Diagnosis of Clostridium difficile infection using an UPLC-MS based metabolomics method

Investigating gut microbiota-blood and urine metabolite correlations in early sepsis-induced acute kidney injury: insights from targeted KEGG analyses

Background

The interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.

Methods

Utilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.

Results

Our study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.

Conclusions

Significant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

Clostridioides difficile Infection in Children: Recent Updates on Epidemiology, Diagnosis, Therapy

Clostridioides (formerly Clostridium) difficile is the most important infectious cause of antibiotic-associated diarrhea worldwide and a leading cause of healthcare-associated infection in the United States. The incidence of C. difficile infection (CDI) in children has increased, with 20 000 cases now reported annually, also posing indirect educational and economic consequences. In contrast to infection in adults, CDI in children is more commonly community-associated, accounting for three-quarters of all cases. A wide spectrum of disease severity ranging from asymptomatic carriage to severe diarrhea can occur, varying by age. Fulminant disease, although rare in children, is associated with high morbidity and even fatality. Diagnosis of CDI can be challenging as currently available tests detect either the presence of organism or disease-causing toxin but cannot distinguish colonization from infection. Since colonization can be high in specific pediatric groups, such as infants and young children, biomarkers to aid in accurate diagnosis are urgently needed. Similar to disease in adults, recurrence of CDI in children is common, affecting 20% to 30% of incident cases. Metronidazole has long been considered the mainstay therapy for CDI in children. However, new evidence supports the safety and efficacy of oral vancomycin and fidaxomicin as additional treatment options, whereas fecal microbiota transplantation is gaining popularity for recurrent infection. Recent advancements in our understanding of emerging epidemiologic trends and management of CDI unique to children are highlighted in this review. Despite encouraging therapeutic advancements, there remains a pressing need to optimize CDI therapy in children, particularly as it pertains to severe and recurrent disease.

Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.

Synergistic effect of co-culture rhizosphere Streptomyces: A promising strategy to enhance antimicrobial activity and plant growth-promoting function

Rhizosphere Streptomyces is one of the important types of rhizosphere microorganisms that plays an important role in promoting plant growth and controlling plant diseases to maintain agricultural ecosystem balance and green ecological agriculture development as beneficial bacteria. Microbial co-culture simulates the complex biocommunity in nature, which has more advantages than the monoculture with a synergistic effect. As the key signal mediums of microorganisms, plants, and their interactions, microbial metabolites are of great significance in revealing their functional mechanism. In this study, two potential plant growth-promoting rhizobacteria, Streptomyces albireticuli MDJK11, and Streptomyces alboflavus MDJK44, were selected to explore the effects of co-culture and monoculture on plant growth promotion and disease prevention, and the metabolic material basis was analyzed by metabonomics. Results showed that Streptomyces MDJK11, MDJK44 monoculture, and co-culture condition all showed good growth promoting and antimicrobial effects. Moreover, as compared to the monoculture, the co-culture showed the advantage of a synergistic enhancement effect. LC-MS-based metabonomics analysis showed the metabolic material bases of Streptomyces for plant growth promotion and disease prevention were mainly plant hormone and antibiotics and the co-culture condition could significantly stimulate the production of plant hormone promoters and macrolide, cyclic peptide, and aminoglycoside antibiotics. The study proved that the co-cultures of S. albireticuli MDJK11 and S. alboflavus MDJK44 have great potential in crop growth promotion and disease prevention.

Pyocyanin Modulates Gastrointestinal Transformation and Microbiota

Phenazines are ubiquitously produced by Pseudomonas spp. in the environment and are widely used in agriculture and clinical therapies, making their accumulation through the food chain cause potential risks to human health. Here, we utilized pyocyanin (PYO) as a representative to study the effects of phenazines on digestive tracts. Pharmacokinetic analysis showed that PYO exhibited low systemic exposure, slow elimination, and low accumulation in both rat and pig models. PYO was subsequently found to induce intestinal microbiota dysbiosis, destroy the mucus layer and physical barrier, and even promote gut vascular barrier (GVB) impairment, consequently increasing the gut permeability. Additionally, integral and metabolomic analyses of the liver demonstrated that PYO induced liver inflammation and metabolic disorders. The metabolic analysis further confirmed that all of the metabolites of PYO retain the nitrogen-containing tricyclic structural skeleton of phenazines, which was the core bioactivity of phenazine compounds. These findings elucidated that PYO could be metabolized by animals. Meanwhile, high levels of PYO could induce intestinal barrier impairment and liver damage, suggesting that we should be alert to the accumulation of phenazines.

Pediatric Clostridioides difficile Infection: Diagnosis and Diagnostic Stewardship

Although the pathogenesis of Clostridioides difficile infection (CDI) is complex and incompletely understood, it is believed that the elaboration of C. difficile toxins is necessary for disease. There are a variety of tests available for the detection of both the C. difficile organism and its toxins; however, each has limitations and the best application of these tests to the diagnosis of CDI in children remains uncertain. Nucleic acid amplification tests are unable to reliably discriminate between CDI and C. difficile colonization, while commercially available enzyme immunoassays for toxin detection lack sensitivity. An understanding of preanalytic factors, relevant patient features, and test performance characteristics is essential to the accurate diagnosis of CDI in children. Specific diagnostic stewardship strategies can also increase the likelihood that positive tests reflect disease rather than colonization. Ultimately, CDI remains a clinical diagnosis and clinical judgment is essential when interpreting test results, regardless of the methods used.

Foodborne pathogens in the omics era

Outbreaks and deaths related to Foodborne Diseases (FBD) occur constantly in the world, as a result of the consumption of contaminated foodstuffs with pathogens such as Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Salmonella spp, Clostridium spp. and Campylobacter spp. The purpose of this review is to discuss the main omic techniques applied in foodborne pathogen and to demonstrate their functionalities through the food chain and to guarantee the food safety. The main techniques presented are genomic, transcriptomic, secretomic, proteomic, and metabolomic, which together, in the field of food and nutrition, are known as "Foodomics." This review had highlighted the potential of omics to integrate variables that contribute to food safety and to enable us to understand their application on foodborne diseases. The appropriate use of these techniques had driven the definition of critical parameters to achieve successful results in the improvement of consumers health, costs and to obtain safe and high-quality products.

Advances and required improvements in methods to diagnosing Clostridioides difficile infections in the healthcare setting

INTRODUCTION

Clostrididioides difficile is associated with adverse clinical outcomes and increased morbidity, mortality, length of hospital stay, and health-care costs.Areas Covered: We searched relevant papers in PubMed for the last 10 years. In major papers, we scanned the bibliographies to ensure that important articles were included. This review addresses the evolving epidemiology of Clostridioides difficile infection (CDI) and discusses novel methods/approaches for improving the diagnosis of this important disease.

EXPERT OPINION

No single diagnostic test to date has demonstrated optimum sensitivity and specificity for detection of CDI. Many institutions have developed multi-step algorithms consistent with guidelines established by various professional societies. Some institutions have successfully tried to improve the pretest probability of molecular assays by implementing appropriate sample rejection criteria and establishing best practice alerts at the time of electronic order entry. Others have established PCR cycle threshold cutoffs to attempt to differentiate symptomatic patients from asymptomatic carriers or to make predictions about severity of disease with variable success. As research advances our understanding of C. difficile pathogenesis and pathophysiology, more information on CDI specific biomarkers is emerging. Finally, assessments of the microbiome and metabolome may expand the diagnostic armamentarium with advances in mass spectrometry and sequencing technologies.

Metabolomic approaches for the determination of metabolites from pathogenic microorganisms: A review

Metabolomics is a high precision analytical approach to obtaining detailed information of varieties of metabolites produced in biological systems, including foods. This study reviews the use of metabolomic approaches such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GC-MS), matrix assisted laser desorption /ionization tandem time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance (NMR) for investigating the presence of foodborne pathogens and their metabolites. Pathogenic fungi and their notable metabolites (mycotoxins) have been studied more extensively using metabolomics as compared to bacteria, necessitating further studies in this regard. Nevertheless, such identified fungal and bacteria metabolites could be used as biomarkers for a more rapid detection of these pathogens in food. Other important compounds detected through metabolomics could also be correlated to functionality of these pathogenic strains, determined by the composition of the foods in which they exist, thereby providing insights into their metabolism. Considering the prevalence of these food pathogens, metabolomics still has potentials in the determination of food-borne pathogenic microorganisms especially for the determination of pathogenic bacteria toxins and is expected to generate research interests for further studies and applications.

Metabolomics in infectious diseases and drug discovery

Metabolomics has emerged as an invaluable tool that can be used along with genomics, transcriptomics and proteomics to understand host–pathogen interactions at small-molecule levels. Metabolomics has been used to study a variety of infectious diseases and applications. The most common application of metabolomics is for prognostic and diagnostic purposes, specifically the screening of disease-specific biomarkers by either NMR-based or mass spectrometry-based metabolomics. In addition, metabolomics is of great significance for the discovery of druggable metabolic enzymes and/or metabolic regulators through the use of state-of-the-art flux analysis, for example, via the elucidation of metabolic mechanisms. This review discusses the application of metabolomics technologies to biomarker screening, the discovery of drug targets in infectious diseases such as viral, bacterial and parasite infections and immunometabolomics, highlights the challenges associated with accessing metabolite compartmentalization and discusses the available tools for determining local metabolite concentrations.

Metabolomics has emerged as an invaluable tool that can be used along with genomics, transcriptomics and proteomics to understand host–pathogen interactions at small-molecule levels.

Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections

Approaches to the identification of metabolites have progressed from early biochemical pathway evaluation to modern high-dimensional metabolomics, a powerful tool to identify and characterize biomarkers of health and disease. In addition to its relevance to classic metabolic diseases, metabolomics has been key to the emergence of immunometabolism, an important area of study, as leukocytes generate and are impacted by key metabolites important to innate and adaptive immunity. Herein, we discuss the metabolomic signatures and pathways perturbed by the activation of the human immune system during infection and vaccination. For example, infection induces changes in lipid (e.g., free fatty acids, sphingolipids, and lysophosphatidylcholines) and amino acid pathways (e.g., tryptophan, serine, and threonine), while vaccination can trigger changes in carbohydrate and bile acid pathways. Amino acid, carbohydrate, lipid, and nucleotide metabolism is relevant to immunity and is perturbed by both infections and vaccinations. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying the host immune response. Its integration with other systems biology platforms will enhance studies of human health and disease.

The related mechanism of complete Freund's adjuvant-induced chronic inflammation pain based on metabolomics analysis

Chronic inflammation pain is a debilitating disease, and its mechanism still remains poorly understood. This study attempted to illuminate the metabolic mechanism of chronic inflammation pain induced by complete Freund’s adjuvant (CFA) injection, especially at spinal level. The chronic inflammation pain model was established by CFA administration. Behavioral testing including mechanical allodynia and thermal hyperalgesia was performed. Meanwhile, a liquid chromatography–mass spectrometry‐based metabolomics approach was applied to analyze potential metabolic biomarkers. The orthogonal partial least squares discrimination analysis mode was employed for determining metabolic changes, and a western blot was performed to detect the protein expression change. The results showed that 27 metabolites showed obviously abnormal expression and seven metabolic pathways were significantly enriched, comprising aminoacyl‐tRNA biosynthesis, arginine and proline metabolism, histidine metabolism, purine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, glutathione metabolism, and phenylalanine metabolism. Meanwhile, the results showed that the expression of arginase I and nitric oxide levels were elevated in the CFA group compared with the control group, while the argininosuccinate synthetase and argininosuccinatelyase proteins were not significantly different between the groups. These findings demonstrate that metabolic changes of the spinal cord may be implicated in neurotransmitter release and pain conductivity following CFA administration.

Establishment of a pattern recognition metabolomics model for the diagnosis of hepatocellular carcinoma

BACKGROUND

Early diagnosis of hepatocellular carcinoma may help to ensure that patients have a chance for long-term survival; however, currently available biomarkers lack sensitivity and specificity.

AIM

To characterize the serum metabolome of hepatocellular carcinoma in order to develop a new metabolomics diagnostic model and identifying novel biomarkers for screening hepatocellular carcinoma based on the pattern recognition method.

METHODS

Ultra-performance liquid chromatography-mass spectroscopy was used to characterize the serum metabolome of hepatocellular carcinoma (n = 30) and cirrhosis (n = 29) patients, followed by sequential feature selection combined with linear discriminant analysis to process the multivariate data.

RESULTS

The concentrations of most metabolites, including proline, were lower in patients with hepatocellular carcinoma, whereas the hydroxypurine levels were higher in these patients. As ordinary analysis models failed to discriminate hepatocellular carcinoma from cirrhosis, pattern recognition analysis was used to establish a pattern recognition model that included hydroxypurine and proline. The leave-one-out cross-validation accuracy and area under the receiver operating characteristic curve analysis were 95.00% and 0.90 [95% Confidence Interval (CI): 0.81-0.99] for the training set, respectively, and 78.95% and 0.84 (95%CI: 0.67-1.00) for the validation set, respectively. In contrast, for α-fetoprotein, the accuracy and area under the receiver operating characteristic curve were 65.00% and 0.69 (95%CI: 0.52-0.86) for the training set, respectively, and 68.42% and 0.68 (95%CI: 0.41-0.94) for the validation set, respectively. The Z test revealed that the area under the curve of the linear discriminant analysis model was significantly higher than the area under the curve of α-fetoprotein (P < 0.05) in both the training and validation sets.

CONCLUSION

Hydroxypurine and proline might be novel biomarkers for hepatocellular carcinoma, and this disease could be diagnosed by the metabolomics model based on pattern recognition.

Metabolomics biotechnology, applications, and future trends: a systematic review

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed. Mass spectrometry-based metabolomics has been used in a variety of disease research areas. However, the deep research of metabolites remains a difficult and lengthy process. Fortunately, mass spectrometry is considered to be a universal tool with high specificity and sensitivity and is widely used around the world. Mass spectrometry technology has been applied to various basic disciplines, providing technical support for the discovery and identification of endogenous substances in living organisms. The combination of metabolomics and mass spectrometry is of great significance for the discovery and identification of metabolite biomarkers. The mass spectrometry tool could further improve and develop the exploratory research of the life sciences. This mini review discusses metabolomics biotechnology with a focus on recent applications of metabolomics as a powerful tool to elucidate metabolic disturbances and the related mechanisms of diseases.

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed.