Metabolomics: small molecules that matter more

Artificial Intelligence in Metabolomics: A Current Review

Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics generates large datasets comprising hundreds to thousands of metabolites with complex relationships. AI, aiming to mimic human intelligence through computational modeling, possesses extraordinary capabilities for big data analysis. In this review, we provide a recent overview of the methodologies and applications of AI in metabolomics studies in the context of systems biology and human health. We first introduce the AI concept, history, and key algorithms for machine learning and deep learning, summarizing their strengths and weaknesses. We then discuss studies that have successfully used AI across different aspects of metabolomic analysis, including analytical detection, data preprocessing, biomarker discovery, predictive modeling, and multi-omics data integration. Lastly, we discuss the existing challenges and future perspectives in this rapidly evolving field. Despite limitations and challenges, the combination of metabolomics and AI holds great promises for revolutionary advancements in enhancing human health.

Metabolic profile of follicular fluid in patients with ovarian endometriosis undergoing IVF: a pilot study

RESEARCH QUESTION

What are the metabolic characteristics of follicular fluid in patients with ovarian endometriosis undergoing IVF?

DESIGN

This was an exploratory cohort study on endometriosis. In total, 19 infertile patients with ovarian endometriosis diagnosed by laparoscopy, and 23 controls matched in terms of age and body mass index (women with infertility due to male or tubal factors) were enrolled in this study. All patients underwent IVF treatment with a gonadotrophin-releasing hormone antagonist protocol, and follicular fluid was collected at oocyte retrieval. The metabolomics of follicular fluid samples was analysed using an ultra-high-performance liquid chromatography Orbitrap Exploris mass spectrometer (UHPLC-OE-MS). The best combination of biomarkers was selected by performing stepwise logistic regression analysis with backward elimination.

RESULTS

Fifteen metabolites were identified as biomarkers associated with endometriosis. A final model containing 8-hydroxy-2-deoxyguanosine, biotin, n-acetyl-L-methionine and n-methylnicotinamide was constructed. Receiver operating characteristic analysis confirmed the value of these parameters in diagnosing endometriosis, with sensitivity of 94.7% and specificity of 95.7%. Enrichment analysis via the Kyoto Encyclopedia of Genes and Genome showed that 15 metabolites were enriched in eight metabolic pathways.

CONCLUSION

Metabolomics based on UHPLC-OE-MS effectively characterized the metabolomics analysis of follicular fluid in patients with ovarian endometriosis. These findings may provide a new basis for better understanding of how diseases progress, and for the discovery of new biomarkers.

Metabolic Profiling Changes Induced by Fermented Blackberries in High-Fat-Diet-Fed Mice Utilizing Gas Chromatography-Mass Spectrometry Analysis

The aim of this study was to investigate the metabolic changes associated with the anti-obesity effects of fermented blackberry extracts in the liver tissues of high-fat-diet-fed mice using mass spectrometry-based metabolomics analysis. C57BL/6J mice were divided into eight groups: normal-diet-fed mice, high-fat-diet-fed mice, high-fat diet treated with blackberry extract, high-fat-diet mice treated with blackberry fermented by L. plantarum, and high-fat diet with blackberry fermented by L. brevis. After 12 weeks, the high-fat-diet group exhibited a greater increase in liver weight compared to the control group, and among the groups, the group administered with blackberry fermented with L. plantarum showed the most pronounced reduction in liver weight. As the primary organ responsible for amino acid metabolism, the liver is crucial for maintaining amino acid homeostasis. In our study, we observed that the levels of several essential amino acids, including isoleucine and valine, were decreased by the high-fat diet, and were recovered by administration of blackberry extract fermented with L. plantarum. Our results demonstrated the potential of blackberry extract fermented with L. plantarum as a functional material for metabolic disorders by restoring some of the amino acid metabolism disturbances induced by a high-fat diet.

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study

Objective

Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results.

Results

Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels.

Conclusion

The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

Elucidating the Phytochemical Landscape of Leaves, Stems, and Tubers of Codonopsis convolvulacea through Integrated Metabolomics

Codonopsis convolvulacea is a highly valued Chinese medicinal plant containing diverse bioactive compounds. While roots/tubers have been the main medicinal parts used in practice, leaves and stems may also harbor valuable phytochemicals. However, research comparing volatiles across tissues is lacking. This study performed metabolomic profiling of leaves, stems, and tubers of C. convolvulacea to elucidate tissue-specific accumulation patterns of volatile metabolites. Ultra-high performance liquid chromatography-tandem mass spectrometry identified 302 compounds, belonging to 14 classes. Multivariate analysis clearly differentiated the metabolic profiles of the three tissues. Numerous differentially accumulated metabolites (DAMs) were detected, especially terpenoids and esters. The leaves contained more terpenoids, ester, and alcohol. The stems accumulated higher levels of terpenoids, heterocyclics, and alkaloids with pharmaceutical potential. The tubers were enriched with carbohydrates like sugars and starch, befitting their storage role, but still retained reasonable amounts of valuable volatiles. The characterization of tissue-specific metabolic signatures provides a foundation for the selective utilization of C. convolvulacea parts. Key metabolites identified include niacinamide, p-cymene, tridecanal, benzeneacetic acid, benzene, and carveol. Leaves, stems, and tubers could be targeted for antioxidants, drug development, and tonics/nutraceuticals, respectively. The metabolomic insights can also guide breeding strategies to enhance the bioactive compound content in specific tissues. This study demonstrates the value of tissue-specific metabolite profiling for informing the phytochemical exploitation and genetic improvement of medicinal plants.

Overcoming donor variability and risks associated with fecal microbiota transplants through bacteriophage-mediated treatments

BACKGROUND

Fecal microbiota transplantation (FMT) and fecal virome transplantation (FVT, sterile filtrated donor feces) have been effective in treating recurrent Clostridioides difficile infections, possibly through bacteriophage-mediated modulation of the gut microbiome. However, challenges like donor variability, costly screening, coupled with concerns over pathogen transfer (incl. eukaryotic viruses) with FMT or FVT hinder their wider clinical application in treating less acute diseases.

METHODS

To overcome these challenges, we developed methods to broaden FVT's clinical application while maintaining efficacy and increasing safety. Specifically, we employed the following approaches: (1) chemostat-fermentation to reproduce the bacteriophage FVT donor component and remove eukaryotic viruses (FVT-ChP), (2) solvent-detergent treatment to inactivate enveloped viruses (FVT-SDT), and (3) pyronin-Y treatment to inhibit RNA virus replication (FVT-PyT). We assessed the efficacy of these processed FVTs in a C. difficile infection mouse model and compared them with untreated FVT (FVT-UnT), FMT, and saline.

RESULTS

FVT-SDT, FVT-UnT, and FVT-ChP reduced the incidence of mice reaching the humane endpoint (0/8, 2/7, and 3/8, respectively) compared to FMT, FVT-PyT, and saline (5/8, 7/8, and 5/7, respectively) and significantly reduced the load of colonizing C. difficile cells and associated toxin A/B levels. There was a potential elimination of C. difficile colonization, with seven out of eight mice treated with FVT-SDT testing negative with qPCR. In contrast, all other treatments exhibited the continued presence of C. difficile. Moreover, the results were supported by changes in the gut microbiome profiles, cecal cytokine levels, and histopathological findings. Assessment of viral engraftment following FMT/FVT treatment and host-phage correlations analysis suggested that transfer of phages likely were an important contributing factor associated with treatment efficacy.

CONCLUSIONS

This proof-of-concept study shows that specific modifications of FVT hold promise in addressing challenges related to donor variability and infection risks. Two strategies lead to treatments significantly limiting C. difficile colonization in mice, with solvent/detergent treatment and chemostat propagation of donor phages emerging as promising approaches. Video Abstract.

Using liquid chromatography and mass spectrometry to predict potential biomarkers for missed miscarriage and its metabolic pathways in a tertiary center: A cross-sectional analytic study

OBJECTIVE

To determine and compare the serum metabolites in missed abortion versus normal early pregnancy using ultra-high-performance liquid chromatography and tandem time-of-flight mass spectrometry, and to determine how these metabolites can be used to predict the potential biomarkers and possible metabolic pathways of a missed abortion.

METHODS

The serum of patients with a missed abortion was used as the experimental group and the serum of patients with an induced abortion during normal early pregnancy was used as the control group. Principal component analysis and orthogonal partial least square discriminant analysis were additionally used to observe the difference in metabolite distribution between the two groups. A variable weight value (variable importance in the projection; VIP) obtained from the orthogonal partial least squares discriminant analysis model more than 1 and P less than 0.05 were taken to indicate significant differences in metabolite screening. After this, enrichment analysis of the metabolic pathways of these metabolites was conducted using Fisher precise test in order to find the metabolic pathway with the highest correlation with the differential metabolites.

RESULTS

In total, 30 patients were included in the experimental group, with 30 patients in the control group. Fifty-five metabolites (VIP > 1, P < 0.05) with significant differences related to missed abortion were selected, among which 35 metabolites increased and 20 decreased in patients with a missed abortion. KEGG pathway enrichment analysis showed that the four metabolic pathways with the highest correlation were cholesterol metabolism, arginine biosynthesis, cell apoptosis, and the FoxO signaling pathway.

CONCLUSION

The missed abortion serum metabolites and changes in related metabolic pathways reported in this study provide a basis for the early prediction and diagnosis of a missed abortion.

The Omics Revolution in Understanding Chicken Reproduction: A Comprehensive Review

Omics approaches have significantly contributed to our understanding of several aspects of chicken reproduction. This review paper gives an overview of the use of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to elucidate the mechanisms of chicken reproduction. Genomics has transformed the study of chicken reproduction by allowing the examination of the full genetic makeup of chickens, resulting in the discovery of genes associated with reproductive features and disorders. Transcriptomics has provided insights into the gene expression patterns and regulatory mechanisms involved in reproductive processes, allowing for a better knowledge of developmental stages and hormone regulation. Furthermore, proteomics has made it easier to identify and quantify the proteins involved in reproductive physiology to better understand the molecular mechanisms driving fertility, embryonic development, and egg quality. Metabolomics has emerged as a useful technique for understanding the metabolic pathways and biomarkers linked to reproductive performance, providing vital insights for enhancing breeding tactics and reproductive health. The integration of omics data has resulted in the identification of critical molecular pathways and biomarkers linked with chicken reproductive features, providing the opportunity for targeted genetic selection and improved reproductive management approaches. Furthermore, omics technologies have helped to create biomarkers for fertility and embryonic viability, providing the poultry sector with tools for effective breeding and reproductive health management. Finally, omics technologies have greatly improved our understanding of chicken reproduction by revealing the molecular complexities that underpin reproductive processes.

Serum Metabolomics Reveals Metabolomic Profile and Potential Biomarkers in Asthma

PURPOSE

Asthma is a highly heterogeneous disease. Metabolomics plays a pivotal role in the pathogenesis and development of asthma. The main aims of our study were to explore the underlying mechanism of asthma and to identify novel biomarkers through metabolomics approach.

METHODS

Serum samples from 102 asthmatic patients and 18 healthy controls were collected and analyzed using liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) system. Multivariate analysis and weighted gene co-expression network analysis (WGCNA) were performed to explore asthma-associated metabolomics profile and metabolites. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Subsequently, 2 selected serum hub metabolites, myristoleic acid and dodecanoylcarnitine, were replicated in a validation cohort using ultra-high performance LC-MS/MS system (UHPLC-MS/MS).

RESULTS

Distinct metabolomics profile of asthma was revealed by multivariate analysis. Then, 116 overlapped asthma-associated metabolites between multivariate analysis and WGCNA, including 12 hub metabolites, were identified. Clinical features-associated hub metabolites were also identified by WGCNA. Among 116 asthma-associated metabolites, Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were revealed by KEGG analysis. Furthermore, serum myristoleic acid and dodecanoylcarnitine were significantly higher in asthmatic patients than in healthy controls in validation cohort. Additionally, serum myristoleic acid and dodecanoylcarnitine demonstrated high sensitivities and specificities in predicting asthma.

CONCLUSIONS

Collectively, asthmatic patients showed a unique serum metabolome. Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were involved in the pathogenesis of asthma. Furthermore, our results suggest the promising values of serum myristoleic acid and dodecanoylcarnitine for asthma diagnosis in adults.

Omics-based novel strategies in the diagnosis of endometriosis

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Applying GC-MS based serum metabolomic profiling to characterize two traditional Chinese medicine subtypes of diabetic foot gangrene

Traditional Chinese medicine (TCM) has a long history and particular advantages in the diagnosis and treatment of diabetic foot gangrene (DFG). Patients with DFG are mainly divided into two subtypes, tendon lesion with edema (GT) and ischemic lesion without edema (GI), which are suitable for different medical strategies. Metabolomics has special significance in unravelling the complexities of multifactorial and multisystemic disorders. This study acquired the serum metabolomic profiles of two traditional Chinese medicine subtypes of DFG to explore potential molecular evidence for subtype characterization, which may contribute to the personalized treatment of DFG. A total of 70 participants were recruited, including 20 with DM and 50 with DFG (20 with GI and 30 with GT). Conventional gas chromatography-mass spectrometry (GC-MS) followed by orthogonal partial least-squares discriminant analysis (OPLS-DA) were used as untargeted metabolomics approaches to explore the serum metabolomic profiles. Kyoto encyclopedia of genes and genomes (KEGG) and MetaboAnalyst were used to identify the related metabolic pathways. Compared with DM patients, the levels of 14 metabolites were altered in the DFG group, which were also belonged to the differential metabolites of GI (13) and GT (7) subtypes, respectively. Among these, urea, α-D-mannose, cadaverine, glutamine, L-asparagine, D-gluconic acid, and indole could be regarded as specific potential metabolic markers for GI, as well as L-leucine for GT. In the GI subtype, D-gluconic acid and L-asparagine are positively correlated with activated partial thromboplastin time (APTT) and fibrinogen (FIB). In the GT subtype, L-leucine is positively correlated with the inflammatory marker C-reactive protein (CRP). Arginine and proline metabolism, glycine, serine and threonine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis are the most important metabolic pathways associated with GI. The main metabolic pathways related to GT include pyrimidine metabolism, glutathione metabolism, biosynthesis of valine, leucine, and isoleucine, as well as valine, serine, and isoleucine with metabolites. The results of this study indicate that patients with different DFG subtypes have distinct metabolic profiles, which reflect the pathological characteristics of each subtype respectively. These findings will help us explore therapeutic targets for DFG and develop precise treatment strategies.

Untargeted metabolomics reveals that declined PE and PC in obesity may be associated with prostate hyperplasia

BACKGROUND

Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood.

METHODS

A prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF).

RESULTS

A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms.

CONCLUSIONS

In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Metabolomics in cirrhosis: Recent advances and opportunities

Liver cirrhosis (LC) represents a significant hepatic disorder that persistently commands the attention of the scientific community, especially concerning its pathogenesis and therapeutic approaches. Metabolomics, the comprehensive profiling of an organism's metabolome, has been increasingly applied in the research of cirrhosis over the past decade. This review summarizes the recent advancements and applications of metabolomics within the context of LC research, in recent five years. It highlights the role of metabolomics in the diagnosis of LC, the assessment of prognostic markers, and the evaluation of therapeutic outcomes. The discussion focuses on the potential and challenges of metabolomics in LC research, including the evolution of analytical technologies, advancements in bioinformatics, and the challenges impeding clinical implementation. Additionally, the review anticipates the forthcoming developments in metabolomics related to LC research, with the objective of facilitating innovative approaches for early detection and intervention in LC.

Metabolomics perspectives into the co-exposure effect of polycyclic aromatic hydrocarbons and metals on renal function: A meet-in-the-middle approach

Studies on the dose effects of kidney impairment and metabolomes in co-exposure to polycyclic aromatic hydrocarbons (PAHs) and metals are limited. We aimed to identify overall associations and metabolic perturbations in 130 participants (53 petrochemical workers and 77 controls) exposed to a PAHs-metals mixture in Southern China. The urinary 7 hydroxylated PAHs and 15 metal(loid)s were determined, and serum creatinine, beta-2 microglobulin, and estimated glomerular filtration rate were health outcomes. The liquid chromatography-mass spectrometry-based method was applied to serum metabolomics. Generalized weighted quantile sum (gWQS) regressions were used to estimate the overall dose-response relationships, and pathway analysis, "meet-in-the-middle" approach, and mediation effect analyses were conducted to identify potential metabolites and biological mechanisms linking exposure with nephrotoxic effects. Our results indicated that renal function reduction was associated with a PAHs-metals mixture in a dose-dependent manner, and 1-hydroxynaphthalene and copper were the most predominant contributors among the two families of pollutants. Furthermore, the metabolic disruptions associated with the early onset of kidney impairment induced by the combination of PAHs and metals encompassed pathways such as phenylalanine-tyrosine-tryptophan biosynthesis, phenylalanine metabolism, and alpha-linolenic acid metabolism. In addition, the specifically identified metabolites demonstrated excellent potential as bridging biomarkers connecting the reduction in renal function with the mixture of PAHs and metals. These findings shed light on understanding the overall associations and metabolic mechanism of nephrotoxic effects of co-exposure to PAHs and metals.

Metabolomic profiling of deep vein thrombosis

Deep vein thrombosis (DVT) of the lower extremities is one of the most common peripheral vascular diseases, with significant complications and sequelae. Metabolomics aims to identify small molecules in biological samples. It can serve as a promising method for screening compounds that can be used for early disease detection, diagnosis, treatment response prediction, and prognosis. In addition, high-throughput metabolomics screening can yield significant insights into the pathophysiological pathways of DVT. Currently, the metabolomic profiles of DVT have yielded inconsistent expression patterns. This article examines the recent advancements in metabolomic studies of DVT and analyzes the factors that may influence the results.

Integration of lipidomics and metabolomics reveals plasma and urinary profiles associated with pediatric Mycoplasma pneumoniae infections and its severity

Mycoplasma pneumoniae is a significant contributor to lower respiratory infections in children. However, the lipidomics and metabolics bases of childhood M. pneumoniae infections remain unclear. In this study, lipidomics and metabolomics analyses were conducted using UHPLC-LTQ-Orbitrap XL mass spectrometry and gas chromatography-triple quadrupole mass spectrometry on plasma (n = 65) and urine (n = 65) samples. MS-DIAL software, in combination with LipidBlast and Fiehn BinBase DB, identified 163 lipids and 104 metabolites in plasma samples, as well as 208 metabolites in urine samples. Perturbed lipid species (adjusted p < 0.05) were observed, including lysophosphatidylethanolamines, phosphatidylinositols, phosphatidylcholines, phosphatidylethanol amines, and triglycerides. Additionally, differential metabolites (adjusted p < 0.05) exhibited associations with amino acid metabolism, nucleotide metabolism, and energy metabolism. Thirteen plasma metabolites, namely l-hydroxyproline, 3-phosphoglycerate, citric acid, creatine, inosine, ribitol, α tocopherol, cholesterol, cystine, serine, uric acid, tagatose, and glycine, showed significant associations with disease severity (p < 0.05) and exhibited distinct separation patterns in M. pneumoniae-infected bronchitis and pneumonia, with an area under the curve of 0.927. Nine of them exhibited either positive or negative correlations with neutrophil or lymphocyte percentages. These findings indicated significant systemic metabolic shifts in childhood M. pneumoniae infections, offering valuable insights into the associated metabolic alterations and their relationship with disease severity.

Jianpi Gushen Huayu decoction ameliorated diabetic nephropathy through modulating metabolites in kidney, and inhibiting TLR4/NF-κB/NLRP3 and JNK/P38 pathways

BACKGROUND

Jianpi Gushen Huayu Decoction (JPGS) has been used to clinically treat diabetic nephropathy (DN) for many years. However, the protective mechanism of JPGS in treating DN remains unclear.

AIM

To evaluate the therapeutic effects and the possible mechanism of JPGS on DN.

METHODS

We first evaluated the therapeutic potential of JPGS on a DN mouse model. We then investigated the effect of JPGS on the renal metabolite levels of DN mice using non-targeted metabolomics. Furthermore, we examined the effects of JPGS on c-Jun N-terminal kinase (JNK)/P38-mediated apoptosis and the inflammatory responses mediated by toll-like receptor 4 (TLR4)/nuclear factor-kappa B (NF-κB)/NOD-like receptor family pyrin domain containing 3 (NLRP3).

RESULTS

The ameliorative effects of JPGS on DN mice included the alleviation of renal injury and the control of inflammation and oxidative stress. Untargeted metabolomic analysis revealed that JPGS altered the metabolites of the kidneys in DN mice. A total of 51 differential metabolites were screened. Pathway analysis results indicated that nine pathways significantly changed between the control and model groups, while six pathways significantly altered between the model and JPGS groups. Pathways related to cysteine and methionine metabolism; alanine, tryptophan metabolism; aspartate and glutamate metabolism; and riboflavin metabolism were identified as the key pathways through which JPGS affects DN. Further experimental validation showed that JPGS treatment reduced the expression of TLR4/NF-κB/NLRP3 pathways and JNK/P38 pathway-mediated apoptosis related factors.

CONCLUSION

JPGS could markedly treat mice with streptozotocin (STZ)-induced DN, which is possibly related to the regulation of several metabolic pathways found in kidneys. Furthermore, JPGS could improve kidney inflammatory responses and ameliorate kidney injuries in DN mice via the TLR4/NF-κB/NLRP3 pathway and inhibit JNK/P38 pathway-mediated apoptosis in DN mice.

Purine salvage-associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model-based study

Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage-associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680-0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.

Monotonic trends of soil microbiomes, metagenomic and metabolomic functioning across ecosystems along water gradients in the Altai region, northwestern China

To investigate microbial communities and their contributions to carbon and nutrient cycling along water gradients can enhance our comprehension of climate change impacts on ecosystem services. Thus, we conducted an assessment of microbial communities, metagenomic functions, and metabolomic profiles within four ecosystems, i.e., desert grassland (DG), shrub-steppe (SS), forest (FO), and marsh (MA) in the Altai region of Xinjiang, China. Our results showed that soil total carbon (TC), total nitrogen, NH4+, and NO3- increased, but pH decreased with soil water gradients. Microbial abundances and richness also increased with soil moisture except the abundances of fungi and protists being lowest in MA. A shift in microbial community composition is evident along the soil moisture gradient, with Proteobacteria, Basidiomycota, and Evosea proliferating but a decline in Actinobacteria and Cercozoa. The β-diversity of microbiomes, metagenomic, and metabolomic functioning were correlated with soil moisture gradients and have significant associations with specific soil factors of TC, NH4+, and pH. Metagenomic functions associated with carbohydrate and DNA metabolisms, as well as phages, prophages, TE, plasmids functions diminished with moisture, whereas the genes involved in nitrogen and potassium metabolism, along with certain biological interactions and environmental information processing functions, demonstrated an augmentation. Additionally, MA harbored the most abundant metabolomics dominated by lipids and lipid-like molecules and organic oxygen compounds, except certain metabolites showing decline trends along water gradients, such as N'-Hydroxymethylnorcotinine and 5-Hydroxyenterolactone. Thus, our study suggests that future ecosystem succession facilitated by changes in rainfall patterns will significantly alter soil microbial taxa, functional potential, and metabolite fractions.

Salivary Biomarkers for Alzheimer's Disease: A Systematic Review with Meta-Analysis

Alzheimer's Disease (AD) is the most common neurodegenerative disease which manifests with progressive cognitive impairment, leading to dementia. Considering the noninvasive collection of saliva, we designed the systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Alzheimer's Disease?" Following the inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Potential biomarkers include mainly proteins, metabolites and even miRNAs. Based on meta-analysis, in AD patients, salivary levels of beta-amyloid42 and p-tau levels were significantly increased, and t-tau and lactoferrin were decreased at borderline statistical significance. However, according to pooled AUC, lactoferrin and beta-amyloid42 showed a significant predictive value for salivary-based AD diagnosis. In conclusion, potential markers such as beta-amyloid42, tau and lactoferrin can be detected in the saliva of AD patients, which could reliably support the early diagnosis of this neurodegenerative disease.

Microbiota Implications in Endocrine-Related Diseases: From Development to Novel Therapeutic Approaches

This comprehensive review article delves into the critical role of the human microbiota in the development and management of endocrine-related diseases. We explore the complex interactions between the microbiota and the endocrine system, emphasizing the implications of microbiota dysbiosis for the onset and progression of various endocrine disorders. The review aims to synthesize current knowledge, highlighting recent advancements and the potential of novel therapeutic approaches targeting microbiota-endocrine interactions. Key topics include the impact of microbiota on hormone regulation, its role in endocrine pathologies, and the promising avenues of microbiota modulation through diet, probiotics, prebiotics, and fecal microbiota transplantation. We underscore the importance of this research in advancing personalized medicine, offering insights for more tailored and effective treatments for endocrine-related diseases.

Abnormal arginine synthesis confers worse prognosis in patients with middle third gastric cancer

BACKGROUND

Gastric cancer at different locations has distinct prognoses and biological behaviors, but the specific mechanism is unclear.

METHODS

Non-targeted metabolomics was performed to examine the differential metabolite phenotypes that may be associated with the effects of tumor location on the prognosis of gastric cancer. And silencing of the rate-limiting enzyme to evaluate the effect of abnormal changes in metabolic pathway on the functional biological assays of gastric cancer cells HGC-27 and MKN28.

RESULTS

In a retrospective study of 94 gastric cancer patients, the average survival time of patients with gastric cancer in the middle third of the stomach was significantly lower than that of patients with gastric cancer in other locations (p < 0.05). The middle third location was also found to be an independent risk factor for poor prognosis (HR = 2.723, 95%CI 1.334-5.520), which was closely associated with larger tumors in this location. Non-targeted metabolomic analysis showed that the differential metabolites affected 16 signaling pathways including arginine synthesis, retrograde endocannabinoid signaling, arginine biosynthesis, and alanine and aspartate and glutamate metabolism between gastric cancer and normal tissue, as well as between tumors located in the middle third of the stomach and other locations. Argininosuccinate synthetase 1 (ASS1), the rate-limiting enzyme of the arginine biosynthesis pathway, catalyzes the production of argininosuccinic acid. Here, knockdown of ASS1 significantly inhibited the proliferation, colony formation, and migration/invasion of gastric cancer cells, and promoted apoptosis.

CONCLUSIONS

Our study suggests that abnormal arginine synthesis may lead to larger tumor size and worse prognosis in gastric cancer located in the middle third position of the stomach. These findings may provide the basis for the stratification and targeted treatment of gastric cancer in different locations.

Low beauvericin concentrations promote PC-12 cell survival under oxidative stress by regulating lipid metabolism and PI3K/AKT/mTOR signaling

Beauvericin (BEA), a naturally occurring cyclic peptide with good pharmacological activity, has been widely explored in anticancer research. Although BEA is toxic, studies have demonstrated its antioxidant activity. However, to date, the antioxidant mechanisms of BEA remain unclear. Herein, we conducted a comprehensive and detailed study of the antioxidant mechanism of BEA using an untargeted metabolomics approach, subsequently validating the results. BEA concentrations of 0.5 and 1 μM significantly inhibited H2O2-induced oxidative stress (OS), decreased reactive oxygen species levels in PC-12 cells, and restored the mitochondrial membrane potential. Untargeted metabolomics indicated that BEA was primarily involved in lipid-related metabolism, suggesting its role in resisting OS in PC-12 cells by participating in lipid metabolism. BEA combated OS damage by increasing phosphatidylcholine, phosphatidylethanolamine, and sphingolipid levels. In the current study, BEA upregulated proteins related to the PI3K/AKT/mTOR pathway, thereby promoting cell survival. These findings support the antioxidant activity of BEA at low concentrations, warranting further research into its pharmacological effects.

Metabolomics analysis of the nutraceutical diversity and physiological quality of Torreya yunnanensis seeds during cold storage

This study investigated how cold storage affects the nutraceutical diversity and physiological quality of Torreya yunnanensis seeds, using a widely targeted UPLC-MS/MS-based metabolomics analysis. The 373 identified metabolites were divided into nine categories: lipids, phenolic acids, amino acids and derivatives, organic acids, nucleotides, saccharides, vitamins and alcohols. Among them, 49 metabolites showed significant changes after 3 months of cold storage, affecting 28 metabolic pathways. The content of amino acid-related metabolites significantly increased, while the content of sugar-related metabolites decreased during storage. Notably, the content of proline acid, shikimic acid, α-linolenic acid and branched-chain amino acids showed significant changes, indicating their potential role in seed storage. This study deepens our understanding of the nutraceutical diversity and physiological quality of T. yunnanensis seeds during storage, providing insight for conservation efforts and habitat restoration.

Metabolomics of natural samples: A tutorial review on the latest technologies

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early-career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early-career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

BRD4 facilitates osteogenic differentiation of human bone marrow mesenchymal stem cells through WNT4/NF-κB pathway

BACKGROUND

Human bone marrow mesenchymal stem cells (hBMSCs) are a major source of osteoblast precursor cells and are directly involved in osteoporosis (OP) progression. Bromodomain-containing protein 4 (BRD4) is an important regulator for osteogenic differentiation. Therefore, its role and mechanism in osteogenic differentiation process deserve further investigation.

METHODS

hBMSCs osteogenic differentiation was evaluated by flow cytometry, alkaline phosphatase assay and alizarin red staining. Western blot was used to test osteogenic differentiation-related proteins, BRD4 protein, WNT family members-4 (WNT4)/NF-κB-related proteins, and glycolysis-related proteins. Metabolomics techniques were used to detect metabolite changes and metabolic pathways. BRD4 and WNT4 mRNA levels were determined using quantitative real-time PCR. Dual-luciferase reporter assay and chromatin immunoprecipitation assay were performed to detect BRD4 and WNT4 interaction. Glycolysis ability was assessed by testing glucose uptake, lactic acid production, and ATP levels.

RESULTS

After successful induction of osteogenic differentiation, the expression of BRD4 was increased significantly. BRD4 knockdown inhibited hBMSCs osteogenic differentiation. Metabolomics analysis showed that BRD4 expression was related to glucose metabolism in osteogenic differentiation. Moreover, BRD4 could directly bind to the promoter of the WNT4 gene. Further experiments confirmed that recombinant WNT4 reversed the inhibition effect of BRD4 knockdown on glycolysis, and NF-κB inhibitors (Bardoxolone Methyl) overturned the suppressive effect of BRD4 knockdown on hBMSCs osteogenic differentiation.

CONCLUSION

BRD4 promoted hBMSCs osteogenic differentiation by inhibiting NF-κB pathway via enhancing WNT4 expression.

Lactic acid enhances vaginal epithelial barrier integrity and ameliorates inflammatory effects of dysbiotic short chain fatty acids and HIV-1

The vaginal microenvironment is key in mediating susceptibility to sexually transmitted infections. A polymicrobial environment with reduced Lactobacilllus spp. is characteristic of vaginal dysbiosis, associated with increased production of several short chain fatty acids (SCFAs), vaginal inflammation and an increased risk of HIV-1 acquisition. In contrast, a eubiotic vaginal microbiome (VMB), dominated by Lactobacillus spp. correlates with increased production of lactic acid (LA), an acidic milieu and protection against HIV-1. Vaginal metabolites, specifically LA and SCFAs including butyric, succinic and acetic acids are associated with modulation of HIV-1 risk. We assessed the impact of combined and individual SCFAs and LA on vaginal epithelial cells (VK2) grown in air-liquid interface cultures. Treatment of VK2 cells with eubiotic SCFA + LA mixture showed increased epithelial barrier integrity, reduced FITC dextran leakage and enhanced expression of cell-cell adhesion proteins. Treatment with dysbiotic SCFA + LA mixture diminished epithelial barrier integrity, increased NFκB activation and inflammatory mediators: TNF-α, IL-6, IL-8 and RANTES. LA was found to be the primary contributor of the beneficial effects. Eubiotic SCFA + LA mixture ameliorated HIV-1 mediated barrier disruption and HIV-1 leakage, whereas dysbiotic SCFA + LA treatment exacerbated HIV-1 effects. These findings indicate a key role for LA in future prophylactic strategies.

Gut Microbiota According to the Metabolome

The human gut microbiota is an ecosystem harboring trillions of microorganisms, encompassing bacteria, viruses, archaea, fungi, and protozoa [...].

Nuclear magnetic resonance-based metabolomic study of rat serum after anterior cruciate ligament injury

Anterior cruciate ligament (ACL) injury, a common sports injury, is associated with a high risk of subsequent osteoarthritis (OA), which can cause serious pain and disability. Understanding the detailed mechanism underlying the predisposition of knee with ACL injury to secondary OA at an early stage is key to preventing future degradation and progression to a clinically significant disease. A total of 56 male Sprague Dawley rats (age, 8 weeks; weight, 180-220 g) were randomly divided into three experimental groups: control, ACL transection (ACLT; where surgical procedure was performed with ACLT), and sham (where surgical procedure was performed without ACLT). The ACLT and sham groups were further divided into three subgroups based on when the rats were sacrificed: 4, 8, and 12 weeks after the surgical procedure. The control group and the aforementioned subgroups contained 8 rats each. We used nuclear magnetic resonance (NMR)-based metabolomic analysis to analyze rat serum samples for the metabolic characteristics and the underlying mechanisms. In total, 28 metabolites were identified in the NMR spectra of the rat sera. At 4 and 8 weeks postoperatively, the sham group demonstrated metabolic profiles different from those of the ACLT group. However, this difference was not observed 12 weeks postoperatively. In total, five metabolites (acetate, succinate, sn-glycero-3-phosphocholine, glucose, and phenylalanine) and five metabolic pathways (phenylalanine, tyrosine, and tryptophan biosynthesis; phenylalanine metabolism; pyruvate metabolism; starch and sucrose metabolism; and histidine metabolism) demonstrated significant differences between the ACLT and sham groups. ACL injury was noted to considerably affect biochemical homeostasis and metabolism; however, these metabolic changes persisted briefly. Moreover, glucose was a characteristic metabolite, and several energy-related metabolic pathways were significantly disturbed. Therefore, an ACL injury may lead to considerable impairments in energy metabolism. Abnormal glucose levels facilitate chondrocyte function impairment and thereby lead to OA progression. Furthermore, lactate may aid in identifying metabolic changes specific to knee trauma not related to an ACL injury. Overall, the metabolic changes in rat serum after an ACL injury were closely related to disturbances in energy metabolism and amino acid metabolism. The current results may aid in understanding the pathogenesis of posttraumatic osteoarthritis.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

Metabolomics in archaeological science: A review of their advances and present requirements

Metabolomics, the study of metabolites (small molecules of <1500 daltons), has been posited as a potential tool to explore the past in a comparable manner to other omics, e.g., genomics or proteomics. Archaeologists have used metabolomic approaches for a decade or so, mainly applied to organic residues adhering to archaeological materials. Because of advances in sensitivity, resolution, and the increased availability of different analytical platforms, combined with the low mass/volume required for analysis, metabolomics is now becoming a more feasible choice in the archaeological sector. Additional approaches, as presented by our group, show the versatility of metabolomics as a source of knowledge about the human past when using human osteoarchaeological remains. There is tremendous potential for metabolomics within archaeology, but further efforts are required to position it as a routine technique.

Comprehensive metabolic profiling of diabetic retinopathy

Diabetic retinopathy (DR) is an important complication of diabetes mellitus and a prevalent blind-causing ophthalmic disease. Despite years of efforts, rapid and accurate diagnosis of DR remains a challenging task. Metabolomics has been used as a diagnostic tool for disease progression and therapy monitoring. In this study, retinal tissues were collected from diabetic mice and age-matched non-diabetic mice. An unbiased metabolic profiling was performed to identify the altered metabolites and metabolic pathways in DR. 311 differential metabolites were identified between diabetic retinas and non-diabetic retinas under the criteria of variable importance in projection (VIP) > 1 and P < 0.05. These differential metabolites were highly enriched in purine metabolism, amino acid metabolism, glycerophospholipid metabolism, and pantaothenate and CoA biosynthesis. We then evaluated the sensitivity and specificity of purine metabolites as the candidate biomarkers for DR through the area under the receiver-operating characteristic curves (AUC-ROCs). Compared with other purine metabolites, adenosine, guanine, and inosine had higher sensitivity, specificity, and accuracy for DR prediction. In conclusion, this study sheds new light on the metabolic mechanism of DR, which can facilitate clinical diagnosis, therapy, and prognosis of DR in the future.

Analysis of Metabolites in Gout: A Systematic Review and Meta-Analysis

(1) Background: Many studies have attempted to explore potential biomarkers for the early detection of gout, but consistent and high levels of evidence are lacking. In this study, metabolomics was used to summarize the changes of metabolites in the literature and explore the potential value of metabolites in predicting the occurrence and development of gout. (2) Methods: We searched the databases including the EMBASE, the Cochrane Library, PubMed, Web of Science, VIP Date, Wanfang Data, and CNKI, and the screening was fulfilled on 30 July 2022. The records were screened according to the inclusion criteria and the risk of bias was assessed. Qualitative analysis was performed for all metabolites, and meta-analysis was performed for metabolite concentrations using random effects to calculate the Std mean difference and 95% confidence interval. (3) Results: A total of 2738 records were identified, 33 studies with 3422 participants were included, and 701 metabolites were identified. The qualitative analysis results showed that compared with the healthy control group, the concentration of 56 metabolites increased, and 22 metabolites decreased. The results of the meta-analysis indicated that 17 metabolites were statistically significant. (4) Conclusions: Metabolites are associated with gout. Some specific metabolites such as uric acid, hypoxanthine, xanthine, KYNA, guanosine, adenosine, creatinine, LB4, and DL-2-Aminoadipic acid have been highlighted in the development of gout.

What makes people grow? Love and hope

BACKGROUND

Hope and love are popular themes of literature and art in many human societies. The human physiology of love and hope is less well understood. This review presents evidence that the lack of love and/or hope delays growth disturbs development and maturation and even kills.

MAIN BODY

Love and hope intersect in promoting healthy human development. Love provides a sense of security and attachment, which are necessary for healthy physical, cognitive, and emotional development. Hope provides a sense of optimism and resilience in the face of adversity. Loving relationships can foster a sense of hope in individuals and in society by providing support systems during difficult times. Similarly, having a sense of hope can make it easier to form loving relationships by providing individuals with the confidence to connect with others. Hope and love are the fundamental basis of human biocultural reproduction, which is the human style of cooperation in the production, feeding, and care of offspring. Examples are given of the association between human growth in height with love and hope, including (1) the global "Long Depression" of 1873-1896, (2) "hospitalism" and the abuse/neglect of infants and children, (3) adoption, (4) international migration, (5) colonial conquest, and (6) social, economic, and political change in Japan between 1970 and 1990.

CONCLUSION

Overall, this review suggests that love and hope are both critical factors in promoting healthy human development and that they intersect in complex ways to support emotional well-being.

Moderate hypoxia induces metabolic divergence in circulating monocytes and tissue resident macrophages from Berkeley sickle cell anemia mice

Introduction

Human and murine sickle cell disease (SCD) associated pulmonary hypertension (PH) is defined by hemolysis, nitric oxide depletion, inflammation, and thrombosis. Further, hemoglobin (Hb), heme, and iron accumulation are consistently observed in pulmonary adventitial macrophages at autopsy and in hypoxia driven rodent models of SCD, which show distribution of ferric and ferrous Hb as well as HO-1 and ferritin heavy chain. The anatomic localization of these macrophages is consistent with areas of significant vascular remodeling. However, their contributions toward progressive disease may include unique, but also common mechanisms, that overlap with idiopathic and other forms of pulmonary hypertension. These processes likely extend to the vasculature of other organs that are consistently impaired in advanced SCD.

Methods

To date, limited information is available on the metabolism of macrophages or monocytes isolated from lung, spleen, and peripheral blood in humans or murine models of SCD.

Results

Here we hypothesize that metabolism of macrophages and monocytes isolated from this triad of tissue differs between Berkley SCD mice exposed for ten weeks to moderate hypobaric hypoxia (simulated 8,000 ft, 15.4% O2) or normoxia (Denver altitude, 5000 ft) with normoxia exposed wild type mice evaluated as controls.

Discussion

This study represents an initial set of data that describes the metabolism in monocytes and macrophages isolated from moderately hypoxic SCD mice peripheral lung, spleen, and blood mononuclear cells.

Recent advances in proteomic-based diagnostics of cystic fibrosis

INTRODUCTION

Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF.

AREAS COVERED

We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers.

EXPERT OPINION

Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.

The combined analysis of urine and blood metabolomics profiles provides an accurate prediction of the training and competitive status of Chinese professional swimmers

Objective: The purpose of this study was to employ metabolomics for the analysis of urine metabolites in swimmers, with the aim of establishing models for assessing their athletic status and competitive potential. Furthermore, the study sought to compare the identification efficacy of multi-component (urine and blood) model versus single-component (urine or blood) models, in order to determine the optimal approach for evaluating training and competitive status. Methods: A total of 187 Chinese professional swimmers, comprising 103 elite and 84 sub-elite level athletes, were selected as subjects for this study. Urine samples were obtained from each participant and subjected to nuclear magnetic resonance (NMR) metabolomics analysis. Significant urine metabolites were screened through multivariable logistic regression analysis, and an identification model was established. Based on the previously established model of blood metabolites, this study compared the discriminative and predictive performance of three models: either urine or blood metabolites model and urine + blood metabolites model. Results: Among 39 urine metabolites, 10 were found to be significantly associated with the athletic status of swimmers (p < 0.05). Of these, levels of 2-KC, cis-aconitate, formate, and LAC were higher in elite swimmers compared to sub-elite athletes, while levels of 3-HIV, creatinine, 3-HIB, hippurate, pseudouridine, and trigonelline were lower in elite swimmers. Notably, 2-KC and 3-HIB exhibited the most substantial differences. An identification model was developed to estimate physical performance and athletic level of swimmers while adjusting for different covariates and including 2-KC and 3-HIB. The urine metabolites model showed an area under the curve (AUC) of 0.852 (95% CI: 0.793-0.912) for discrimination. Among the three identification models tested, the combination of urine and blood metabolites showed the highest performance than either urine or blood metabolites, with an AUC of 0.925 (95% CI: 0.888-0.963). Conclusion: The two urine metabolites, 2-KC and 3-HIV, can serve as significant urine metabolic markers to establish a discrimination model for identifying the athletic status and competitive potential of Chinese elite swimmers. Combining two screened urine metabolites with four metabolites reported exhibiting significant differences in blood resulted in improved predictive performance compared to using urine metabolites alone. These findings indicate that combining blood and urine metabolites has a greater potential for identifying and predicting the athletic status and competitive potential of Chinese professional swimmers.

The Impact of the Serum Extraction Protocol on Metabolomic Profiling Using UPLC-MS/MS and FTIR Spectroscopy

Biofluid metabolomics is a very appealing tool to increase the knowledge associated with pathophysiological mechanisms leading to better and new therapies and biomarkers for disease diagnosis and prognosis. However, due to the complex process of metabolome analysis, including the metabolome isolation method and the platform used to analyze it, there are diverse factors that affect metabolomics output. In the present work, the impact of two protocols to extract the serum metabolome, one using methanol and another using a mixture of methanol, acetonitrile, and water, was evaluated. The metabolome was analyzed by ultraperformance liquid chromatography associated with tandem mass spectrometry (UPLC-MS/MS), based on reverse-phase and hydrophobic chromatographic separations, and Fourier transform infrared (FTIR) spectroscopy. The two extraction protocols of the metabolome were compared over the analytical platforms (UPLC-MS/MS and FTIR spectroscopy) concerning the number of features, the type of features, common features, and the reproducibility of extraction replicas and analytical replicas. The ability of the extraction protocols to predict the survivability of critically ill patients hospitalized at an intensive care unit was also evaluated. The FTIR spectroscopy platform was compared to the UPLC-MS/MS platform and, despite not identifying metabolites and consequently not contributing as much as UPLC-MS/MS in terms of information concerning metabolic information, it enabled the comparison of the two extraction protocols as well as the development of very good predictive models of patient's survivability, such as the UPLC-MS/MS platform. Furthermore, FTIR spectroscopy is based on much simpler procedures and is rapid, economic, and applicable in the high-throughput mode, i.e., enabling the simultaneous analysis of hundreds of samples in the microliter range in a couple of hours. Therefore, FTIR spectroscopy represents a very interesting complementary technique not only to optimize processes as the metabolome isolation but also for obtaining biomarkers such as those for disease prognosis.

Involvement of p38 MAPK/cPLA2 and arachidonic acid metabolic pathway in Shengmai injection-induced pseudo-allergic reactions

ETHNOPHARMACOLOGICAL RELEVANCE

Adverse reactions to traditional Chinese medicine injections involve pseudo-allergic reactions (PARs). However, in clinical practice, "immediate allergic reactions" and PARs in response to these injections are not often differentiated.

AIM OF THE STUDY

This study aimed to clarify the type of reactions produced by Shengmai injections (SMI) and elucidate the possible mechanism.

MATERIALS AND METHODS

A mouse model was used to evaluate vascular permeability. Metabolomic and arachidonic acid metabolite (AAM) analyses were performed using UPLC-MS/MS, and the p38 MAPK/cPLA2 pathway was detected by western blotting.

RESULTS

The first exposure to intravenous SMI rapidly and dose-dependently induced edema and exudative reactions in the ears and lungs. These reactions were not IgE-dependent and were likely to be PARs. Metabolomic analysis showed that endogenous substances were perturbed in SMI-treated mice, in which the arachidonic acid (AA) metabolic pathway was the most affected. SMI substantially increased the levels of AAMs in lung, including prostaglandins (PGs), leukotrienes (LTs), and hydroxy-eicosatetraenoic acids (HETEs). The p38 MAPK/cPLA2 signaling pathway was activated after a single SMI dose. Inhibitors of cyclooxygenase-2 and 5-lipoxygenase enzymes reduced exudation and inflammation in the ears and lungs of mice.

CONCLUSION

Production of inflammatory factors that increase vascular permeability may result in SMI-induced PARs, and p38 MAPK/cPLA2 signaling pathway and downstream AA metabolic pathway are involved in the reactions.

Maternal microbiota and gestational diabetes: impact on infant health

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that has been associated with an increased risk of obesity and diabetes in the offspring. Pregnancy is accompanied by tightly regulated changes in the endocrine, metabolic, immune, and microbial systems, and deviations from these changes can alter the mother's metabolism resulting in adverse pregnancy outcomes and a negative impact on the health of her infant. Maternal microbiomes are significant drivers of mother and child health outcomes, and many microbial metabolites are likely to influence the host health. This review discusses the current understanding of how the microbiota and microbial metabolites may contribute to the development of GDM and how GDM-associated changes in the maternal microbiome can affect infant's health. We also describe microbiota-based interventions that aim to improve metabolic health and outline future directions for precision medicine research in this emerging field.

LC/MS-Based Untargeted Metabolomics Study in Women with Nonalcoholic Steatohepatitis Associated with Morbid Obesity

This study investigated the importance of a metabolomic analysis in a complex disease such as nonalcoholic steatohepatitis (NASH) associated with obesity. Using an untargeted metabolomics technique, we studied blood metabolites in 216 morbidly obese women with liver histological diagnosis. A total of 172 patients were diagnosed with nonalcoholic fatty liver disease (NAFLD), and 44 were diagnosed with normal liver (NL). Patients with NAFLD were classified into simple steatosis (n = 66) and NASH (n = 106) categories. A comparative analysis of metabolites levels between NASH and NL demonstrated significant differences in lipid metabolites and derivatives, mainly from the phospholipid group. In NASH, there were increased levels of several phosphatidylinositols and phosphatidylethanolamines, as well as isolated metabolites such as diacylglycerol 34:1, lyso-phosphatidylethanolamine 20:3 and sphingomyelin 38:1. By contrast, there were decreased levels of acylcarnitines, sphingomyelins and linoleic acid. These findings may facilitate identification studies of the main pathogenic metabolic pathways related to NASH and may also have a possible applicability in a panel of metabolites to be used as biomarkers in future algorithms of the disease diagnosis and its follow-up. Further confirmatory studies in groups with different ages and sexes are necessary.

Metabolomics of infectious diseases in the era of personalized medicine

Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.

Metabolomics Approach Reveals Important Glioblastoma Plasma Biomarkers for Tumor Biology

Glioblastoma (GB) is the most aggressive and frequent primary malignant tumor of the central nervous system and is associated with poor overall survival even after treatment. To better understand tumor biochemical alterations and broaden the potential targets of GB, this study aimed to evaluate differential plasma biomarkers between GB patients and healthy individuals using metabolomics analysis. Plasma samples from both groups were analyzed via untargeted metabolomics using direct injection with an electrospray ionization source and an LTQ mass spectrometer. GB biomarkers were selected via Partial Least Squares Discriminant and Fold-Change analyses and were identified using tandem mass spectrometry with in silico fragmentation, consultation of metabolomics databases, and a literature search. Seven GB biomarkers were identified, some of which were unprecedented biomarkers for GB, including arginylproline (m/z 294), 5-hydroxymethyluracil (m/z 143), and N-acylphosphatidylethanolamine (m/z 982). Notably, four other metabolites were identified. The roles of all seven metabolites in epigenetic modulation, energy metabolism, protein catabolism or folding processes, and signaling pathways that activate cell proliferation and invasion were elucidated. Overall, the findings of this study highlight new molecular targets to guide future investigations on GB. These molecular targets can also be further evaluated to derive their potential as biomedical analytical tools for peripheral blood samples.

Transcriptomics and metabolomics analysis of L-phenylalanine overproduction in Escherichia coli

BACKGROUND

Highly efficient production of L-phenylalanine (L-Phe) in E. coli has been achieved by multiple rounds of random mutagenesis and modification of key genes of the shikimate (SHIK) and L-Phe branch pathways. In this study, we performed transcriptomic (16, 24 and 48 h) and metabolomic analyses (8, 16, 24, 32,40, and 48 h) based on time sequences in an engineered E. coli strain producing L-Phe, aiming to reveal the overall changes of metabolic activities during the fermentation process.

RESULTS

The largest biomass increase rate and the highest production rate were seen at 16 h and 24 h of fermentation, respectively reaching 5.9 h^-1 and 2.76 g/L/h, while the maximal L-Phe titer of 60 g/L was accumulated after 48 h of fermentation. The DEGs and metabolites involved in the EMP, PP, TCA, SHIIK and L-Phe-branch pathways showed significant differences at different stages of fermentation. Specifically, the significant upregulation of genes encoding rate-limiting enzymes (aroD and yidB) and key genes (aroF, pheA and aspC) pushed more carbon flux toward the L-Phe synthesis. The RIA changes of a number of important metabolites (DAHP, DHS, DHQ, Glu and PPN) enabled the adequate supply of precursors for high-yield L-Phe production. In addition, other genes related to Glc transport and phosphate metabolism increased the absorption of Glc and contributed to rerouting the carbon flux into the L-Phe-branch.

CONCLUSIONS

Transcriptomic and metabolomic analyses of an L-Phe overproducing strain of E. coli confirmed that precursor supply was not a major limiting factor in this strain, whereas the rational distribution of metabolic fluxes was achieved by redistributing the carbon flux (for example, the expression intensity of the genes tyrB, aspC, aroL and aroF/G/H or the activity of these enzymes is increased to some extent), which is the optimal strategy for enhancing L-Phe production.

Serum and urine metabolomics analyses reveal metabolic pathways and biomarkers in relation to nasopharyngeal carcinoma

RATIONALE

Nasopharyngeal carcinoma (NPC) is a malignant tumor that is endemic in Southeast Asia, North Africa, and southern China. There is an urgent need for effective early diagnosis and treatment of this disease since NPC is currently often detected at advanced stages.

METHODS

To reveal the underlying metabolic mechanisms and discover potential diagnostic biomarkers of NPC, we employed ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) and UHPLC-Q-Exactive Orbitrap MS, respectively, to analyze 54 serum samples and 54 urine samples from 27 patients with NPC and 27 healthy control individuals.

RESULTS

A total of 1230 metabolites were determined in serum samples, and 181 of the 1230 metabolites were significantly changed in NPC patients. The 181 metabolites were enriched in 16 pathways, including biosynthesis of unsaturated fatty acids, cholesterol metabolism, and ferroptosis. A total of 2509 metabolites were detected in the urine samples. Among them, 179 metabolites were significantly altered in NPC patients, and these metabolites were enriched in eight pathways, including the tricarboxylic acid (TCA) cycle and caffeine metabolism. Seven metabolites, including creatinine and paraxanthine, were found to be significantly changed in both NPC serum and urine samples. Based on them, further biomarker analysis revealed that the panel of three serum metabolites, octanoylcarnitine, creatinine, and decanoyl-l-carnitine, displayed a perfect diagnostic performance (area under the curve [AUC] = 0.973) to distinguish NPC patients from controls, while the other three-metabolite biomarker panel, consisting of stachydrine, decanoyl-l-carnitine, and paraxanthine, had an AUC = 0.809 to distinguish NPC and control in urine samples.

CONCLUSION

This work highlights the key metabolites and metabolic pathways disturbed in NPC and presents potential biomarkers for effective diagnosis of this disease.

Targeted and non-targeted metabolomics uncovering the effects of Er-Miao-Wan formula on rats with hyperuricemia

Er-Miao-Wan formula (EMW), composed of Phellodendri Chinensis Cortex and Atractylodis Rhizoma, is widely used in the treatment of hyperuricemia (HUA), gout, and related complications as a classic compound formula. However, its mechanisms for the treatment of HUA still need to be further systematically investigated. The study aimed to perform modern analytical techniques to elucidate the mechanisms of EMW in improving the symptoms of HUA from the perspective of metabolomics. We used a high-fructose diet to establish a rat model of HUA to evaluate the effects of EMW on improving HUA. Next, we established a targeted metabolomics analysis method to quantitatively analyze purine metabolites in plasma by using ultra-high-performance liquid chromatography with ultraviolet and triple quadrupole mass spectrometry (UHPLC-UV-QQQ MS), and combined with plasma non-targeted metabolomics analysis by using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF MS) to clarify the potential mechanisms of EMW to improve HUA. Oral administration of EMW could significantly increase the urinary uric acid and decrease the serum uric acid, and exhibited a remarkable effect on improving HUA. Plasma targeted metabolomics analysis showed that six purine metabolites related to HUA, including uric acid, hypoxanthine, xanthine, deoxyadenosine, deoxyguanosine, and deoxyinosine, were changed in the EMW-treated group. Further, principal component analysis (PCA) and partial least squares discrimination analysis (PLS-DA) showed that the mechanism of EMW interfering with purine metabolic pathway in the rats with HUA could be different from that of allopurinol. On the basis of plasma non-targeted metabolomics, PCA and orthogonal partial least squares discriminant analysis (OPLA-DA) screened and identified 23 potential biomarkers in the rats with HUA, and 11 biomarkers showed a trend of reversion after the intervention of EMW. The pathway analysis suggested that EMW might have therapeutic effects on the rats with HUA via the metabolic pathways including phenylalanine metabolism, glycerophospholipid metabolism, and tryptophan metabolism. In this study, a plasma targeted metabolomics method that can simultaneously quantify nine purine metabolites in rats with HUA was established for the first time, which can be used to study diseases closely related to HUA. In addition, we further explored the overall effect of EMW on HUA in combination with the metabonomic method established by non-targeted metabolomics, which was helpful to solve the defect that the pharmacological mechanism caused by multi-components and multi-targets of traditional Chinese medicine was difficult to explain scientifically and comprehensively. In summary, EMW could effectively alleviate the symptoms of high-fructose-induced HUA, and the study provided a reference for the potential therapeutic mechanism of EMW.

Uveal Melanoma Patients Have a Distinct Metabolic Phenotype in Peripheral Blood

Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.

New insight of metabolomics in ocular diseases in the context of 3P medicine

Metabolomics refers to the high-through untargeted or targeted screening of metabolites in biofluids, cells, and tissues. Metabolome reflects the functional states of cells and organs of an individual, influenced by genes, RNA, proteins, and environment. Metabolomic analyses help to understand the interaction between metabolism and phenotype and reveal biomarkers for diseases. Advanced ocular diseases can lead to vision loss and blindness, reducing patients' quality of life and aggravating socio-economic burden. Contextually, the transition from reactive medicine to the predictive, preventive, and personalized (PPPM / 3P) medicine is needed. Clinicians and researchers dedicate a lot of efforts to explore effective ways for disease prevention, biomarkers for disease prediction, and personalized treatments, by taking advantages of metabolomics. In this way, metabolomics has great clinical utility in the primary and secondary care. In this review, we summarized much progress achieved by applying metabolomics to ocular diseases and pointed out potential biomarkers and metabolic pathways involved to promote 3P medicine approach in healthcare.

Lipid dysregulation associated with progression of silica-induced pulmonary fibrosis

Silicosis is an irreversible, progressive, fibrotic lung disease caused by long-term exposure to dust-containing silica particles at the workplace. Despite the precautions enforced, the rising incidence of silicosis continues to occur globally, particularly in developing countries. A better understanding of the disease progression and potential metabolic reprogramming of silicosis is warranted. The low- or high-dose silica-induced pulmonary fibrosis in mice was constructed to mimic chronic or accelerated silicosis. Silica-induced mice lung fibrosis was analyzed by histology, lung function, and computed tomography scans. Non-targeted metabolomics of the lung tissues was conducted by ultra-high-performance liquid chromatography-mass spectrometry to show the temporal metabolic trajectory. The low-dose silica-induced silicosis characterized inflammation for up to 42 days, with the onset of cellular silicon nodules. Conversely, the high-dose silica-induced silicosis characterized inflammation for up to 14 days, after which the disease developed rapidly, with a large volume of collagen deposition, presenting progressive massive fibrosis. Both low- and high silica-induced fibrosis had aberrant lipid metabolism. Combined with the RNA-Seq data, this multiomics study demonstrated alterations in the enzymes involved in sphingolipid metabolism. Time-dependent metabolic reprogramming revealing abnormal glycerophospholipid metabolism was intimately associated with the process of inflammation, whereas sphingolipid metabolism was crucial during lung fibrosis. These findings suggest that lipid dysregulation, especially sphingolipid metabolism, was involved in the process of silicosis.

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study

BACKGROUND

Endometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography-mass spectrometer (GC-MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers.

METHODS

Twenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC-MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis.

RESULTS

Partial least squares discriminant analysis was performed to determine the differences between the two groups (p = 0.003). Threonic acid, 3-hydroxybutyric acid, and proline increased significantly in endometriosis patients, while alanine and valine decreased. ROC curves were built to test the diagnostic power of metabolites. The pathway analysis identified the synthesis and degradation of ketone bodies and the biosynthesis of phenylalanine, tyrosine, and tryptophan as the most altered pathways.

CONCLUSIONS

The metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers.