is usually applied to wastewater with a low content of biological degradable organics, i.e. after biological treatment. Especially low molecular weight (LMW) compounds are known to compete with pharmaceuticals for adsorption sites. The goal of this study was to test the hypothesis that biological treatment is necessary for efficient pharmaceutical removal. Source-separated urine after anaerobic storage (anaerobically stored urine) and after aerobic biological removal of organics without nitrification (organics-depleted urine) were used in this study. In anaerobically stored urine 60% of the organic compounds were LMW organics, of which about 40% were acetate and propionate. 74% of the DOC and 100% of acetate and propionate were removed during aerobic biological treatment. To investigate the effect of the organic compounds on pharmaceutical removal, sorption experiments with 19 spiked pharmaceuticals and one artificial sweetener were conducted with powdered activated carbon. Ethanol, another LMW organic, was included in the study, as it is regularly used for pharmaceutical spiking thereby strongly increasing the DOC content. The experiments showed that the adsorption of the pharmaceuticals and the sweetener were hardly affected by the easily biodegradable LMW organics or ethanol. Therefore, it was concluded that biological pre-treatment is not necessary for efficient pharmaceutical adsorption. Since acetate, propionate and ethanol contribute substantially to the DOC content but do not absorb UV light, the latter is recommended as indicator for pharmaceutical removal in solutions with high contents of biodegradable LMW organics.