Multi Platforms Strategies and Metabolomics Approaches for the Investigation of Comprehensive Metabolite Profile in Dogs with Babesia canis Infection

Canine babesiosis is an important tick-borne disease worldwide, caused by parasites of the Babesia genus. Although the disease process primarily affects erythrocytes, it may also have multisystemic consequences. The goal of this study was to explore and characterize the serum metabolome, by identifying potential metabolites and metabolic pathways in dogs naturally infected with Babesia canis using liquid and gas chromatography coupled to mass spectrometry. The study included 12 dogs naturally infected with B. canis and 12 healthy dogs. By combining three different analytical platforms using untargeted and targeted approaches, 295 metabolites were detected. The untargeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) metabolomics approach identified 64 metabolites, the targeted UHPLC-MS/MS metabolomics approach identified 205 metabolites, and the GC-MS metabolomics approach identified 26 metabolites. Biological functions of differentially abundant metabolites indicate the involvement of various pathways in canine babesiosis including the following: glutathione metabolism; alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; cysteine and methionine metabolism; and phenylalanine, tyrosine, and tryptophan biosynthesis. This study confirmed that host–pathogen interactions could be studied by metabolomics to assess chemical changes in the host, such that the differences in serum metabolome between dogs with B. canis infection and healthy dogs can be detected with liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) methods. Our study provides novel insight into pathophysiological mechanisms of B. canis infection.     

NMR in metabolomics and natural products research: two sides of the same coin

Small molecules are central to biology, mediating critical phenomena such as metabolism, signal transduction, mating attraction, and chemical defense. The traditional categories that define small molecules, such as metabolite, secondary metabolite, pheromone, hormone, and so forth, often overlap, and a single compound can appear under more than one functional heading. Therefore, we favor a unifying term, biogenic small molecules (BSMs), to describe any small molecule from a biological source. In a similar vein, two major fields of chemical research,natural products chemistry and metabolomics, have as their goal the identification of BSMs, either as a purified active compound (natural products chemistry) or as a biomarker of a particular biological state (metabolomics). Natural products chemistry has a long tradition of sophisticated techniques that allow identification of complex BSMs, but it often fails when dealing with complex mixtures. Metabolomics thrives with mixtures and uses the power of statistical analysis to isolate the proverbial "needle from a haystack", but it is often limited in the identification of active BSMs. We argue that the two fields of natural products chemistry and metabolomics have largely overlapping objectives: the identification of structures and functions of BSMs, which in nature almost inevitably occur as complex mixtures. Nuclear magnetic resonance (NMR) spectroscopy is a central analytical technique common to most areas of BSM research. In this Account, we highlight several different NMR approaches to mixture analysis that illustrate the commonalities between traditional natural products chemistry and metabolomics. The primary focus here is two-dimensional (2D) NMR; because of space limitations, we do not discuss several other important techniques, including hyphenated methods that combine NMR with mass spectrometry and chromatography. We first describe the simplest approach of analyzing 2D NMR spectra of unfractionated mixtures to identify BSMs that are unstable to chemical isolation. We then show how the statistical method of covariance can be used to enhance the resolution of 2D NMR spectra and facilitate the semi-automated identification of individual components in a complex mixture. Comparative studies can be used with two or more samples, such as active vs inactive, diseased vs healthy, treated vs untreated, wild type vs mutant, and so on. We present two overall approaches to comparative studies: a simple but powerful method for comparing two 2D NMR spectra and a full statistical approach using multiple samples. The major bottleneck in all of these techniques is the rapid and reliable identification of unknown BSMs; the solution will require all the traditional approaches of both natural products chemistry and metabolomics as well as improved analytical methods, databases, and statistical tools.     

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.     

Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites-pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate-whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing "omics"-based, diagnostic tests to help influence therapies.     

Metabolomics as a Tool to Elucidate the Sensory,Nutritional and Safety Quality of Wheat Bread—A Review

Wheat (Triticum aestivum) is one of the most extensively cultivated and used staple crops in human nutrition, while wheat bread is annually consumed in more than nine billion kilograms over the world. Consumers’ purchase decisions on wheat bread are largely influenced by its nutritional and sensorial characteristics. In the last decades, metabolomics is considered an effective tool for elucidating the information on metabolites; however, the deep investigations on metabolites still remain a difficult and longtime action. This review gives emphasis on the achievements in wheat bread metabolomics by highlighting targeted and untargeted analyses used in this field. The metabolomics approaches are discussed in terms of quality, processing and safety of wheat and bread, while the molecular mechanisms involved in the sensorial and nutritional characteristics of wheat bread are pointed out. These aspects are of crucial importance in the context of new consumers’ demands on healthy bakery products rich in bioactive compounds but, equally, with good sensorial acceptance. Moreover, metabolomics is a potential tool for assessing the changes in nutrient composition from breeding to processing, while monitoring and understanding the transformations of metabolites with bioactive properties, as well as the formation of compounds like toxins during wheat storage.     

Metabolomics as an Important Tool for Determining the Mechanisms of Human Skeletal Muscle Deconditioning

Muscle deconditioning impairs both locomotor function and metabolic health, and is associated with reduced quality life and increased mortality rates. Despite an appreciation of the existence of phenomena such as muscle anabolic resistance, mitophagy, and insulin resistance with age and disease in humans, little is known about the mechanisms responsible for these negative traits. With the complexities surrounding these unknowns and the lack of progress to date in development of effective interventions, there is a need for alternative approaches. Metabolomics is the study of the full array of metabolites within cells or tissues, which collectively constitute the metabolome. As metabolomics allows for the assessment of the cellular metabolic state in response to physiological stimuli, any chronic change in the metabolome is likely to reflect adaptation in the physiological phenotype of an organism. This, therefore, provides a holistic and unbiased approach that could be applied to potentially uncover important novel facets in the pathophysiology of muscle decline in ageing and disease, as well as identifying prognostic markers of those at risk of decline. This review will aim to highlight the current knowledge and potential impact of metabolomics in the study of muscle mass loss and deconditioning in humans and will highlight key areas for future research.     

An Overview of Near Infrared Spectroscopy and Its Applications in the Detection of Genetically Modified Organisms

Near-infrared spectroscopy (NIRS) has become a more popular approach for quantitative and qualitative analysis of feeds, foods and medicine in conjunction with an arsenal of chemometric tools. This was the foundation for the increased importance of NIRS in other fields, like genetics and transgenic monitoring. A considerable number of studies have utilized NIRS for the effective identification and discrimination of plants and foods, especially for the identification of genetically modified crops. Few previous reviews have elaborated on the applications of NIRS in agriculture and food, but there is no comprehensive review that compares the use of NIRS in the detection of genetically modified organisms (GMOs). This is particularly important because, in comparison to previous technologies such as PCR and ELISA, NIRS offers several advantages, such as speed (eliminating time-consuming procedures), non-destructive/non-invasive analysis, and is inexpensive in terms of cost and maintenance. More importantly, this technique has the potential to measure multiple quality components in GMOs with reliable accuracy. In this review, we brief about the fundamentals and versatile applications of NIRS for the effective identification of GMOs in the agricultural and food systems.     

The life sciences mass spectrometry research unit

The Life Sciences Mass Spectrometry (LSMS) research unit focuses on the development of novel analytical workflows based on innovative mass spectrometric and software tools for the analysis of low molecular weight compounds, peptides and proteins in complex biological matrices. The present article summarizes some of the recent work of the unit: i) the application of matrix-assisted laser desorption/ionization (MALDI) for mass spectrometry imaging (MSI) of drug of abuse in hair, ii) the use of high resolution mass spectrometry for simultaneous qualitative/quantitative analysis in drug metabolism and metabolomics, and iii) the absolute quantitation of proteins by mass spectrometry using the selected reaction monitoring mode.     

Modeling electrospun nanofibers: An overview from theoretical,empirical, and numerical approaches

Electrospinning is a sophisticated material process to manufacture well-tailored nanofibers for fiber reinforcement, tissue scaffolding, drug delivery, nanofiltration, cosmetics, and protective clothing. Abundant information and knowledge are reported from experimental observation and material characterization to determine and control nanofiber properties. However, experimental results need to be interpreted systematically through theoretical, analytical, and numerical models for the optimization of fiber diameter and alignment, porosity, and estimation of mechanical properties of electrospun nanofibers. This paper provides a comprehensive review on current status of modeling approaches used in electrospun nanofibers to elucidate their systematic research approaches including material fabrication, experimental characterization, and modeling.     

New approaches for studying the chemical diversity of natural resources and the bioactivity of their constituents

Natural products (NPs) have historically been an important source of lead molecules in drug discovery. However, the interest that the pharmaceutical industry has had in NPs has declined in part because of the lack of compatibility of traditional natural-product extract libraries with high-throughput screenings and the low hit rate. Furthermore, in contrast to the synthetic libraries, compounds from natural sources are likely to have complex structures which slow down the identification process and contribute to problems related to supply and manufacturing. In this paper, we summarise some of the strategies that are being developed in our research unit to address these issues. On one hand, differential screening strategies were established with the aim of identifying dynamically induced NPs from silent biosynthetic pathways in plants and fungi that had been exposed to different stress situations. On the other hand, high-resolution HPLC techniques were optimised for biological and chemical profiling of crude extracts. This led to an integrated platform for rapid and efficient identification of new drug-leads and biomarkers of interest that were based on miniaturised technological approaches and metabolomics.     

Comparison of Three Approaches to Model Particle Penetration Coefficient through a Single Straight Crack in a Building Envelope

In this study, we present three approaches to predict particle penetration coefficients through a single straight crack in building envelops. The three approaches are an analytical approach, an Eulerian approach, and a Lagrangian approach, respectively. The particle penetration coefficient through an idealized straight crack (smooth inner surfaces) and a strand board crack (rough inner surfaces) were modeled by the three presented approaches. The calculated results were compared with the literature results. The comparison shows that for the idealized smooth crack, the modeled results by the Eulerian approach match the experiments best for the entire range of particle sizes studied among the three approaches. The predicted results by the analytical approach also match the experiments reasonable well. Results modeled by the Lagrangian approach are less satisfied for fine particles (d _p < 0.1 μm). Overall, all the three approaches agree well with the experiments for particle sizes ranging from 0.4–1.2 μm. For cracks with rough inner surfaces, the results agree better with the measurements for all the three approaches by adjusting the boundary conditions to incorporate the “intercept” effect of roughness on particle deposition in the cracks.     

FUNCTIONAL GENOMICS AND INSECT CHEMICAL ECOLOGY

High-throughput molecular techniques (i.e., genomics) are now beginning to make their way into chemical ecology research. Pioneering functional genomics studies have made significant contributions to our understanding of insect pheromone production, reception, behavior, and insect–plant interactions. Much of this research involves nonmodel organisms, including the honey bee, silkworm, and bark beetles, underscoring that researchers need not be restricted to traditional model organisms for high-throughput research. Furthermore, the technology can reveal physiological interactions that might otherwise be missed by more traditional molecular approaches. Functional genomics should become more widely used as researchers appreciate the wealth of information this potent approach can supply. This review concentrates on a summary of available technologies for functional genomics as they may be applied by chemical ecologists studying insects. Allied technologies (proteomics and metabolomics) are introduced briefly toward the end in the context of future applications.     

Serum Metabolomic and Lipidomic Profiling Reveals Novel Biomarkers of Efficacy for Benfotiamine in Alzheimer’s Disease

Serum metabolomics and lipidomics are powerful approaches for discovering unique biomarkers in various diseases and associated therapeutics and for revealing metabolic mechanisms of both. Treatment with Benfotiamine (BFT), a thiamine prodrug, for one year produced encouraging results for patients with mild cognitive impairment and mild Alzheimer’s disease (AD). In this study, a parallel metabolomics and lipidomics approach was applied for the first exploratory investigation on the serum metabolome and lipidome of patients treated with BFT. A total of 315 unique metabolites and 417 lipids species were confidently identified and relatively quantified. Rigorous statistical analyses revealed significant differences between the placebo and BFT treatment groups in 25 metabolites, including thiamine, tyrosine, tryptophan, lysine, and 22 lipid species, mostly belonging to phosphatidylcholines. Additionally, 10 of 11 metabolites and 14 of 15 lipid species reported in previous literature to follow AD progression changed in the opposite direction to those reported to reflect AD progression. Enrichment and pathway analyses show that significantly altered metabolites by BFT are involved in glucose metabolism and biosynthesis of aromatic amino acids. Our study discovered that multiple novel biomarkers and multiple mechanisms that may underlie the benefit of BFT are potential therapeutic targets in AD and should be validated in studies with larger sample sizes.     

INSTANTANEOUS RESPONSE OF PULVERIZED COAL PARTICLES TO FLUCTUATING TEMPERATURE IN A HOT GAS FLOW

The instantaneous temperature response of pulverized coal particles to fluctuating gas temperature in a hot airflow is investigated. The particle relaxation time for temperature is analyzed. Both numerical and analytical approaches are adopted to solve the instantaneous particle energy equation. The results obtained by the two approaches are quite close. The gas temperature fluctuation has an obvious influence on the particle instantaneous temperature, especially for particles with relatively small diameters. The effects of fluctuation intensity and frequency of the gas temperature, as well as particle Reynolds number, on the particle instantaneous temperature response are delineated. The present study provides a basis for further exploring the impacts of gas turbulence on the particle reactive behaviors.     

INSTANTANEOUS RESPONSE OF PULVERIZED COAL PARTICLES TO FLUCTUATING TEMPERATURE IN A HOT GAS FLOW

The instantaneous temperature response of pulverized coal particles to fluctuating gas temperature in a hot airflow is investigated. The particle relaxation time for temperature is analyzed. Both numerical and analytical approaches are adopted to solve the instantaneous particle energy equation. The results obtained by the two approaches are quite close. The gas temperature fluctuation has an obvious influence on the particle instantaneous temperature, especially for particles with relatively small diameters. The effects of fluctuation intensity and frequency of the gas temperature, as well as particle Reynolds number, on the particle instantaneous temperature response are delineated. The present study provides a basis for further exploring the impacts of gas turbulence on the particle reactive behaviors.