MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

Pang, Zhiqiang; Chong, Jasmine; Li, Shuzhao; Xia, Jianguo

doi:10.3390/metabo10050186

Cited by 445 publications

(344 citation statements)

References 47 publications

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“…MetaboAnalystR 3.0 [ 51 ], statTarget2 [ 52 ] and Bioconductor package manager using R programming language [ 53 ], were used to perform statistical analyses. Quality control based signal correction was performed using random forest implementation (QC-RFSC) [ 54 ].…”

Section: Methodsmentioning

confidence: 99%

Potential Lipid Signatures for Diagnosis and Prognosis of Sepsis and Systemic Inflammatory Response Syndrome

et al. 2020

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Systemic inflammatory response syndrome (SIRS) and sepsis are two conditions which are difficult to differentiate clinically and which are strongly impacted for prompt intervention. This study identified potential lipid signatures that are able to differentiate SIRS from sepsis and to predict prognosis. Forty-two patients, including 21 patients with sepsis and 21 patients with SIRS, were involved in the study. Liquid chromatography coupled to mass spectrometry and multivariate statistical methods were used to determine lipids present in patient plasma. The obtained lipid signatures revealed 355 features for the negative ion mode and 297 for the positive ion mode, which were relevant for differential diagnosis of sepsis and SIRS. These lipids were also tested as prognosis predictors. Lastly, L-octanoylcarnitine was found to be the most promising lipid signature for both the diagnosis and prognosis of critically ill patients, with accuracies of 75% for both purposes. In short, we presented the determination of lipid signatures as a potential tool for differential diagnosis of sepsis and SIRS and prognosis of these patients.

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Section: Methodsmentioning

confidence: 99%

Potential Lipid Signatures for Diagnosis and Prognosis of Sepsis and Systemic Inflammatory Response Syndrome

et al. 2020

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“…The statistical significance was evaluated with Student's t test or oneway analysis of variance. The heatmap was performed on Metaboanalyst (76).The results were considered as significant for a p value≤0.05. Secondary data analysis and correlation matrices were calculated using the open-source software GNU-R. Bacterial growth counts across all the tested scenarios as well as metrics related to each lipid composition (viz.…”

Section: Methodsmentioning

confidence: 99%

The impact of plasma membrane lipid composition on flagella-mediated adhesion of enterohemorrhagicEscherichia coli

Cazzola

Lemaire

Acket

et al. 2020

Preprint

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AbstractEnterohemorrhagic Escherichia coli (EHEC) O157:H7 is a major cause of foodborne gastrointestinal illness. The adhesion of EHEC on host tissues is the first step enabling bacterial colonization. Adhesins like fimbriae and flagella mediate this mechanism. Here, we studied the interaction of the bacterial flagellum with the host cell’s plasma membrane using Giant Unilamellar Vesicles (GUVs) as a biologically relevant model. Cultured cell lines contain many different molecular components including proteins and glycoproteins. In contrast, with GUVs we can characterize the bacterial mode of interaction solely with a defined lipid part of the cell membrane. Bacterial adhesion on GUVs was dependent on the presence of the flagellar filament and its motility. By testing different phospholipid head groups, the nature of the fatty acid chains or the liposome curvature, we found that lipid packing is a key parameter to enable bacterial adhesion. Using HT-29 cells grown in the presence of polyunsaturated fatty acid (α-linolenic acid) or saturated fatty acid (palmitic acid), we found that α-linolenic acid reduced adhesion of wild type EHEC but not of a non-flagellated mutant. Finally, our results reveal that the presence of flagella is advantageous for the bacteria to bind to lipid rafts. We speculate that polyunsaturated fatty acids prevent flagellar adhesion on membrane bilayers and play a clear role for optimal host colonization. Flagella-mediated adhesion to plasma membranes has broad implications to host-pathogen interactions.ImportanceBacterial adhesion is a crucial step to allow bacteria to colonize their hosts, invade tissues and form biofilm. Enterohemorrhagic E. coli O157:H7 is a human pathogen and the causative agent of diarrhea and hemorrhagic colitis. Here, we use biomimetic membrane models and cell lines to decipher the impact of lipid content of the plasma membrane on enterohemorrhagic E. coli flagella-mediated adhesion. Our findings provide evidence that polyunsaturated fatty acid (α-linolenic acid) inhibits E. coli flagella adhesion to the plasma membrane in a mechanism separate from its antimicrobial and anti-inflammatory functions. In addition, we confirm that cholesterol-enriched lipid microdomains, often called lipid rafts are important in bacterial adhesion. These findings significantly strengthen plasma membrane adhesion via bacterial flagella in an important human pathogen. This mechanism represents a promising target for the development of novel anti-adhesion therapies.

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“…To explore if combining parameters of microglia morphology, phenotype and density could reveal different MS subgroups, we performed a principle component analysis (PCA) with scaling of the parameters using the web-based MetaboAnalyst (http:// www.metaboanalyst.ca) 47 . We included measures for microglia morphology and shape (AUC derived from the sholl analysis and soma size), microglia protein expression (P2Y12, TMEM119, CD68, HLA class II) and microglial density.…”

Section: Principal Component Analysismentioning

confidence: 99%

Meningeal inflammation in multiple sclerosis induces phenotypic changes in cortical microglia that differentially associate with neurodegeneration

Olst

Rodriguez-Mogeda

Picon-Munoz

et al. 2020

Preprint

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Meningeal inflammation strongly associates with demyelination and neuronal loss in the underlying cortex of progressive MS patients, contributing to clinical disability. However, the pathological mechanisms of meningeal inflammation-induced cortical pathology are still largely elusive. Using extensive analysis of human post-mortem tissue, we identified two distinct microglial phenotypes, termed MS1 and MS2, in the cortex of progressive MS patients. These phenotypes differed in morphology and protein expression, but both associated with inflammation of the overlying meninges. We could replicate the MS-specific microglial phenotypes in a novel in vivo rat model for progressive MS-like meningeal inflammation, with microglia present at 1 month post-induction resembling MS1 microglia whereas those at 2 months acquired an MS2-like phenotype. Interestingly, MS1 microglia were involved in presynaptic displacement and phagocytosis and associated with a relative sparing of neurons in the MS and animal cortex. In contrast, the presence of MS2 microglia coincided with substantial neuronal loss. Taken together, we uncovered that in response to meningeal inflammation, microglia acquire two distinct phenotypes that differentially associate with neurodegeneration in the progressive MS cortex. Our data suggests that these phenotypes occur sequentially and that microglia may lose their protective properties over time, contributing to neuronal loss.

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MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

Cited by 445 publications

References 47 publications

Potential Lipid Signatures for Diagnosis and Prognosis of Sepsis and Systemic Inflammatory Response Syndrome

Potential Lipid Signatures for Diagnosis and Prognosis of Sepsis and Systemic Inflammatory Response Syndrome

The impact of plasma membrane lipid composition on flagella-mediated adhesion of enterohemorrhagicEscherichia coli

Meningeal inflammation in multiple sclerosis induces phenotypic changes in cortical microglia that differentially associate with neurodegeneration

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