Fold Change Analysis Research Articles

Identification of the Intestinal Microbes Associated with Locomotion.

Given the impact of the gut microbiome on human physiology and aging, it is possible that the gut microbiome may affect locomotion in the same way as the host's own genes. There is not yet any direct evidence linking the gut microbiome to locomotion, though there are some potential connections, such as regular physical activity and the immune system. In this study, we demonstrate that the gut microbiome can contribute differently to locomotion. We remodeled the original gut microbiome of mice through fecal microbiota transplantation (FMT) using human feces and compared the changes in locomotion of the same mice before and three months after FMT. We found that FMT affected locomotion in three different ways: positive, none (the same), and negative. Analysis of the phylogenesis, α-diversities, and β-diversities of the gut microbiome in the three groups showed that a more diverse group of intestinal microbes was established after FMT in each of the three groups, indicating that the human gut microbiome is more diverse than that of mice. The FMT-remodeled gut microbiome in each group was also different from each other. Fold change and linear correlation analyses identified Lacrimispora indolis, Pseudoflavonifractor phocaeensis, and Alistipes senegalensis in the gut microbiome as positive contributors to locomotion, while Sphingobacterium cibi, Prevotellamassilia timonensis, Parasutterella excrementihominis, Faecalibaculum rodentium, and Muribaculum intestinale were found to have negative effects. This study not only confirms the presence of gut microbiomes that contribute differently to locomotion, but also explains the mixed results in research on the association between the gut microbiome and locomotion.

400-P: Spatial Metabolomics Analysis by MSI-DeepPath Identifies Key Pathways in ZDF Diabetic Kidney Disease Model

Background: The Zucker Diabetic Fatty (ZDF) rat is a popular model of type 2 diabetes as it develops pathologic changes in the kidney similar to human diabetic nephropathy. To identify metabolic pathways linked to pathologic features MALDI mass spectrometry imaging (MSI) can be a powerful platform. However, quantification of metabolites from MALDI-MSI is very challenging. Our MSI-DeepPath computational platform enables spatial quantitation of metabolites from any tissue section size. Methods: Control and obese ZDF male rats (age 6mo, n=5/group) were studied. Spatial metabolomics analysis of kidney tissue sections was performed using MALDI-MSI at 20 µm resolution. Metabolites were detected at mass accuracy <2 ppm using Q-Exactive orbitrap MS followed by annotations using METASPACE. SygnaMap’s MSI-DeepPath computational platform was used to quantify the annotated metabolites. Results: Of 400 metabolites annotated at m/z range 70-500 Da the top features were selected using t-test, p value and fold change analysis. The top 20 biomarkers that separated ZDF from controls included glucose, serine, histidine, and glutamate. The most significantly upregulated metabolite was tyrosinamide (8.2-fold, p=8.02 x 10-9 ). The most significant downregulated metabolite was L-threonine (0.3-fold, p=2.03 x 10-9). Pathway analysis revealed that aminoacyl-tRNA biosynthesis, galactose, glyoxylate and dicarboxylate metabolic pathways can discriminate healthy from diabetic kidney samples. Conclusion: MSIDeepPath enables quantification of spatial metabolomics of tissue sections using MALDI-MSI data. This new tool can be applied across normal and diseased samples allowing for robust statistical analysis of spatial omics data. Using MSI-DeepPath on kidney sections from the ZDF rat we identified regulation of metabolites linked to key pathways of diabetic kidney disease. Disclosure L.Hejazi: None. S.Sharma: None. A.Ruiz: None. G.Zhang: None. F.C.Tucci: None. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. Funding National Institutes of Health (1R43DK130732-01A1)

Metabolic Changes in Blood-derived Extracellular Vesicles of Malnourished Breast Cancer Patients.

Cancer cachexia describes a multifactorial wasting syndrome marked by a metabolic imbalance leading to the loss of muscle and fat tissue. Extracellular vesicles (EV) provide unique insights into their parental cells' metabolism. The value of these vesicles as diagnostic tools in cancer cachexia has not been investigated so far. A previously analyzed metabolomics dataset on large EV from breast cancer patients was used for analyzing the metabolomic changes in patients with malnutrition. Follow-up time was 6 months. The data were analyzed using fold change analysis, volcano plotting, receiver operator characteristic (ROC) analysis, pathway analysis, and survival analysis. In patients with weight loss, statistical analysis revealed an increase in lysophosphatidylcholines (lysoPC a C16:0, lysoPC a C18:0, lysoPC a C18:1, lysoPC a C18:2, lysoPC a C20:4), sphingomyelins (SM (OH) C22:2 and SM C18:1), and phosphatidylcholines (PC aa C24:0, PC ae C34:3). When combined, these metabolites are a good predictor for cachexia in ROC curve analysis (AUC of 0.970; 95%CI=0.920-1.000; p<0.0001). Pathway analysis revealed an involvement of metabolites in "choline metabolism in cancer" and "glycerophospholipid metabolism". Large EV reflect metabolic changes in cancer patients suffering from cancer cachexia. Metabolic changes at the time of drawing blood were associated with the weight status (stable vs. weight loss) six months later and thereby could have a predictive impact.

Metabolomics Approach Reveals Important Glioblastoma Plasma Biomarkers for Tumor Biology.

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

Metabolomics to study the sublethal effects of diazepam and irbesartan on glass eels (Anguilla anguilla)

Since glass eels are continuously exposed to contamination throughout their migratory journey in estuaries, to a certain extent the fall in the population of this endangered species might be attributed to this exposure, which is especially acute in estuaries under high urban pressure. In this work, metabolomics was used to address the main objective of this study, to evaluate the effects of two pharmaceuticals previously identified as potential concerning chemicals for fish (diazepam and irbesartan) on glass eels. An exposure experiment to diazepam, irbesartan and their mixture was carried out over 7 days followed by 7 days of depuration phase. After exposure, glass eels were individually sacrificed using a lethal bath of anesthesia, and then an unbiased sample extraction method was used to extract separately the polar metabolome and the lipidome. The polar metabolome was submitted to targeted and non-targeted analysis, whereas for the lipidome only the non-targeted analysis was carried out. A combined strategy using partial least squares discriminant analysis and univariate and multivariate statistical analysis (ANOVA, ASCA, t-test, and fold-change analysis) was used to identify the metabolites altered in the exposed groups with respect to the control group. The results of the polar metabolome analysis revealed that glass eels exposed to the diazepam-irbesartan mixture were the most impacted ones, with altered levels for 11 metabolites, some of them belonging to the energetic metabolism, which was confirmed to be sensitive to these contaminants. Additionally, the dysregulation of the levels of twelve lipids, most of them with energetic and structural functions, was also found after exposure to the mixture, which might be related to oxidative stress, inflammation, or alteration of the energetic metabolism.

Up-Regulation of S100 Gene Family in Brain Samples of a Subgroup of Individuals with Schizophrenia: Meta-analysis.

The S100 proteins family is known to affect neuroinflammation and astrocyte activation, which have been suggested to be contributors to the pathogenesis of schizophrenia. We conducted a systematic meta-analysis of S100 genes differential expression in postmortem samples of patients with schizophrenia vs. healthy controls, following the commonly used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Twelve microarray datasets met the inclusion criteria (overall 511 samples,253 schizophrenia and 258 controls were analyzed). Nine out of 21 genes were significantly up-regulated or with tendency for up-regulation. A per-sample fold change analysis indicated that the S100 genes' up-regulation was concentrated in a subgroup of the patients. None of the genes have been found to be down-regulated. ANXA3, which encodes Annexin 3 protein and was associated with neuroinflammation, was up-regulated and positively correlated with the S100 genes' expression pattern. In addition, astrocytes and endothelial cell markers were significantly correlated with S100A8 expression. S100 correlation with ANXA3 and endothelial cell markers suggests that the up-regulation we detected reflects increased inflammation. However, it might also reflect astrocytes abundance or activation. The fact that S100 proteins were shown to be up-regulated in blood samples and other body fluids of patients with schizophrenia suggests a potential role as biomarkers, which might help disease subtyping, and the development of etiological treatments for immune dysregulation in schizophrenia.

312 Metabolomics Approach to Cellular Senescence: Characterizing the Secretory Phenotype and Metabolism of Irradiation-Induced Senescent Human Pre- Adipocytes

OBJECTIVES/GOALS: The study aims to identify and measure metabolites in irradiation-induced senescent pre-adipocytes induced by the increased secretion of pro-inflammatory cytokines. Through untargeted metabolomics, we seek to understand the alterations to metabolism and mitochondrial activity that occur during irradiation-induced senescence. METHODS/STUDY POPULATION: First, commercially available human primary subcutaneous pre-adipocytes were cultured in vitro, and irradiated to induce senescence. To confirm senescence, cells were stained for beta-galactosidase, which was positive in senescent pre-adipocytes. The cells and their conditioned cultured media were then collected and frozen for untargeted metabolomics to profile metabolites. The sample analysis is currently underway and will be conducted using central carbon isotope tracing and chromatograph mass spectrometry. Principal Component Analysis, fold change analysis, and heat maps will be used to detect and report the changes in metabolite signals. Oxygen consumption rate and extracellular acidification rate measurements are in progress at present using the Agilent Seahorse XF Cell Mito Stress Test. RESULTS/ANTICIPATED RESULTS: We expect that metabolites of central carbon metabolism and oxidative phosphorylation will be upregulated. The concentrations of metabolites of pathways altered by the pro-inflammatory cytokines that have been identified to be secreted by senescent cells are expected to be altered. The metabolites measured in conditioned culture media will provide insight into the changes to the cellular microenvironment caused by senescence. Finally, we anticipate that mitochondrial function, and both aerobic and anaerobic metabolism will be altered in senescent pre-adipocytes compared to controls. Through the present study, we will achieve a better understanding the metabolic alterations that occur as part of cell senescence in pre-adipocytes. DISCUSSION/SIGNIFICANCE: Adipose tissue dysfunction due to the accumulation of senescent cells has been linked to chronic diseases such as diabetes and insulin resistance, and inflammaging. Through this study, we expect to provide new insight into the metabolic alterations of senescence and offer a backbone for prospective translational human studies and clinical trials.

Efficient prioritization of CRISPR screen hits by accounting for targeting efficiency of guide RNA

BackgroundCRISPR-based screens are revolutionizing drug discovery as tools to identify genes whose ablation induces a phenotype of interest. For instance, CRISPR-Cas9 screening has been successfully used to identify novel therapeutic targets in cancer where disruption of genes leads to decreased viability of malignant cells. However, low-activity guide RNAs may give rise to variable changes in phenotype, preventing easy identification of hits and leading to false negative results. Therefore, correcting the effects of bias due to differences in guide RNA efficiency in CRISPR screening data can improve the efficiency of prioritizing hits for further validation. Here, we developed an approach to identify hits from negative CRISPR screens by correcting the fold changes (FC) in gRNA frequency by the actual, observed frequency of indel mutations generated by gRNA.ResultsEach gRNA was coupled with the “reporter sequence” that can be targeted by the same gRNA so that the frequency of mutations in the reporter sequence can be used as a proxy for the endogenous target gene. The measured gRNA activity was used to correct the FC. We identified indel generation efficiency as the dominant factor contributing significant bias to screening results, and our method significantly removed such bias and was better at identifying essential genes when compared to conventional fold change analysis. We successfully applied our gRNA activity data to previously published gRNA screening data, and identified novel genes whose ablation could synergize with vemurafenib in the A375 melanoma cell line. Our method identified nicotinamide N-methyltransferase, lactate dehydrogenase B, and polypyrimidine tract-binding protein 1 as synergistic targets whose ablation sensitized A375 cells to vemurafenib.ConclusionsWe identified the variations in target cleavage efficiency, even in optimized sgRNA libraries, that pose a strong bias in phenotype and developed an analysis method that corrects phenotype score by the measured differences in the targeting efficiency among sgRNAs. Collectively, we expect that our new analysis method will more accurately identify genes that confer the phenotype of interest.

Integrative analysis of sensory evaluation and non-targeted metabolomics to unravel tobacco leaf metabolites associated with sensory quality of heated tobacco.

Heated tobacco (Nicotiana tabacum L.) products are heating tobacco plug at a temperature of 350°C and produce different emissions in aerosol and sensory perceptions of tobacco leaf compared with combustible tobacco. Previous study assessed different tobacco varieties in heated tobacco for sensory quality and analyzed the links between sensory scores of the final products and certain chemical classes in tobacco leaf. However, contribution of individual metabolites to sensory quality of heated tobacco remains largely open for investigation. In present study, five tobacco varieties were evaluated as heated tobacco for sensory quality by an expert panel and the volatile and non-volatile metabolites were analyzed by non-targeted metabolomics profiling. The five tobacco varieties had distinct sensory qualities and can be classified into higher and lower sensory rating classes. Principle component analysis and hierarchical cluster analysis showed that leaf volatile and non-volatile metabolome annotated were grouped and clustered by sensory ratings of heated tobacco. Orthogonal projections to latent structures discriminant analysis followed by variable importance in projection and fold-change analysis revealed 13 volatiles and 345 non-volatiles able to discriminate the tobacco varieties with higher and lower sensory ratings. Some compounds such as β-damascenone, scopoletin, chlorogenic acids, neochlorogenic acids, and flavonol glycosyl derivatives had strong contribution to the prediction of sensory quality of heated tobacco. Several lyso-phosphatidylcholine and lyso-phosphatidylethanolamine lipid species, and reducing and non-reducing sugar molecules were also positively related to sensory quality. Taken together, these discriminating volatile and non-volatile metabolites support the role of leaf metabolites in affecting the sensory quality of heated tobacco and provide new information on the types of leaf metabolites that can be used to predict applicability of tobacco varieties for heated tobacco products.

Multi-country metabolic signature discovery for chicken health classification

IntroductionTo decrease antibiotic resistance, their use as growth promoters in the agricultural sector has been largely abandoned. This may lead to decreased health due to infectious disease or microbiome changes leading to gut inflammation.ObjectivesWe aimed to generate a m/z signature classifying chicken health in blood, and obtain biological insights from the resulting m/z signature.MethodsWe used direct infusion mass-spectrometry to determine a machine-learned metabolomics signature that classifies chicken health from a blood sample. We then challenged the resulting models by investigating the classification capability of the signature on novel data obtained at poultry houses in previously unseen countries using a Leave-One-Country-Out (LOCO) cross-validation strategy. Additionally, we optimised the number of mass/charge (m/z) values required to maximise the classification capability of Random Forest models, by developing a novel ranking system based on combined univariate t-test and fold-change analyses and building models based on this ranking through forward and reverse feature selection.ResultsThe multi-country and LOCO models could classify chicken health. Both resulting 25-m/z and 3784-m/z signatures reliably classified chicken health in multiple countries. Through mummichog enrichment analysis on the large m/z signature, we found changes in amino acid metabolism, including branched chain amino acids and polyamines.ConclusionWe reliably classified chicken health from blood, independent of genetic-, farm-, feed- and country-specific confounding factors. The 25-m/z signature can be used to aid development of a per-metabolite panel. The extended 3784-m/z version can be used to gain a deeper understanding of the metabolic causes and consequences of low chicken health. Together, they may facilitate future treatment, prevention and intervention.

Distinct effects of α-linolenic acid and docosahexaenoic acid on the expression of genes related to cholesterol metabolism and the response to infection in THP-1 monocytes and immune cells of obese humans

BackgroundMonocytes play a large role in chronic inflammatory conditions such as obesity, atherosclerosis and infection. Marine-derived omega-3 fatty acids such as docosahexaenoic acid (DHA) beneficially alter immune function and attenuate chronic inflammation in part by modifying gene expression. Comparisons with plant-derived omega-3 α-linolenic acid (ALA) on immune cell gene expression and function are limited. MethodsTranscriptome analysis was performed on THP-1 human monocytes treated with ALA, DHA or vehicle for 48 hr using fold change analysis, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), variable importance analysis (VIP), and ingenuity pathway analysis (IPA). Candidate genes were validated by qPCR. Functional assays evaluated the transcriptomic predictions. Expression of candidate transcripts identified in THP-1 cells were examined in PBMC from clinical trial (OXBIO; NCT 03583281) participants consuming ALA- or DHA-rich oil supplements. FindingsALA and DHA-treated monocytes presented distinct transcriptomic profiles as per VIP and PLS-DA. Both fatty acids were predicted to reduce cellular cholesterol content, while ALA would uniquely increase response to infection and chemotactic signals. Functional assays revealed ALA and DHA decreased cholesterol content. DHA significantly decreased the response to infection and chemotaxis, but ALA had no effect. Candidate transcripts responded similarly in PBMC from n-3 PUFA supplemented women with obesity. ConclusionALA and DHA differentially alter the transcription profiles and functions associated with the response to infection, chemotaxis, and cholesterol metabolism in mononuclear immune cells. Thus, they may uniquely affect related disease processes contributing to obesity, atherosclerosis, and the response to infection.

Investigation of dichlorodiphenyltrichloroethane (DDT) on xenobiotic enzyme disruption and metabolomic bile acid biosynthesis in DDT-sprayed areas using wild rats.

Dichlorodiphenyltrichloroethane (DDT) is an organochlorine insecticide used worldwide. Several studies have reported the toxic effects of DDT and its metabolites on steroid hormone biosynthesis; however, its environmental effects are not well understood. This study examined wild rats collected in DDT-sprayed areas of South Africa and quantified plasma metabolites using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). Fold change analysis of the metabolome revealed the effect of DDT on bile acid biosynthesis. Gene expression of the related enzyme in rat liver samples was also quantified. Significant association was found between DDT and gene expression levels related to constitutive androstane receptor mediated enzymes, such as Cyp2b1 in rat livers. However, our results could not fully demonstrate that enzymes related to bile acid biosynthesis were strongly affected by DDT. The correlation between DDT concentration and gene expression involved in steroid hormone synthesis in testis was also evaluated; however, no significant correlation was found. The disturbance of metabolic enzymes occurred in rat liver in the target area. Our results suggest that DDT exposure affects gene expression in wild rats living in DDT-sprayed areas. Therefore, there is a need for DDT toxicity evaluation in mammals living in DDT-sprayed areas. We could not find an effective biomarker that could reflect the mechanism of DDT exposure; however, this approach can provide new insights for future research to evaluate DDT effects in sprayed areas.

Expression of CLEC3B in Oral Squamous Cell Carcinoma and its Association with Clinicopathological Features

Background: Oral squamous cell carcinoma is one of the leading causes of cancer related morbidity worldwide. The socioeconomic status and clinicopathological parameters have predictive importance specifically for head and neck squamous cell carcinoma. Literature has reported various studies on CLEC3B, and its correlation with OSCC has yet to be explored. Aim: To examine the association of CLEC3B expression with the clinicopathological parameters in the blood and saliva of OSCC patients and healthy individuals. Methodology: This case-control study was conducted on 40 blood and 40 saliva samples recruited from Ziauddin University Hospital and the Abbasi Shaheed Hospital. Blood and saliva samples were taken from 20 OSCC patients as well as 20 healthy individuals as controls. Demographic details including age, gender, and habits were collected directly from participants on a proforma. RT-qPCR was carried out to determine the association of CLEC3B expression in the blood and saliva of OSCC patients and healthy individuals with clinicpathological parameters. Result: Significant expression was observed in blood and saliva samples of OSCC (p-value 0.001*). CLEC3B was significantly expressed in saliva samples with respect to pathological grading and staging of OSCC. Moreover the foldchange analysis was considerably underexpressed in both samples (saliva p-value 0.042, blood p-value 0.014).Whereas no significant association was found with respect to the habits, age and gender of patients. The significant expression of CLEC3B in saliva may improve the ability of clinicians to detect OSCC at an early stage and may help to reduce the mortality rate of patients. Conclusion: A significant association of salivary CLEC3B was observed with the staging and grading of OSCC and it was found that CLEC3B may have the potential to be used as a suitable biomarker for the detection and diagnosis of OSCC. This study could provide insight into ongoing evidence on the importance of CLEC3B in early detection of oral cancer. Furthermore, the salivary gene expression can be used to characterize tumor grading and staging. Keywords: CLEC3B, Biomarkers, Gene expression, Oral cancer, RT-qPCR, molecular diagnostics

OXTR Gene mRNA Expression is Correlated to Prosocial Behavior of Children in the Golden Generation Program of Nusa Tenggara Barat

BACKGROUND: Cases of undernutrition, such as stunting and wasting, in Nusa Tenggara Barat (NTB), Indonesia, was found to be relatively high. Therefore, local government launched a golden generation program called GEN NTB to improve the quality of human resources by achieving a healthy, intelligent, devout, and productive generation in 2045. One of the genes known to be related with prosocial behavior is the oxytocin transferase (OXTR) gene. This study was conducted to determine the association between OXTR gene mRNA expression and prosocial behavior of the GEN NTB children.METHODS: This was an analytical observational case-control study involving 25 children as GEN NTB samples and 26 children as controls. Blood samples were tested for OXTR protein level with enzyme-linked immunosorbent assay (ELISA), and OXTR mRNA expression with real time polymerase chain reaction (RT-PCR). Prosocial behavior was characterized and determined by using a rating method, which valued from 1 to 4 for poor to very good behavior.RESULTS: The average OXTR protein levels of the GEN NTB group was 88.28 ng/mL, which were higher than the average OXTR protein levels of control group (2.41 ng/mL). According to fold change analysis, the OXTR mRNA expression in GEN NTB group was also higher than the control group (10.91 vs. 6.40). Interestingly, observations on the prosocial behavior of the GEN NTB group showed significantly higher rate values compared to the control group (17.3 vs. 8.0, p=0.034). Hence, these findings showed that the OXTR protein level and OXTR mRNA expression was correlated with the better prosocial behavior.CONCLUSION: Higher rating of prosocial behavior of the GEN NTB children is related to the higher OXTR mRNA expression levels. This might be attributed to the interventions of GEN NTB program that may elevate children's quality of life since early childhood.KEYWORDS: GEN NTB, OXTR protein, mRNA expression, prosocial behavior, children

Potential Plasma Metabolic Biomarkers of Tourette Syndrome Discovery Based on Integrated Nontargeted and Targeted Metabolomics Screening Plasma Metabolic Biomarkers of TS.

Tourette syndrome (TS) is a chronic neuropsychiatric disorder characterized by abnormal movements, phonations, and tics, but an accurate TS diagnosis remains challenging and indeed depends on its description of clinical symptoms. Our study was conducted to discover and verify some metabolite biomarkers based on nontargeted and targeted metabolomics. We conducted untargeted ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) for preliminary screening of potential biomarkers on 30 TS patients and 10 healthy controls and then performed validation experiments based on targeted ultrahigh-performance liquid chromatography triple quadrupole-MS (UHPLC/MS/MS) on 35 TS patients and 14 healthy controls. 1775 differentially expressed metabolites were identified by partial least squares discriminant analysis (PLS-DA), fold-change analysis, T-test, and hierarchical clustering analysis (adjusted p value <0.05 and |logFC| > 1). TS plasma samples were found to be differentiated from healthy samples in our approach. Furthermore, aspartate and asparagine metabolism pathways were considered to be a significant enrichment pathway in TS progression based on metabolite pathway enrichment analysis. For the 8 metabolites involved in this pathway that we detected, we then performed validation experiments based on targeted UHPLC/MS/MS. The t-test, Mann-Whitney U test, and receiver operating characteristic (ROC) curve analysis were used to determine potential biomarkers. Ultimately, L-arginine and L-pipecolic acid were validated as significantly differentiated metabolites (p < 0.05), with an AUC of 70.0% and 80.3%, respectively. L-pipecolic acid was defined as a potential biomarker for TS diagnosis by the combined application of nontargeted and targeted metabolomic analysis.

Metabolic changes during exclusive enteral nutrition in pediatric Crohn’s disease patients

Background and aimsExclusive enteral nutrition is recommended as a first-line treatment in active pediatric Crohn’s Disease, but its mechanism of action is still not clear. We aimed to assess alterations in the metabolic profile of newly diagnosed pediatric Crohn’s Disease patients before and during exclusive enteral nutrition therapy.MethodsPlasma samples from 14 pediatric Crohn’s Disease patients before and after 3–4 weeks on exclusive enteral nutrition were analyzed using mass spectrometry. T-test, fold change and orthogonal partial least squares discriminant analysis were used for mining significant features. Correlation analysis was performed between the annotated features and the weighted pediatric Crohn’s disease activity index using Pearson r distance.ResultsAmong the 13 compounds which decreased during exclusive enteral nutrition, most are related to diet, while one is a bacterial metabolite, Bacteriohopane-32,33,34,35-tetrol. The phosphatidic acid metabolite PA(15:1/18:0) was significantly reduced and correlated with the weighted pediatric Crohn’s disease activity index. Lipids increased during exclusive enteral nutrition therapy included phosphatidylethanolamines; PE(24:1/24:1), PE(17:2/20:2) and one lactosylceramide; LacCer(d18:1/14:0).ConclusionFood additives and other phytochemicals were the major metabolites, which decreased following the exclusion of a regular diet during exclusive enteral nutrition. An alteration in bacterial biomarkers may reflect changes in intestinal microbiota composition and metabolism. Thus, metabolomics provides an opportunity to characterize the molecular mechanisms of dietary factors triggering Crohn’s Disease activity, and the mechanisms of action of exclusive enteral nutrition, thereby providing the basis for the development and evaluation of improved intervention strategies for prevention and treatment.

Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography-Mass spectrometry.

Objective: Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. Methods: In total, 50 cases of OSA patients (49.74 ± 11.87years) and 30 controls (39.20 ± 3.29years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea-hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography-mass spectrometry (GC-MS). Results: A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Conclusion: Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.

Temporal lipid profiling in the progression from acute to chronic heart failure in mice and ischemic human hearts

Background and aimsMyocardial infarction (MI) is a leading cause of heart failure (HF). After MI, lipids undergo several phasic changes implicated in cardiac repair if inflammation resolves on time. However, if inflammation continues, that leads to end stage HF progression and development. Numerous studies have analyzed the traditional risk factors; however, temporal lipidomics data for human and animal models are limited. Thus, we aimed to obtain sequential lipid profiling from acute to chronic HF. MethodsHere, we report the comprehensive lipidome of the hearts from diseased and healthy subjects. To induce heart failure in mice, we used a non-reperfused model of coronary ligation, and MI was confirmed by echocardiography and histology, then temporal kinetics of lipids in different tissues (heart, spleen, kidney), and plasma was quantitated from heart failure mice and compared with naïve controls. For lipid analysis in mouse and human samples, untargeted liquid chromatography-linear trap quadrupole orbitrap mass spectrometry (LC-LTQ-Orbitrap MS) was performed. ResultsIn humans, multivariate analysis revealed distinct cardiac lipid profiles between healthy and ischemic subjects, with 16 lipid species significantly downregulated by 5-fold, mainly phosphatidylethanolamines (PE), in the ischemic heart. In contrast, PE levels were markedly increased in mouse tissues and plasma in chronic MI, indicating possible cardiac remodeling. Further, fold change analysis revealed site-specific lipid biomarkers for acute and chronic HF. A significant decrease in sulfatides (SHexCer (34:1; 2O)) and sphingomyelins (SM (d18:1/16:0)) was observed in mouse tissues and plasma in chronic HF. ConclusionsOverall, a significant decreased lipidome in human ischemic LV and differential lipid metabolites in the transition of acute to chronic HF with inter-organ communication could provide novel insights into targeting integrative pathways for the early diagnosis or development of novel therapeutics to delay/prevent HF.

Characterization of terpenoids and norisoprenoids from base and retail Qingke Baijiu by GC × GC-TOFMS and multivariate statistical analysis

Qingke (highland barley) Baijiu is a special Chinese Baijiu which is mainly produced from Qinghai-Tibet Plateau. Since the pine board is used as the bottom of the fermentation pit, we deduced that the terpenoids and norisoprenoids in pine board might be introduced into Qingke Baijiu. Thus, the terpenoids and norisoprenoids in Qingke Baijiu were investigated by headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The results showed that γ-terpinene (0.70–530.72 μg/L), α-phellandrene (0.34–256.66 μg/L), longicyclene (0–38.55 μg/L), α-pinene (1.21–35.54 μg/L) and limonene (0.93–23.69 μg/L) were the top 5 terpenoids/norisoprenoids in Qingke Baijiu. Pulegone was detected and reported for the first time in Baijiu, and the concentrations in Qingke Baijiu were 0.78 μg/L (fresh) and 3.90 μg/L (7 years old). According to the principal component analysis (PCA) plot, young, aged, and retail Qingke Baijiu could be differentiated clearly. Fold change (FC) and t-tests analysis indicated that β-pinene, γ-terpinene, and α-selinene were the most different terpenoids/norisoprenoids between young and aged Qingke Baijiu, and longifolene was the most different terpenoids/norisoprenoids between base and retail Qingke Baijiu. The terpenoids and norisoprenoids, such as (E)-β-ionone, isoborneol and β-cyclocitral, could be potential markers indicating the ageing process of Qingke Baijiu.

Metabolomics Analysis of Lettuce (Lactuca sativa L.) Affected by Low Potassium Supply

Lettuce is a commercially significant leafy vegetable worldwide. Potassium (K) is an essential macronutrient for lettuce growth and development and significantly impacts its metabolites. Biomarkers that are indicative of variations in the K status of lettuce before the occurrence of biophysical changes (e.g., leaf or canopy morphological, textural and color features), can be adopted to determine the early K status of lettuce. To understand the effect of low K on diverse metabolites, we examined the metabolic response of lettuce in a closed cultivation room under controlled conditions. The evaluation was based on large-scale untargeted metabolomics assay of the K group using liquid chromatography-mass spectrometry. Data were analyzed with a fold-change (FC) analysis, t-test, and orthogonal partial least square-discriminant analysis. Fifty-two metabolites were classified into two groups by the FC, p, and the variable importance in projection (VIP). Low K led to an increment in 40 metabolites (FC &gt; 2, p &lt; 0.05, VIP &gt; 1) and a decrease in 12 metabolites (FC &lt; 0.5, p &lt; 0.05, VIP &gt; 1). Ten pathways were significantly enriched with metabolic biomarkers. In light of the complex interactive relationships among N, P, and K, the top five biomarkers were screened further by VIP &gt; 4.00. Adenosine, FA 18:1+3O, uridine, cis-aconitate, and D(-)-gulono-gamma-lactone showed an increase in low-K stress samples, and may be considered potential metabolic biomarkers. This study validates the impact of low K on lettuce metabolism, and identifies biomarkers that can be used to monitor the K status in lettuce.