Unraveling Cecal Alterations in Colonized Mice through Comprehensive Metabolic Profiling.

The disruption of gut microbiota caused by antibiotics favors the intestinal colonization of - a Gram-positive, spore-forming anaerobic bacterium that causes potentially fatal gastrointestinal infections. In an endeavor to elucidate the complexities of the gut-brain axis in the context of infection (CDI), a murine model has been used to investigate the potential effects of antibiotic administration and subsequent colonization by , as well as the impact of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the cecal metabolome for the first time. This follows our previous research which highlighted the metabolic effect of CDI and these treatments in the brain and employs the same four different metabolomics-based methods (targeted GC-MS/MS, targeted HILIC-MS/MS, untargeted RP-LC-HRMS/MS and untargeted GC-MS).

Metabolic Phenotyping Study of Mouse Brain Following Microbiome Disruption by Colonization.

infection (CDI) is responsible for an increasing number of cases of post-antibiotic diarrhea worldwide, which has high severity and mortality among hospitalized elderly patients. The disruption of gut microbiota due to antibacterial medication facilitates the intestinal colonization of . In the present study, a murine model was used to investigate the potential effects of antibiotic administration and subsequent colonization by , as well as the effects of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the brain metabolome for the first time.

Metabolic consequences for mice lacking Endosialin: LC-MS/MS-based metabolic phenotyping of serum from C56Bl/6J Control and CD248 knock-out mice.

Introduction: The Endosialin/CD248/TEM1 protein is expressed in adipose tissue and its expression increases with obesity. Recently, genetic deletion of CD248 has been shown to protect mice against atherosclerosis on a high fat diet.

Objectives: We investigated the effect of high fat diet feeding on visceral fat pads and circulating lipid profiles in CD248 knockout mice compared to controls.

Metabolic Phenotyping Study of Mouse Brains Following Acute or Chronic Exposures to Ethanol.

The chronic and acute effect of ethanol administration on the metabolic phenotype of mouse brain was studied in a C57BL/6 mouse model of ethanol abuse using both untargeted and targeted ultra performance liquid chromatography-tandem mass spectrometry. Two experiments based on either chronic (8 week) exposure to ethanol of both male and female mice or acute exposure of male mice for 11 days, plus 2 oral gavage doses of 25% ethanol, were undertaken. Marked differences were found in amino acids, nucleotides, nucleosides, and related metabolites as well as a number of different lipids.

Natural variation in tolerance to sub-zero temperatures among populations of Arabidopsis lyrata ssp. petraea.

Background: Temperature is one of the most important abiotic factors limiting plant growth and productivity. Many plants exhibit cold acclimation to prepare for the likelihood of freezing as temperatures decrease towards 0 °C. The physiological mechanisms associated with enabling increased tolerance to sub-zero temperatures vary between species and genotypes.

Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis.

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani.

Complex Interplay between Sphingolipid and Sterol Metabolism Revealed by Perturbations to the Leishmania Metabolome Caused by Miltefosine.

With the World Health Organization reporting over 30,000 deaths and 200,000 to 400,000 new cases annually, visceral leishmaniasis is a serious disease affecting some of the world's poorest people. As drug resistance continues to rise, there is a huge unmet need to improve treatment. Miltefosine remains one of the main treatments for leishmaniasis, yet its mode of action (MoA) is still unknown.

Applications of Metabolomics in Cancer Studies.

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated.

Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics.

Introduction: Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

A Single In-Vial Dual Extraction Strategy for the Simultaneous Lipidomics and Proteomics Analysis of HDL and LDL Fractions.

A single in-vial dual extraction (IVDE) procedure for the subsequent analysis of lipids and proteins in the high-density lipoprotein (HDL) and low-density lipoprotein (LDL) fractions derived from the same biological sample is presented. On the basis of methyl-tert-butyl ether (MTBE) extraction, IVDE leads to the formation of three phases: a protein pellet at the bottom, an aqueous phase with polar compounds, and an ether phase with lipophilic compounds. After sample extraction, performed within a high-performance liquid chromatography vial insert, the ether phase was directly injected for lipid fingerprinting, while the protein pellet, after evaporation of the remaining sample, was used for proteomics analysis.

Looking into aqueous humor through metabolomics spectacles - exploring its metabolic characteristics in relation to myopia.

Aqueous humor is the transparent fluid found in the anterior chamber of the eye that provides the metabolic requirements to the avascular tissues surrounding it. Despite the fact that metabolomics could be a powerful tool in the characterization of this biofluid and in revealing metabolic signatures of common ocular diseases such as myopia, it has never to our knowledge previously been applied in humans. In this research a novel method for the analysis of aqueous humor is presented to show its application in the characterization of this biofluid using CE-MS.

To treat or not to treat: metabolomics reveals biomarkers for treatment indication in chronic lymphocytic leukaemia patients.

In chronic lymphocytic leukaemia (CLL), the clinical course of patients is heterogeneous. Some present an aggressive disease onset and require immediate therapy, while others remain without treatment for years. Current disease staging systems developed by Rai and Binet may be useful in forecasting patient survival time, but do not discriminate between stable and progressive forms of the disease in the early stages.

Metabolic profiling reveals potential metabolic markers associated with Hypoxia Inducible Factor-mediated signalling in hypoxic cancer cells.

Hypoxia inducible factors (HIFs) plays an important role in oxygen compromised environments and therefore in tumour survival. In this research, metabolomics has been applied to study HIFs metabolic function in two cell models: mouse hepatocellular carcinoma and human colon carcinoma, whereby the metabolism has been profiled for a range of oxygen potentials. Wild type cells have been compared to cells deficient in HIF signalling to reveal its effect on cellular metabolism under normal oxygen conditions as well as low oxygen, hypoxic and anoxic environments.

Missing value imputation strategies for metabolomics data.

The origin of missing values can be caused by different reasons and depending on these origins missing values should be considered differently and dealt with in different ways. In this research, four methods of imputation have been compared with respect to revealing their effects on the normality and variance of data, on statistical significance and on the approximation of a suitable threshold to accept missing data as truly missing. Additionally, the effects of different strategies for controlling familywise error rate or false discovery and how they work with the different strategies for missing value imputation have been evaluated.

In-source fragmentation and correlation analysis as tools for metabolite identification exemplified with CE-TOF untargeted metabolomics.

The role of non-targeted metabolomics with its discovery power is constantly growing in many different fields of science. However, its biggest advantage of uncovering the unexpected is turning into one of its biggest bottlenecks, particularly in metabolite identification. Among different methods for metabolite identification or ID confirmation, tandem MS analysis plays a very important role.

Metabolomics as a tool for drug discovery and personalised medicine. A review.

Studying the effects of drugs on the metabolome constitutes a huge part of the metabolomics discipline. Whether the approach is associated with drug discovery (altered pathways due to the disease that provide future targets and information into the mechanism of action or resistance, etc.) or pharmacometabolomics (studying the outcome of treatment), there have been many aspiring published articles in this area.

Metabolomic evaluation of Mitomycin C and rapamycin in a personalized treatment of pancreatic cancer.

In a personalized treatment designed for a patient with pancreatic cancer resistant to other treatments, the success of Mitomycin C (MMC) has been highlighted. This was revealed in a murine xenograft tumor model encompassing pancreatic adenocarcinoma cells extracted from the patient. The patient was found to exhibit a biallelic inactivation of the PALB2 gene, involved in DNA repair in addition to another mutation in the TSC2 gene that induces susceptibility of the tumor to therapeutic targets of the PI3K-mTOR pathway.

Influence of missing values substitutes on multivariate analysis of metabolomics data.

Missing values are known to be problematic for the analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data. Typically these values cover about 10%-20% of all data and can originate from various backgrounds, including analytical, computational, as well as biological. Currently, the most well known substitute for missing values is a mean imputation.

A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions.

Background: Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments.

Searching for urine biomarkers of bladder cancer recurrence using a liquid chromatography-mass spectrometry and capillary electrophoresis-mass spectrometry metabolomics approach.

The incidence and rate of recurrence of bladder cancer is high, particularly in developed countries, however current methods for diagnosis are limited to detecting high-grade tumours using often invasive methods. A panel of biomarkers to characterise tumours of different grades that could also distinguish between patients exhibiting the disease with first incidence or recurrence could be useful for bladder cancer diagnostics. In this study, potential metabolic biomarkers have been discovered through mass spectrometry based metabolomics of urine.

Metabolomics in cancer biomarker discovery: current trends and future perspectives.

Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels.