Metabolomic Profiling of Infectious Parapneumonic Effusions Reveals Biomarkers for Guiding Management of Children with Streptococcus pneumoniae Pneumonia

Metabolomic Analysis Reveals the Association of Severe Bronchopulmonary Dysplasia with Gut Microbiota and Oxidative Response in Extremely Preterm Infants

Bronchopulmonary dysplasia (BPD) is a chronic lung disease mainly affecting premature infants needing ventilation or oxygen for respiratory distress. This study aimed to evaluate the molecular linkages for BPD in very and extremely preterm infants using a metabolomics-based approach. A case-control study of enrolling preterm infants born before 32 weeks gestational age (GA) was prospectively performed. These preterm infants were subsequently stratified into the following two groups for further analysis: no or mild BPD, and moderate or severe BPD based on the 2019 NICHD criteria. Urinary metabolomic profiling was performed using 1H-Nuclear magnetic resonance (NMR) spectroscopy coupled with partial least squares discriminant analysis (PLS-DA) at a corrected age of 6 months. Metabolites significantly differentially related to GA and BPD severity were performed between groups, and their roles in functional metabolic pathways were also assessed. A total of 89 preterm infants born before 32 weeks gestation and 50 infants born at term age (above 37 completed weeks' gestation) served as controls and were enrolled into the study. There were 21 and 24 urinary metabolites identified to be significantly associated with GA and BPD severity, respectively (p < 0.05). Among them, N-phenylacetylglycine, hippurate, acetylsalicylate, gluconate, and indoxyl sulfate were five metabolites that were significantly higher, with the highest importance in both infants with GA < 28 weeks and those with moderate to severe BPD, whereas betaine and N,N-dimethylglycine were significantly lower (p < 0.05). Furthermore, ribose and a gluconate related pentose phosphate pathway were strongly associated with these infants (p < 0.01). In conclusion, urinary metabolomic analysis highlights the crucial role of gut microbiota dysbiosis in the pathogenesis of BPD in preterm infants, accompanied by metabolites related to diminished antioxidative capacity, prompting an aggressive antioxidation response in extremely preterm infants with severe BPD.

Common pathogenic bacteria-induced reprogramming of the host proteinogenic amino acids metabolism

Apart from cancer, metabolic reprogramming is also prevalent in other diseases, such as bacterial infections. Bacterial infections can affect a variety of cells, tissues, organs, and bodies, leading to a series of clinical diseases. Common Pathogenic bacteria include Helicobacter pylori, Salmonella enterica, Mycobacterium tuberculosis, Staphylococcus aureus, and so on. Amino acids are important and essential nutrients in bacterial physiology and support not only their proliferation but also their evasion of host immune defenses. Many pathogenic bacteria or opportunistic pathogens infect the host and lead to significant changes in metabolites, especially the proteinogenic amino acids, to inhibit the host's immune mechanism to achieve its immune evasion and pathogenicity. Here, we review the regulation of host metabolism, while host cells are infected by some common pathogenic bacteria, and discuss how amino acids of metabolic reprogramming affect bacterial infections, revealing the potential adjunctive application of amino acids alongside antibiotics.

Metabolomics Analysis Reveals Molecular Signatures of Metabolic Complexity in Children with Hypercholesterolemia

Despite the importance of hypercholesterolemia in children, it is overlooked, and there are currently few metabolomics-based approaches available to understand its molecular mechanisms. Children from a birth cohort had their cholesterol levels measured with the aim of identifying the metabolites for the molecular biological pathways of childhood hypercholesterolemia. One hundred and twenty-five children were enrolled and stratified into three groups according to cholesterol levels (acceptable, <170 mg/dL, n = 42; borderline, 170–200 mg/dL, n = 52; and high, >200 mg/dL, n = 31). Plasma metabolomic profiles were obtained by using 1H-nuclear magnetic resonance (NMR) spectroscopy, and partial least squares-discriminant analysis (PLS-DA) was applied using the MetaboAnalyst 5.0 platform. Metabolites significantly associated with different cholesterol statuses were identified, and random forest classifier models were used to rank the importance of these metabolites. Their associations with serum lipid profile and functional metabolic pathways related to hypercholesterolemia were also assessed. Cholesterol level was significantly positively correlated with LDL-C and Apo-B level, as well as HDL-C and Apo-A1 level separately, whereas HDL-C was negatively correlated with triglyceride level (p < 0.01). Eight metabolites including tyrosine, glutamic acid, ornithine, lysine, alanine, creatinine, oxoglutaric acid, and creatine were significantly associated with the different statuses of cholesterol level. Among them, glutamic acid and tyrosine had the highest importance for different cholesterol statuses using random forest regression models. Carbohydrate and amino acid metabolisms were significantly associated with different cholesterol statuses, with glutamic acid being involved in all amino acid metabolic pathways (FDR-adjusted p < 0.01). Hypercholesterolemia is a significant health concern among children, with up to 25% having high cholesterol levels. Glutamic acid and tyrosine are crucial amino acids in lipid metabolism, with glutamic-acid-related amino acid metabolism playing a significant role in regulating cholesterol levels.

Metabolomics in pediatric lower respiratory tract infections and sepsis: a literature review

Lower respiratory tract infections (LRTIs) are a leading cause of morbidity and mortality in children. The ability of healthcare providers to diagnose and prognose LRTIs in the pediatric population remains a challenge, as children can present with similar clinical features regardless of the underlying pathogen or ultimate severity. Metabolomics, the large-scale analysis of metabolites and metabolic pathways offers new tools and insights that may aid in diagnosing and predicting the outcomes of LRTIs in children. This review highlights the latest literature on the clinical utility of metabolomics in providing care for children with bronchiolitis, pneumonia, COVID-19, and sepsis. IMPACT: This article summarizes current metabolomics approaches to diagnosing and predicting the course of pediatric lower respiratory infections. This article highlights the limitations to current metabolomics research and highlights future directions for the field.

Biomarkers identification in follicular fluid of women with OHSS by using UPLC-MS method

To figure out the differentially changed metabolites and disturbed pathways in follicular fluid (FF) of patients with OHSS in comparison to the control group undergoing in vitro fertilization (IVF), we conducted this metabolomic analysis between two groups, the OHSS group included 30 patients treated with oocyte retrieval and developed OHSS in the next 7-14 days, while another 30 patients without OHSS tendency were selected as the control group. The FF samples were obtained during the process of oocyte retrieval. FF samples were analyzed using ultra-high liquid chromatography-tandem mass spectrometry (UPLC-MS). The results identified a total of 59 differentially changed metabolites, including 33 decreased metabolites (P < 0.01) and 26 increased metabolites (P < 0.01) in FF of OHSS compared with the control group. 12 metabolites could be the most valuable biomarkers for OHSS based on ROC results. Our correlation analyses showed that deoxyinosine levels were found positively correlated with serum estradiol (E2) levels in OHSS patients, while L-isoleucine, pyruvic acid, maleamate, and arachidonic acid were found to be positively correlated with the number of retrieved oocytes. Furthermore, 4-hydroxyphenylacetaldehyde, deoxycorticosterone, creatinine, and creatine were found to be negatively associated with serum E2 levels, while 4-hydroxyphenylacetaldehyde, L-carnitine, isovaleric acid and L-2-hydroxyglutaric acid were negatively related with the number of oocytes retrieved in OHSS patients. Taken together, our study provides better identification of OHSS FF metabolic dynamics, suggesting the metabolic compounds can be used as valuable predictors or treatment targets of OHSS.

Microbiome systems biology advancements for natural well-being

Throughout the years all data from epidemiological, physiological and omics have suggested that the microbial communities play a considerable role in modulating human health. The population of microorganisms residing in the human intestine collectively known as microbiota presents a genetic repertoire that is higher in magnitude than the human genome. They play an essential role in host immunity and neuronal signaling. Rapid enhancement of sequence based screening and development of humanized gnotobiotic model has sparked a great deal of interest among scientists to probe the dynamic interactions of the commensal bacteria. This review focuses on systemic analysis of the gut microbiome to decipher the complexity of the host-microbe intercommunication and gives a special emphasis on the evolution of targeted precision medicine through microbiome engineering. In addition, we have also provided a comprehensive description of how interconnection between metabolism and biochemical reactions in a specific organism can be obtained from a metabolic network or a flux balance analysis and combining multiple datasets helps in the identification of a particular metabolite. The review highlights how genetic modification of the critical components and programming the resident microflora can be employed for targeted precision medicine. Inspite of the ongoing debate on the utility of gut microbiome we have explored on the probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also recapitulates integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet-microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of the disease. Inspite of the ongoing debate on the utility of the gut microbiome we have explored how probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also summarises integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet- microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from the microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of disease.

Metabolomics profile in acute respiratory distress syndrome by nuclear magnetic resonance spectroscopy in patients with community-acquired pneumonia

Background

Acute respiratory distress syndrome (ARDS) is a challenging clinical problem. Discovering the potential metabolic alterations underlying the ARDS is important to identify novel therapeutic target and improve the prognosis. Serum and urine metabolites can reflect systemic and local changes and could help understanding metabolic characterization of community-acquired pneumonia (CAP) with ARDS.

Methods

Clinical data of patients with suspected CAP at the First Affiliated Hospital of Wenzhou Medical University were collected from May 2020 to February 2021. Consecutive patients with CAP were enrolled and divided into two groups: CAP with and without ARDS groups. ¹H nuclear magnetic resonance-based metabolomics analyses of serum and urine samples were performed before and after treatment in CAP with ARDS (n = 43) and CAP without ARDS (n = 45) groups. Differences metabolites were identifed in CAP with ARDS. Furthermore, the receiver operating characteristic (ROC) curve was utilized to identify panels of significant metabolites for evaluating therapeutic effects on CAP with ARDS. The correlation heatmap was analyzed to further display the relationship between metabolites and clinical characteristics.

Results

A total of 20 and 42 metabolites were identified in the serum and urine samples, respectively. Serum metabolic changes were mainly involved in energy, lipid, and amino acid metabolisms, while urine metabolic changes were mainly involved in energy metabolism. Elevated levels of serum 3-hydroxybutyrate, lactate, acetone, acetoacetate, and decreased levels of serum leucine, choline, and urine creatine and creatinine were detected in CAP with ARDS relative to CAP without ARDS. Serum metabolites 3-hydroxybutyrate, acetone, acetoacetate, citrate, choline and urine metabolite 1-methylnicotinamide were identified as a potential biomarkers for assessing therapeutic effects on CAP with ARDS, and with AUCs of 0.866 and 0.795, respectively. Moreover, the ROC curve analysis revealed that combined characteristic serum and urine metabolites exhibited a better classification system for assessing therapeutic effects on CAP with ARDS, with a AUC value of 0.952. In addition, differential metabolites strongly correlated with clinical parameters in patients with CAP with ARDS.

Conclusions

Serum- and urine-based metabolomics analyses identified characteristic metabolic alterations in CAP with ARDS and might provide promising circulatory markers for evaluating therapeutic effects on CAP with ARDS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02075-w.

Metabolomics analysis reveals molecular linkages for the impact of vitamin D on childhood allergic airway diseases

BACKGROUND

Several studies have reported the relevance between serum vitamin D and allergic immunoglobulin E (IgE) responses and atopic diseases. However, a metabolomics-based approach to the impacts of vitamin D on allergic reactions remains unclear.

METHODS

A total of 111 children completed a 3-year follow-up were enrolled and classified based on longitudinal vitamin D status (≥ 30 ng/ml, n = 54; 20-29.9 ng/ml, n = 41; <20 ng/ml, n = 16). Urinary metabolomic profiling was performed using ¹ H-Nuclear magnetic resonance (NMR) spectroscopy at age 3. Integrative analyses of their associations related to vitamin D levels, atopic indices, and allergies were performed, and their roles in functional metabolic pathways were also assessed.

RESULTS

Six and five metabolites were identified to be significantly associated with vitamin D status and atopic diseases, respectively (FDR-adjusted p-value <.05). A further correlation analysis revealed that vitamin D-associated 3-hydroxyisobutyric acid and glutamine were positively correlated with atopic disease-associated succinic acid and alanine, respectively. Furthermore, hippuric acid was negatively correlated with atopic disease-associated formic acid, which was positively correlated with vitamin D level (p < .01). Absolute eosinophil count (AEC) was positively correlated with serum D. pteronyssinus- and D. farinae-specific IgE level (p < .01) but negatively correlated with vitamin D level (p < .05). Amino acid metabolisms were significantly associated with vitamin D related to childhood allergies.

CONCLUSION

Integrative metabolomic analysis provides the link of vitamin D-associated metabolites with the gut microbiome and immunoallergic reactions related to childhood allergies.

Metabolic preference assay for rapid diagnosis of bloodstream infections

Bloodstream infections (BSIs) cause >500,000 infections and >80,000 deaths per year in North America. The length of time between the onset of symptoms and administration of appropriate antimicrobials is directly linked to mortality rates. It currently takes 2–5 days to identify BSI pathogens and measure their susceptibility to antimicrobials – a timeline that directly contributes to preventable deaths. To address this, we demonstrate a rapid metabolic preference assay (MPA) that uses the pattern of metabolic fluxes observed in ex-vivo microbial cultures to identify common pathogens and determine their antimicrobial susceptibility profiles. In a head-to-head race with a leading platform (VITEK 2, BioMérieux) used in diagnostic laboratories, MPA decreases testing timelines from 40 hours to under 20. If put into practice, this assay could reduce septic shock mortality and reduce the use of broad spectrum antibiotics.

It is currently slow to identify bloodstream infection pathogens. Here the authors report a rapid metabolic preference assay that uses the pattern of metabolic fluxes observed in ex-vivo microbial cultures to identify common pathogens and determine their antimicrobial susceptibility profiles.

Integrated metabolic and microbial analysis reveals host-microbial interactions in IgE-mediated childhood asthma

A metabolomics-based approach to address the molecular mechanism of childhood asthma with immunoglobulin E (IgE) or allergen sensitization related to microbiome in the airways remains lacking. Fifty-three children with lowly sensitized non-atopic asthma (n = 15), highly sensitized atopic asthma (n = 13), and healthy controls (n = 25) were enrolled. Blood metabolomic analysis with ¹H-nuclear magnetic resonance (NMR) spectroscopy and airway microbiome composition analysis by bacterial 16S rRNA sequencing were performed. An integrative analysis of their associations with allergen-specific IgE levels for lowly and highly sensitized asthma was also assessed. Four metabolites including tyrosine, isovalerate, glycine, and histidine were uniquely associated with lowly sensitized asthma, whereas one metabolite, acetic acid, was strongly associated with highly sensitized asthma. Metabolites associated with highly sensitized asthma (valine, isobutyric acid, and acetic acid) and lowly sensitized asthma (isovalerate, tyrosine, and histidine) were strongly correlated each other (P < 0.01). Highly sensitized asthma associated metabolites were mainly enriched in pyruvate and acetyl-CoA metabolisms. Metabolites associated with highly sensitized atopic asthma were mostly correlated with microbiota in the airways. Acetic acid, a short-chain fatty acid (SCFA), was negatively correlated with the genus Atopobium (P < 0.01), but positively correlated with the genus Fusobacterium (P < 0.05). In conclusion, metabolomics reveals microbes-related metabolic pathways associated with IgE responses to house dust mite allergens in childhood asthma. A strong correlation of metabolites related to highly sensitized atopic asthma with airway microbiota provides linkages between the host-microbial interactions and asthma endotypes.

Metabolomics reveals microbial-derived metabolites associated with immunoglobulin E responses in filaggrin-related atopic dermatitis

BACKGROUND

Filaggrin (FLG) gene mutation and immunoglobulin E (IgE)-mediated sensitization are the most important predictors of atopic dermatitis (AD). However, a metabolomics-based approach to address the metabolic impact of FLG mutations on allergic IgE responses for AD is still lacking. We, though, determine the relationships of metabolic profiles in AD with FLG mutations and allergic responses.

METHODS

Eighty-one children with adolescent AD (n = 58) and healthy controls (n = 23) were prospectively enrolled. Mutations in the filaggrin gene were identified using whole-exome sequencing, and plasma metabolic profiles were determined using ¹ H-nuclear magnetic resonance (NMR) spectroscopy. Integrative analyses of their associations related to total serum IgE levels were performed, and further metabolic functional pathways for AD were also assessed.

RESULTS

Metabolites contributed to the separation between AD and controls were identified using the supervised partial least squares discriminant analysis (Q² /R²  = 0.90, P_permutation <0.001). Nitrogen and amino acid metabolisms for energy production, and microbe-related methane and propanoate metabolisms were significantly associated with AD compared with healthy controls (FDR-adjusted p < .05). Five of fifteen metabolites related to FLG mutations were positively correlated with total serum IgE levels. Among them, dimethylamine and isopropanol were strongly associated with methane metabolism and propanoate metabolism, respectively, in AD with FLG mutations (FDR-adjusted p < .01).

CONCLUSION

A strong correlation of microbial-derived metabolites, dimethylamine and isopropanol, with FLG mutations and IgE allergic reactions provides the influence of host genetics on the microbiome to regulate susceptibility to allergic responses in the pathogenesis of AD.

Urine metabolic phenotyping in children with nocturnal enuresis and comorbid neurobehavioral disorders

Nocturnal enuresis (NE) is a common problem among 10% school-aged children. The etiologies underlying childhood NE is complex and not fully understood nowadays. Nevertheless, increasing evidence suggests a potential link between neurobehavioral disorders and enuresis in children. In this study, we aimed to explore novel metabolomic insights into the pathophysiology of NE and also, its association with pediatric psychiatric problems. Urine collected from 41 bedwetting children and 27 healthy control children was analyzed by using ¹H-nuclear magnetic resonance spectroscopy from August 2017 to December 2018. At regular follow-up, there were 14 children with refractory NE having a diagnosis of attention deficient hyperactivity disorder (ADHD) or anxiety. Eventually, we identified eight significantly differential urinary metabolites and particularly increased urinary excretion of betaine, creatine and guanidinoacetate linked to glycine, serine and threonine metabolism were associated with a comorbidity of neurobehavioral disorders in refractory bedwetting children. Notably, based on physiological functions of betaine acting as a renal osmolyte and methyl group donor, we speculated its potential role in modulation of renal and/or central circadian clock systems, becoming a useful urinary metabolic marker in diagnosis of treatment-resistant NE in children affected by these two disorders.

A study of the proteomic expression in patients with complicated parapneumonic pleural effusion

Introduction

The present study aimed to investigate the differences in the proteomic expression between uncomplicated parapneumonic pleural effusion (UPPE) and complicated parapneumonic pleural effusion (CPPE).

Material and methods

There were 10 patients with UPPE and 10 patients with CPPE. These patients were combined due to the complication of pleural effusion and further divided into group A and group B. An LC-MS analysis was conducted with the extraction of high-abundance proteins, and proteins with 1.5-fold or higher difference multiples were identified as differential proteins. Then, gene ontology (GO) and KEGG analyses were conducted on the differential proteins between the groups.

Results

Compared with the UPPE group, there were 38 upregulated proteins and 29 downregulated proteins in the CPPE group. The GO analysis revealed that the CPPE group had enhanced expressions in monosaccharide biosynthesis, glucose catabolism, fructose-6-phosphate glycolysis, glucose-6-phosphate glycolysis, and NADH regeneration as well as reduced expressions in fibrinogen complexes, protein polymerization, and coagulation. Moreover, the KEGG analysis showed that the CPPE group had enhanced expressions in amino acid synthesis, the HIF-1 signalling pathway, and glycolysis/glycoisogenesis and decreased expressions in platelet activation and complement activation.

Conclusions

In pleural effusion in patients with CPPE, there are enhanced expressions of proteins concerning glucose and amino acid metabolism, NADH regeneration, and HIF-1 signalling pathways together with decreased expressions of proteins concerning protein polymerization, blood coagulation, platelet activation, and complement activation.

Altered exosomal microRNA profiles in bronchoalveolar lavage fluid can mediate metabolism in patients with Acinetobacter baumannii ventilator-associated pneumonia

Background

Ventilator-associated pneumonia (VAP) is a major public health problem and is most commonly caused by Acinetobacter baumannii (Ab) infection. In our study, we investigated the profiles of exosomal microRNAs (miRNAs) extracted from the bronchoalveolar lavage fluid (BALF) and serum of patients with Acinetobacter baumannii ventilator-associated pneumonia (Ab-VAP). We also examined the serum metabolomic profiles of these patients. Our aim was to study the associations between lung tissue-derived exosomal miRNAs and changes in global metabolism in patients with Ab-VAP.

Methods

Consecutively sampled patients admitted to an intensive care unit (ICU) for pulmonary infection treatment were enrolled in this study. Demographic information and biochemical measurements were collected. Serum samples were obtained following overnight fasting on admission. Bronchoscopies were performed and BALF samples were collected from each patient. Exosomes were extracted using kits from System Biosciences (SBI) and miRNA sequencing was performed. Non-targeted metabolomics were used to express metabolic profiles.

Results

We found significant changes in the miRNA profiles of patients with Ab-VAP; these changes occurred in both BALF exosomal miRNA and serum exosomal miRNA. Gene Ontology analysis further identified the function of miRNA in system metabolism. Serum metabolomic profiles and ratios of biological significance were found to be differentially regulated in Ab-VAP patients. This differential regulation was correlated with the differential expression of miRNAs.

Conclusions

Our data summarizes the dysregulation of serum metabolism and exosomal miRNA excretion that occurs in Ab-VAP patients. The correlation found between BALF exosomal miRNA and dysregulated metabolism, as indicated by the irregular expression of metabolites in the cellular metabolic pathway, highlights potential biomarkers for the diagnosis and treatment of Ab infection.

Metabolomic profiling of parapneumonic effusion reveals a regulatory role of dipeptides in interleukin-8 production in neutrophil-like cells

Bacterial pneumonia is a lethal condition, and approximately 40% of bacterial pneumonia patients experience parapneumonic effusion (PPE). Based on the severity of inflammation, PPEs can be categorized as early-stage uncomplicated PPE (UPPE), advanced-stage complicated PPE (CPPE) and, most seriously, thoracic empyema. Appropriate antibiotic treatment at the early stage of PPE can prevent PPE progression and reduce mortality, indicating that understanding PPE generation and components can help researchers develop corresponding treatment strategies for PPE. To this end, metabolomes of 73 PPE (38 UPPE and 35 CPPE samples) and 30 malignant pleural effusion (MPE) samples were profiled with differential ¹²C₂-/¹³C₂-isotope dansylation labeling-based mass spectrometry. We found that PPE is characterized by elevated levels of dipeptides, especially for PPEs at advanced stages. Furthermore, with integrated proteomic and transcriptomic analyses of PPEs, the levels of dipeptides were strongly associated with the production of interleukin-8 (IL-8), an inflammation-associated cytokine. The production of IL-8 indeed increased upon the treatment of HL-60-derived neutrophilic cells with dipeptides, Gly-Val and Gly-Tyr. Our findings help to elucidate the metabolic perturbations present in PPE and indicate for the first time that dipeptides may be involved in the immune regulation observed during PPE progression.

Discovery and predictive modeling of urine microbiome, metabolite and cytokine biomarkers in hospitalized patients with community acquired pneumonia

Pneumonia is the leading cause of infectious related death costing 12 billion dollars annually in the United States alone. Despite improvements in clinical care, total mortality remains around 4%, with inpatient mortality reaching 5–10%. For unknown reasons, mortality risk remains high even after hospital discharge and there is a need to identify those patients most at risk. Also of importance, clinical symptoms alone do not distinguish viral from bacterial infection which may delay appropriate treatment and may contribute to short-term and long-term mortality. Biomarkers have the potential to provide point of care diagnosis, identify high-risk patients, and increase our understanding of the biology of disease. However, there have been mixed results on the diagnostic performance of many of the analytes tested to date. Urine represents a largely untapped source for biomarker discovery and is highly accessible. To test this hypothesis, we collected urine from hospitalized patients with community-acquired pneumonia (CAP) and performed a comprehensive screen for urinary tract microbiota signatures, metabolite, and cytokine profiles. CAP patients were diagnosed with influenza or bacterial (Streptococcus pneumoniae and Staphylococcus aureus) etiologies and compared with healthy volunteers. Microbiome signatures showed marked shifts in taxonomic levels in patients with bacterial etiology versus influenza and CAP versus normal. Predictive modeling of 291 microbial and metabolite values achieved a + 90% accuracy with LASSO in predicting specific pneumonia etiology. This study demonstrates that urine from patients hospitalized with pneumonia may serve as a reliable and accessible sample to evaluate biomarkers that may diagnose etiology and predict clinical outcomes.

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections

Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection. We adopted machine learning methods for training different classifiers with a clinical-metabolomic database from sepsis cases to identify the pathogen of sepsis. Records of clinical indicators and concentration of metabolites were obtained for each patient upon their arrival at the hospital. Machine learning algorithms were used in 100 patients with clear infection and corresponding 29 controls to select specific biosignatures to discriminate microorganism in septic patients. The sensitivity, specificity, and AUC value of clinical and metabolomic characteristics in predicting diagnostic outcomes were determined at admission. Our analyses demonstrate that the biosignatures selected by machine learning algorithms could have diagnostic value on the identification of infected patients and Gram-positive from Gram-negative; related AUC values were 0.94 ± 0.054 and 0.80 ± 0.085, respectively. Pathway and blood disease enrichment analyses of clinical and metabolomic biomarkers among infected patients showed that sepsis disease was accompanied by abnormal nitrogen metabolism, cell respiratory disorder, and renal or intestinal failure. The panel of selected clinical and metabolomic characteristics might be powerful biomarkers to discriminate patients with sepsis.

Metabolomic Analysis Reveals Distinct Profiles in the Plasma and Urine Associated with IgE Reactions in Childhood Asthma

Several metabolomics studies have identified altered metabolic pathways that are related to asthma. However, an integrative analysis of the metabolic responses across blood and urine for a comprehensive framework of asthma in early childhood remains lacking. Fifty-four age-matched children with asthma (n = 28) and healthy controls (n = 26) were enrolled. Metabolome analysis of the plasma and urine samples was performed using ¹H-nuclear magnetic resonance (NMR) spectroscopy coupled with partial least-squares discriminant analysis (PLS-DA). Integrated analysis of blood and urine metabolic profiling related to IgE reactions for childhood asthma was investigated. A significantly higher plasma histidine level was found, in parallel with lower urinary 1-methylnicotinamide and trimethylamine N-oxide (TMAO) levels, in children with asthma compared to healthy controls. Compared to children without allergic sensitization, 11 (92%) plasma metabolites and 8 (80%) urinary metabolites were found to be significantly different in children with IgE and food sensitization respectively. There were significant correlations between the plasma 3-hydroxybutyric acid and excreted volumes of the hydroxy acids, which were strongly correlated to plasma leucine and valine levels. Urine N-phenylacetylglycine, a microbial-host co-metabolite, was strongly correlated with total serum and food allergen-specific IgE levels. Plasma pyruvate and urine valine, leucine, and isoleucine degradation metabolisms were significantly associated with allergic sensitization for childhood asthma. In conclusion, blood and urine metabolome reflect different metabolic pathways in allergic reactions. Plasma pyruvate metabolism to acetic acid appears to be associated with serum IgE production, whereas urine branched-chain amino acid metabolism primarily reflects food allergic reactions against allergies.

Serum metabolite profiles as potential biochemical markers in young adults with community-acquired pneumonia cured by moxifloxacin therapy

Despite the utilization of various biochemical markers and probability calculation algorithms based on clinical studies of community-acquired pneumonia (CAP), more specific and practical biochemical markers remain to be found for improved diagnosis and prognosis. In this study, we aimed to detect the alteration of metabolite profiles, explore the correlation between serum metabolites and inflammatory markers, and seek potential biomarkers for young adults with CAP. 13 Eligible young mild CAP patients between the ages of 18 and 30 years old with CURB65 = 0 admitted to the respiratory medical department were enrolled, along with 36 healthy participants as control. Untargeted metabolomics profiling was performed and metabolites including alcohols, amino acids, carbohydrates, fatty acids, etc. were detected. A total of 227 serum metabolites were detected. L-Alanine, 2-Hydroxybutyric acid, Methylcysteine, L-Phenylalanine, Aminoadipic acid, L-Tryptophan, Rhamnose, Palmitoleic acid, Decanoylcarnitine, 2-Hydroxy-3-methylbutyric acid and Oxoglutaric acid were found to be significantly altered, which were enriched mainly in propanoate and tryptophan metabolism, as well as antibiotic-associated pathways. Aminoadipic acid was found to be significantly correlated with CRP levels and 2-Hydroxy-3-methylbutyric acid and Palmitoleic acid with PCT levels. The top 3 metabolites of diagnostic values are 2-Hydroxybutyric acid(AUC = 0.90), Methylcysteine(AUC = 0.85), and L-Alanine(AUC = 0.84). The AUC for CRP and PCT are 0.93 and 0.91 respectively. Altered metabolites were correlated with inflammation severity and were of great diagnostic value for CAP.

New insights into pediatric community-acquired pneumonia gained from untargeted metabolomics: A preliminary study

BACKGROUND

Available diagnostics often fail to distinguish viral from bacterial causes of pediatric community-acquired pneumonia (pCAP). Metabolomics, which aims at characterizing diseases based on their metabolic signatures, has been applied to expand pathophysiological understanding of many diseases. In this exploratory study, we used the untargeted metabolomic analysis to shed new light on the etiology of pCAP.

METHODS

Liquid chromatography coupled with mass spectrometry was used to quantify the metabolite content of urine samples collected from children hospitalized for CAP of pneumococcal or viral etiology, ascertained using a conservative algorithm combining microbiological and biochemical data.

RESULTS

Fifty-nine children with CAP were enrolled over 16 months. Pneumococcal and viral cases were distinguished by means of a multivariate model based on 93 metabolites, 20 of which were identified and considered as putative biomarkers. Among these, six metabolites belonged to the adrenal steroid synthesis and degradation pathway.

CONCLUSIONS

This preliminary study suggests that viral and pneumococcal pneumonia differently affect the systemic metabolome, with a stronger disruption of the adrenal steroid pathway in pneumococcal pneumonia. This finding may lead to the discovery of novel diagnostic biomarkers and bring us closer to personalized therapy for pCAP.

Gut microbial-derived butyrate is inversely associated with IgE responses to allergens in childhood asthma

BACKGROUND

A comprehensive metabolomics-based approach to address the impact of specific gut microbiota on allergen sensitization for childhood rhinitis and asthma is still lacking.

METHODS

Eighty-five children with rhinitis (n = 27) and with asthma (n = 34) and healthy controls (n = 24) were enrolled. Fecal metabolomic analysis with ¹ H-nuclear magnetic resonance (NMR) spectroscopy and microbiome composition analysis by bacterial 16S rRNA sequencing were performed. An integrative analysis of their associations with allergen-specific IgE levels for allergic rhinitis and asthma was also assessed.

RESULTS

Amino acid, β-alanine, and butanoate were the predominant metabolic pathways in the gut. Among them, amino acid metabolism was negatively correlated with the phylum Firmicutes, which was significantly reduced in children with rhinitis and asthma. Levels of histidine and butyrate metabolites were significantly reduced in children with rhinitis (P = 0.029) and asthma (P = 0.009), respectively. In children with asthma, a reduction in butyrate-producing bacteria, including Faecalibacterium and Roseburia spp., and an increase in Clostridium spp. were negatively correlated with fecal amino acids and butyrate, respectively (P < 0.01). Increased Escherichia spp. accompanied by increased β-alanine and 4-hydroxybutyrate appeared to reduce butyrate production. Low fecal butyrate was significantly associated with increased total serum and mite allergen-specific IgE levels in children with asthma (P < 0.05).

CONCLUSION

A reduced fecal butyrate is associated with increased mite-specific IgE levels and the risk of asthma in early childhood. Fecal β-alanine could be a specific biomarker connecting the metabolic dysbiosis of gut microbiota, Clostridium and Escherichia spp., in childhood asthma.

Metabolomics Reveals Anaerobic Bacterial Fermentation and Hypoxanthine Accumulation for Fibrinous Pleural Effusions in Children with Pneumonia

Fibrin formation in infectious parapneumonic effusion (IPE) characterizes complicated parapneumonic effusion and is important for providing guidelines for the management of IPEs that require aggressive interventions. We aim to identify metabolic mechanisms associated with bacterial invasion, inflammatory cytokines, and biochemical markers in cases of fibrinous infectious pleural effusions in children with pneumonia. Pleural fluid metabolites were determined by ¹H nuclear magnetic resonance spectroscopy. Metabolites that contributed to the separation between fibrinous and nonfibrinous IPEs were identified using supervised partial least squares discriminant analysis ( Q²/ R² = 0.84; P_permutation < 0.01). IL-1β in the inflammatory cytokines and glucose in the biochemical markers were significantly correlated with 11 and 9 pleural fluid metabolites, respectively, and exhibited significant overlaps. Four metabolites, including glucose, lactic acid, 3-hydroxybutyric acid, and hypoxanthine, were significantly correlated with plasminogen activator inhibitor type 1 in the fibrinolytic system enzymes. Metabolic pathway analysis revealed that anaerobic bacterial fermentation with increased lactic acid and butyric acid via glucose consumption and adenosine triphosphate hydrolysis with increased hypoxanthine appeared to be associated with fibrinous IPE. Our results demonstrate that an increase in lactic acid anaerobic fermentation and hypoxanthine accumulation under hypoxic conditions are associated with fibrin formation in IPE, representing advanced pleural inflammatory progress in children with pneumonia.

Metabolic regulation protects mice against Klebsiella pneumoniae lung infection

PURPOSE

Klebsiella pneumoniae-caused pneumonia is a risk factor for development of lung injury. However, the current clinical isolates of K. pneumoniae are mostly multidrug-resistance and thus must be addressed with new treatments. One ideal approach is to enhance the innate immunity of the infected host through metabolic modulators.

MATERIALS AND METHODS

We used GC/MS-based metabolomics to profile the metabolomes among Control, Dead and Survival groups. The key metabolites were administrated in mice, and the bacterial loads in lung and survival were measured. The effect of the key metabolites on macrophage phagocytosis was determined by flow cytometry.

RESULTS

Compared with the mice that compromised from K. pneumoniae lung infection, mice that survived the infection displayed the varied metabolomic profile. The differential analysis of metabolome showed D-Glucose, Glutamine, L-Serine, Myo-inositol, Ethanedioic acid and Lactic acid related to the host surviving a K. pneumoniae lung infection. Further pathway enrichment analysis proposed that valine, leucine and isoleucine biosynthesis involved in outcome of lung infection. The follow-up data showed that exogenous L-Serine, L-Valine and L-Leucine could decline the load of K. pneumoniae in infected lung and increases the mouse survival. More interestingly, L-Serine, L-Valine and L-Leucine also were able to promote macrophage phagocytosis that is the natural way to promote hosts to clear lung pathogens.

CONCLUSIONS

Our study establishes a novel strategy of identifying metabolic modulator from surviving host and emphasizes the feasibility of employing the metabolic modulator as a therapy for K. pneumoniae lung infection.