Metabolomics in the Diagnosis of Bacterial Infections

One of the essential factors in the appropriate treatment of infections is accurate and timely laboratory diagnosis. The correct diagnosis of infections plays a vital role in determining desirable therapy and controlling the spread of pathogens. Traditional methods of infection diagnosis are limited by several factors such as insufficient sensitivity and specificity, being time-consuming and laborious, having a low ability to distinguish infection from non-infectious inflammatory conditions and a low potential to predict treatment outcomes. Therefore, it is necessary to find innovative strategies for detecting specific biomarkers in order to diagnose infections. The rapid advancement of metabolomics makes it possible to determine the pattern of metabolite changes in the both of pathogen and the host during an infection. Metabolomics is a method used to assess the levels and type of metabolites in an organism. Metabolites are of low-molecular-weight compounds produced as a result of metabolic processes and pathways within cells. Metabolomics provides valuable data to detect accurate biomarkers of specific biochemical features directly related to certain phenotypes or conditions. This study aimed to review the applications and progress of metabolomics as a biomarker for the diagnosis of bacterial infections.

High-Throughput and Untargeted Metabolic Profiling Revealed the Potential Effect and Mechanisms of Paeoniflorin in Young Asthmatic Rats

Paeoniflorin (PF) is a multi-target monoterpenoid glycoside and possesses broad pharmacological functions, e.g., anti-inflammation, anti-depression, antitumor, abirritation, neuroprotection, antioxidant, and enhancing cognitive and learning ability. PF has gained a large amount of attention for its effect on asthma disease as the growth rate of asthma has increased in recent years. However, its mechanism of action on asthma is still unclear. In this study, we have explored the action mechanism of PF on asthma disease. Furthermore, high-throughput untargeted metabolic profiling was performed through ultraperformance liquid chromatography/electrospray ionization quadruple time-of-flight high-definition mass spectrometry (QA) UPLC-Q/TOF-MS combined with pattern recognition approaches and pathway analysis. A total of 20 potential biomarkers were discovered by UPLC/MS and urine metabolic profiling. The key pathways including the citrate cycle (the TCA cycle), pyrimidine metabolism, pentose phosphate pathway, tyrosine metabolism, and tryptophan metabolism were affected by PF. In conclusion, we have discovered metabolite biomarkers and revealed the therapeutic mechanism of PF based on liquid chromatography coupled with mass spectrometry untargeted metabolomics. The untargeted metabolomics combined with UPLC-MS is a useful tool for exploring the therapeutic mechanism and targets of PF in the treatment of asthma. Metabolomics combined with UPLC-MS is an integrated method to explore the metabolic mechanism of PF in the treatment of asthma rats and to reveal the potential targets, providing theoretical support for the study of the treatment of PF.

Gender-specific association of oxidative stress and immune response in septic shock mortality using NMR-based metabolomics

Background: Sepsis and septic shock are still associated with a high mortality rate. The early-stage prediction of septic shock outcomes would be helpful to clinicians for designing their treatment protocol. In addition, it would aid clinicians in patient management by understanding gender disparity in terms of clinical outcomes of septic shock by identifying whether there are sex-based differences in sepsis-associated mortality. Objective: This study aimed to test the hypothesis that gender-based metabolic heterogeneity is associated with sepsis survival and identify the biomarkers of mortality for septic shock in an Indian cohort. Method: The study was performed in an Indian population cohort diagnosed with sepsis/septic shock within 24 hours of admission. The study group was 50 patients admitted to intensive care, comprising 23 females and 27 males. Univariate and multivariate analysis were performed to identify the biomarkers for septic shock mortality and the gender-specific metabolic fingerprint in septic shock-associated mortality. Results: The energy-related metabolites, ketone bodies, choline, and NAG were found to be primarily responsible for differentiating survivors and non-survivors. The gender-based mortality stratification identified a female-specific association of the anti-inflammatory response, innate immune response, and β oxidation, and a male-specific association of the pro-inflammatory response to septic shock. Conclusion: The identified mortality biomarkers may help clinicians estimate the severity of a case, as well as predict the outcome and treatment efficacy. The study underlines that gender is one of the most significant biological factors influencing septic shock metabolomic profiles. This understanding can be utilized to identify novel gender-specific biomarkers and innovative targets relevant for gender medicine.

Metabolomics: An emerging potential approach to decipher critical illnesses

Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.

High-throughput metabolomics discovers metabolite biomarkers and insights the protective mechanism of schisandrin B on myocardial injury rats

Schisandrin B has been proved to possess anti-inflammatory and anti-endoplasmic effects, could improve cardiac function, inhibit apoptosis, and reduce inflammation after ischemic injury. However, the detailed metabolic mechanism and potential pathways of Schisandrin B effects on myocardial injury are unclear. Metabolomics could yield in-depth mechanistic insights and explore the potential therapeutic effect of natural products. In this study, the preparation of doxorubicin-induced myocardial injury rat model for evaluation of Schisandrin B on viral myocarditis sequelae related pathological changes and its mechanism. The metabolite profiling of myocardial injury rats was performed through ultra-high performance liquid chromatography combined with mass spectrometry combined with pattern recognition approaches and pathway analysis. A total of 15 metabolites (nine in positive ion mode and six in negative ion mode) were considered as potential biomarkers of myocardial injury, and these metabolites may correlate with the regulation of Schisandrin B treatment. A total of six metabolic pathways are closely related to Schisandrin B treatment, including glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, etc. This study revealed the potential biomarkers and metabolic network pathways of myocardial injury, and illuminated the protective mechanism of Schisandrin B on myocardial injury.

Functional Metabolomics Analysis Elucidating the Metabolic Biomarker and Key Pathway Change Associated With the Chronic Glomerulonephritis and Revealing Action Mechanism of Rhein

Chronic glomerulonephritis (CGN) as the culprit of kidney failure can increase the mortality of critically ill patients and seriously threatens people’s health all over the world. This study using metabolomics strategy is to reveal the potential therapeutic mechanism-related targets to evaluate the effects of rhein (RH) on CGN rats. Changes of serum metabolites and pathways were analyzed by non-targeted metabolomic method based on liquid chromatography-mass spectrometry (LC-MS) combined with ingenuity pathway analysis. In addition, the levels of biochemical indicators were also detected. A total of 25 potential biomarkers were identified to express serum metabolic turbulence in CGN animal model, and then 16 biomarkers were regulated by RH trending to the normal states. From metabolite enrichment and pathway analysis, pharmacological activity of RH on CGN were mainly involved in six vital metabolic pathways including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, tricarboxylic acid cycle (TCA cycle), alanine, aspartate, and glutamate metabolism, arginine and proline metabolism. It suggested CGN treatment with RH, which may be mediated via interference with metabolic pathway such as amino acid metabolism, arachidonic acid metabolism, and TCA cycle to regulating inflammation, oxidation response and immune regulation against CGN. It showed that metabolomics method offer deeply insight into the therapeutic mechanisms of natural product.

High-throughput metabolomic method based on liquid chromatography: high resolution mass spectrometry with chemometrics for metabolic biomarkers and pathway analysis to reveal the protective effects of baicalin on thyroid cancer

Cell metabonomics focuses on discovering metabolic biomarkers and pathway changes in cells from biological systems to obtain the cell properties and functional information under different conditions. Baicalin possesses various pharmacological activities, and plays a vital role in the oncology research field. However, the detailed mechanism of its action is still unclear. In this work, we employed ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) based non-targeted metabolomics method associated with chemometrics analysis to explore metabolic pathways and biomarkers for investigating the efficacy and pharmacological targets of baicalin against thyroid cancer cells. In addition, morphological observation, parameter calculation of cell proliferation and apoptosis were carried out, which assisted in elucidation of pharmacological activity of baicalin on the human thyroid cancer cells. The results showed that baicalin possesses an intense stimulative apoptosis and inhibits proliferation activity on SW579 human thyroid cancer cells, and partially reversed the cell metabolite abnormalities. A total of nineteen differentiated metabolites in SW579 cells were identified and deemed as potential biomarkers after the baicalin treatment, involving nine metabolic pathways, such as taurine and hypotaurine metabolism, pyrimidine metabolism, fructose and mannose metabolism, steroid hormone biosynthesis and sphingolipid metabolism. High-throughput non-targeted metabolomics provide an insight into specialized mechanism of baicalin against thyroid cancer and contributes to novel drug discovery and thyroid cancer management in clinical practice.

Exploring the metabolic biomarkers and pathway changes in crucian under carbonate alkalinity exposure using high-throughput metabolomics analysis based on UPLC-ESI-QTOF-MS

The aims of this study is to explore the metabolomic biomarker and pathway changes in crucian under carbonate alkalinity exposures using high-throughput metabolomics analysis based on ultra-performance liquid chromatography-electrospray ionization-quadrupole time of flight-tandem mass spectrometry (UPLC-ESI-QTOF-MS) for carrying out adaptive evolution of fish in environmental exposures and understanding molecular physiological mechanisms of saline–alkali tolerance in fishes. Under 60 day exposure management, the UPLC-ESI-QTOF-MS technology, coupled with a pattern recognition approach and metabolic pathway analysis, was utilized to give insight into the metabolic biomarker and pathway changes. In addition, biochemical parameters in response to carbonate alkalinity in fish were detected for chronic impairment evaluation. A total of twenty-seven endogenous metabolites were identified to distinguish the biochemical changes in fish in clean water under exposure to different concentrations of carbonate alkalinity (CA); these mainly involved amino acid synthesis and metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, pyruvate metabolism and the citrate cycle (TCA cycle). Compared with the control group, CA exposure increased the level of blood ammonia; TP; ALB; Gln in the liver and gills; GS; urea in blood, the liver and gills; CREA; CPS; Glu and LDH; and decreased the level of weight gain rate, oxygen consumption, discharge rate of ammonia, SOD, CAT, ALT, AST and Na⁺/K⁺-ATPase. At low concentrations, CA can change the normal metabolism of fish in terms of changing the osmotic pressure regulation capacity, antioxidant capacity, ammonia metabolism and liver and kidney function to adapt to the CA exposure environment. As the concentration of CA increases, various metabolic processes in crucian are inhibited, causing chronic damage to the body. The results show that the metabolomic strategy is a potentially powerful tool for identifying the mechanisms in response to different environmental exposomes and offers precious information about the chronic response of fish to CA.

We explore the metabolic biomarker and pathway changes accompanying the adaptive evolution of crucian subjected to carbonate alkalinity exposure, using UPLC-ESI-QTOF-MS, in order to understand the molecular physiological mechanisms of saline–alkali tolerance.

Rapid lipidomics analysis for sepsis-induced liver injury in rats and insights into lipid metabolic pathways using ultra-performance liquid chromatography/mass spectrometry

Lipidomics has been applied in the identification and quantification of molecular lipids within an organism, and to provide insights into mechanisms in clinical medicine. Sepsis is a major systemic inflammatory syndrome and the liver here is a potential target organ for dysfunctional response. However, the study of alterations in global lipid profiles associated with sepsis-induced liver injury is still limited. In this work, we set out to determine alterations of lipidomics profiles in a rat model of sepsis-induced liver injury using an untargeted lipidomics strategy. Liquid chromatography coupled with mass spectrometry in conjunction with multivariate data analysis and pathway analysis were used to acquire a global lipid metabolite profile. Meanwhile, biochemistry index and histopathological examinations of the liver were performed to obtain auxiliary measurements for determining the pathological changes associated with sepsis-induced liver injury. Eleven lipid metabolites and two metabolic pathways were discovered and associated with sepsis-induced liver injury. The results indicated that various biomarkers and pathways may provide evidence for and insight into lipid profile alterations associated with sepsis-induced liver injury, and hence pointed to potential strategic targets for clinical diagnosis and therapy in the future.

Lipidomics has been applied in the identification and quantification of molecular lipids within an organism, and to provide insights into mechanisms in clinical medicine.

Retracted Article: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome

High-throughput metabolomics can be used to investigate the therapeutic targets and metabolic mechanisms of traditional Chinese medicine formulae.

High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction

High-throughput metabolic profiling technology has been used for biomarker discovery and to reveal underlying metabolic mechanisms.

Gingerol suppresses sepsis-induced acute kidney injury by modulating methylsulfonylmethane and dimethylamine production

Acute kidney injury (AKI) and metabolic dysfunction are critical complications in sepsis syndrome; however, their pathophysiological mechanisms remain poorly understood. Therefore, we evaluated whether the pharmacological properties of 6-gingerol (6G) and 10-gingerol (10G) could modulate AKI and metabolic disruption in a rat model of sepsis (faecal peritonitis). Animals from the sham and AKI groups were intraperitoneally injected with 6G or 10G (25 mg/kg). Septic AKI decreased creatinine clearance and renal antioxidant activity, but enhanced oxidative stress and the renal mRNA levels of tumour necrosis factor-α, interleukin-1β, and transforming growth factor-β. Both phenol compounds repaired kidney function through antioxidant activity related to decreased oxidative/nitrosative stress and proinflammatory cytokines. Metabolomics analysis indicated different metabolic profiles for the sham surgery group, caecal ligation and puncture model alone group, and sepsis groups treated with gingerols. ¹H nuclear magnetic resonance analysis detected important increases in urinary creatine, allantoin, and dimethylglycine levels in septic rats. However, dimethylamine and methylsulfonylmethane metabolites were more frequently detected in septic animals treated with 6G or 10G, and were associated with increased survival of septic animals. Gingerols attenuated septic AKI by decreasing renal disturbances, oxidative stress, and inflammatory response through a mechanism possibly correlated with increased production of dimethylamine and methylsulfonylmethane.

Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach

Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute kidney injury (AKI) induced by contrast is a serious complication in patients undergoing administration of iodinated contrast media. It is becoming a major health concern in clinic, however, the molecular mechanisms of contrast-induced acute kidney injury (CI-AKI) have not been well characterized. In this study, we used serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) combined with pattern recognition to explore and characterize potential metabolites and metabolic pathway in an experimental model for CI-AKI. Seventeen differentiating metabolites in the serum were identified involving the pivotal metabolic pathways related to tryptophan metabolism, glycerophospholipid metabolism, steroid hormone biosynthesis, pyrimidine metabolism, sphingolipid metabolism, aminoacyl-tRNA biosynthesis. Our study provides novel insight into pathophysiologic mechanisms of AKI by changing biomarkers and pathways.

Retracted Article: High performance liquid chromatography coupled with high resolution mass spectrometry-based characterization of lipidomic responses from rats with kidney injuries

Metabolism of lipids is essential for the regulation of a variety of key cellular functions. Recent advances in high performance liquid chromatography coupled with high resolution mass spectrometry have expanded our knowledge of lipid metabolism in diseases. Currently, sepsis is one of the most important public health problems all over the world, which is a serious systemic inflammatory syndrome leading to infection by various agents or trauma and subsequently to a multiple organ dysfunction response. However, little is known about the lipids affected by sepsis and their roles in kidney injuries. In this study, we present targeted and non-targeted lipidomics strategies to discover the lipid metabolism variation in serum in rats with sepsis-induced kidney injuries. Liquid chromatography (LC) coupled with mass spectrometry (MS) and multivariate data analysis were used to obtain the global lipid metabolic profiles. In addition, biochemical parameters and histopathological examination results for the kidney were analyzed to support the pathological changes during sepsis-induced kidney injury. The identification of ten proposed lipids and five relevant pathways will promote a better understanding of lipid profile alterations in kidney injury. The results suggested that lipid metabolism in sepsis-induced kidney injury had changed significantly and contribute by offering potential targets for clinical diagnosis and therapy in the future, which would be worth further studies to broaden the applications of high performance liquid chromatography coupled with high resolution mass spectrometry in the study of lipid metabolism.

In this study, we present targeted and non-targeted lipidomics strategies to discover the lipid metabolism variation in serum in rats with sepsis-induced kidney injuries.

High-throughput metabolomics enables metabolite biomarkers and metabolic mechanism discovery of fish in response to alkalinity stress

High throughput mass spectrometry (MS)-based metabolomics is a popular platform for small molecule metabolites analyses that are widely used for detecting biomarkers in the research field of environmental assessment. Crucian carp (Carassius carassius, CC) is an economically and ecologically important fish in Asia. It can adapt to extremely high alkalinity, providing us with valuable material to understand the adaptation mechanism for extreme environmental stress. However, the information on the metabolite biomarkers and metabolic mechanisms of CC exposed to alkaline stress is not entirely clear. We applied high-throughput UPLC-Q-TOF/MS combined with chemometrics to identify changes in the metabolome of CC exposed to different concentrations of alkalinity for long term effects. Metabolic differences among alkalinity-treated groups were identified by multivariate statistical analysis. Further, 7 differential metabolites were found after exposure to alkaline conditions. In total, 23 metabolic pathways of these differential metabolites were significantly affected. Alkalinity exposure resulted in widespread change in metabolic profiles in the plasma with disruptions in the phenylalanine metabolism, glycine, serine and threonine metabolism, pyruvate metabolism, tyrosine metabolism, etc. The integrated pathway analysis of the associated metabolites showed that tRNA charging, l-cysteine degradation II, superpathway of methionine degradation, l-serine degradation, tyrosine biosynthesis IV, etc. appear to be the most significantly represented functional categories. Overall, this study demonstrated that metabolic changes in CC played a role in adaptation to the highly alkaline environmental stress.

High throughput mass spectrometry (MS)-based metabolomics is a popular platform for small molecule metabolites analyses that are widely used for detecting biomarkers in the research field of environmental assessment.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

Metabolomic estimation of the diagnosis of hepatocellular carcinoma based on ultrahigh performance liquid chromatography coupled with time-of-flight mass spectrometry

Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis. Metabolic characteristics of hepatocellular carcinoma (HCC) may enable the discovery of novel biomarkers for its diagnosis. In this work, metabolomics was used to investigate metabolic alterations of HCC patients. Plasma samples from HCC patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry and metabolic differences were analyzed using pattern recognition methods. 23 distinguishable metabolites were identified. The altered metabolic pathways were associated with arginine and proline metabolism, glycine, serine and threonine metabolism, steroid hormone biosynthesis, starch and sucrose metabolism, etc. To demonstrate the utility of plasma biomarkers for the diagnosis of HCC, five metabolites comprising deoxycholic acid 3-glucuronide, 6-hydroxymelatonin glucuronide, 4-methoxycinnamic acid, 11b-hydroxyprogesterone and 4-hydroxyretinoic acid were selected as candidate biomarkers. These metabolites that contributed to the combined model could significantly increase the diagnostic performance of HCC. It has proved to be a powerful tool in the discovery of new biomarkers for disease detection and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests.

Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis.

LC-MS-based plasma metabolomics reveals metabolic variations in ovariectomy-induced osteoporosis in female Wistar rats

Osteoporosis with a reduction in bone mineral density has become one of the most common metabolic bone diseases.

Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer

Prostate cancer (PCa) is the second leading cause of cancer death among men and associated with profound metabolic changes.

Technological advances in current metabolomics and its application in tradition Chinese medicine

During the last few years, many metabolomics technologies have been established in biomedical research for analyzing the changes of metabolite levels.

Exploration of metabolite signatures using high-throughput mass spectrometry coupled with multivariate data analysis

Disease impacts important metabolic pathways and the alteration of metabolites may serve as a potential biomarker for early-stage diagnosis.