Lipidomics in drug discovery

Saturated Hydroxy Fatty Acids Exhibit a Cell Growth Inhibitory Activity and Suppress the Cytokine-Induced β-Cell Apoptosis

The field of bioactive lipids is ever expanding with discoveries of novel lipid molecules that promote human health. Adopting a lipidomic-assisted approach, two new families of previously unrecognized saturated hydroxy fatty acids (SHFAs), namely, hydroxystearic and hydroxypalmitic acids, consisting of isomers with the hydroxyl group at different positions, were identified in milk. Among the various regio-isomers synthesized, those carrying the hydroxyl at the 7- and 9-positions presented growth inhibitory activities against various human cancer cell lines, including A549, Caco-2, and SF268 cells. In addition, 7- and 9-hydroxystearic acids were able to suppress β-cell apoptosis induced by proinflammatory cytokines, increasing the possibility that they can be beneficial in countering autoimmune diseases, such as type 1 diabetes. 7-(R)-Hydroxystearic acid exhibited the highest potency both in cell growth inhibition and in suppressing β-cell death. We propose that such naturally occurring SHFAs may play a role in the promotion and protection of human health.

A Novel Lipidomics-Based Approach to Evaluating the Risk of Clinical Hepatotoxicity Potential of Drugs in 3D Human Microtissues

The importance of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis is expected to grow substantially due to recent failures in detecting severe toxicity issues of new chemical entities during preclinical/clinical development. Traditionally, safety risk assessment studies for humans have been conducted in animals during advanced preclinical or clinical phase of drug development. However, potential drug toxicity in humans now needs to be detected in the drug discovery process as soon as possible without reliance on animal studies. The "omics", such as genomics, proteomics, and metabolomics, have recently entered pharmaceutical research in both drug discovery and drug development, but to the best of our knowledge, no applications in high-throughput safety risk assessment have been attempted so far. This paper reports an innovative method to anticipate adverse drug effects in an early discovery phase based on lipid fingerprints using human three-dimensional microtissues. The risk of clinical hepatotoxicity potential was evaluated for a data set of 22 drugs belonging to five different therapeutic chemical classes and with various drug-induced liver injury effect. The treatment of microtissues with repeated doses of each drug allowed collecting lipid fingerprints for five time points (2, 4, 7, 9, and 11 days), and multivariate statistical analysis was applied to search for correlations with the hepatotoxic effect. The method allowed clustering of the drugs based on their hepatotoxic effect, and the observed lipid impairments for a number of drugs was confirmed by literature sources. Compared to traditional screening methods, here multiple interconnected variables (lipids) are measured simultaneously, providing a snapshot of the cellular status from the lipid perspective at a molecular level. Applied here to hepatotoxicity, the proposed workflow can be applied to several tissues, being tridimensional microtissues from various origins.

Antibiotic Discovery: Where Have We Come from, Where Do We Go?

Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

Systems Biology to Support Nanomaterial Grouping

The assessment of potential health risks of engineered nanomaterials (ENMs) is a challenging task due to the high number and great variety of already existing and newly emerging ENMs. Reliable grouping or categorization of ENMs with respect to hazards could help to facilitate prioritization and decision making for regulatory purposes. The development of grouping criteria, however, requires a broad and comprehensive data basis. A promising platform addressing this challenge is the systems biology approach. The different areas of systems biology, most prominently transcriptomics, proteomics and metabolomics, each of which provide a wealth of data that can be used to reveal novel biomarkers and biological pathways involved in the mode-of-action of ENMs. Combining such data with classical toxicological data would enable a more comprehensive understanding and hence might lead to more powerful and reliable prediction models. Physico-chemical data provide crucial information on the ENMs and need to be integrated, too. Overall statistical analysis should reveal robust grouping and categorization criteria and may ultimately help to identify meaningful biomarkers and biological pathways that sufficiently characterize the corresponding ENM subgroups. This chapter aims to give an overview on the different systems biology technologies and their current applications in the field of nanotoxicology, as well as to identify the existing challenges.

Lipidomic analyses in epidemiology

Clinical lipid measurements have been the mainstay of risk assessment for chronic disease since the Framingham study commenced over 60 years ago. Thousands of subsequent epidemiological studies have provided much insight into the relationship between plasma lipid profiles, health and disease. However, the human lipidome consists of thousands of individual lipid species, and current lipidomic technology presents us with an unprecedented opportunity to measure lipid phenotypes, representing genomic, metabolic, diet and lifestyle-related exposures, in large epidemiological studies. The number of epidemiological studies using lipidomic profiling is increasing and has the potential to provide improved biological and clinical insight into human disease. In this review, we discuss current lipidomic technologies, epidemiological studies using these technologies and the statistical approaches used in the analysis of the resulting data. We highlight the potential of integrating genomic and lipidomic datasets and discuss the future opportunities and challenges in this emerging field.

Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Lipidomics is a newly emerged discipline that studies cellular lipids on a large scale based on analytical chemistry principles and technological tools, particularly mass spectrometry. Recently, techniques have greatly advanced and novel applications of lipidomics in the biomedical sciences have emerged. This review provides a timely update on these aspects. After briefly introducing the lipidomics discipline, we compare mass spectrometry-based techniques for analysis of lipids and summarize very recent applications of lipidomics in health and disease. Finally, we discuss the status of the field, future directions, and advantages and limitations of the field.

A Lipidomic and Metabolomic Serum Signature from Nonhuman Primates Exposed to Ionizing Radiation

INTRODUCTION

Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a "snapshot" of potential cellular damage.

OBJECTIVES

The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR).

METHODS

Serum sample lipids and metabolites were extracted using a biphasic liquid-liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode.

RESULTS

Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation.

CONCLUSIONS

This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.

Stimulated Raman scattering microscopy: an emerging tool for drug discovery

Optical microscopy techniques have emerged as a cornerstone of biomedical research, capable of probing the cellular functions of a vast range of substrates, whilst being minimally invasive to the cells or tissues of interest. Incorporating biological imaging into the early stages of the drug discovery process can provide invaluable information about drug activity within complex disease models. Spontaneous Raman spectroscopy has been widely used as a platform for the study of cells and their components based on chemical composition; but slow acquisition rates, poor resolution and a lack of sensitivity have hampered further development. A new generation of stimulated Raman techniques is emerging which allows the imaging of cells, tissues and organisms at faster acquisition speeds, and with greater resolution and sensitivity than previously possible. This review focuses on the development of stimulated Raman scattering (SRS), and covers the use of bioorthogonal tags to enhance sample detection, and recent applications of both spontaneous Raman and SRS as novel imaging platforms to facilitate the drug discovery process.

High resolution ion mobility-mass spectrometry for separation and identification of isomeric lipids

Lipidomics is a particularly difficult analytical challenge due to the number and importance of isomeric species that are known or postulated in biological samples. Current separation and identification techniques are too often insufficiently powerful, slow or ambiguous. High resolution, low field ion mobility coupled to mass spectrometry is shown here to have sufficient performance to represent a new alternative for lipidomics. For the first time, drift-tube ion mobility separation of lipid isomers that differ only in position of the acyl chain, position of the double bond or double bond geometry is demonstrated. Differences in collision cross sections of less than 1% are sufficient for baseline separation. The same level of performance is maintained in complex biological mixtures. More than 130 high-precision reduced mobility and collision cross section values were also determined for a range of lipids. Such data can be the basis of a new lipidomics workflow, as the appropriate libraries are developed.

Glycerophospholipid Profiles of Bats with White-Nose Syndrome

Pseudogymnoascus destructans is an ascomycetous fungus responsible for the disease dubbed white-nose syndrome (WNS) and massive mortalities of cave-dwelling bats. The fungus infects bat epidermal tissue, causing damage to integumentary cells and pilosebaceous units. Differences in epidermal lipid composition caused by P. destructans infection could have drastic consequences for a variety of physiological functions, including innate immune efficiency and water retention. While bat surface lipid and stratum corneum lipid composition have been described, the differences in epidermal lipid content between healthy tissue and P. destructans-infected tissue have not been documented. In this study, we analyzed the effect of wing damage from P. destructans infection on the epidermal polar lipid composition (glycerophospholipids [GPs] and sphingomyelin) of little brown bats (Myotis lucifugus). We hypothesized that infection would lead to lower levels of total lipid or higher oxidized lipid product proportions. Polar lipids from three damaged and three healthy wing samples were profiled by electrospray ionization tandem mass spectrometry. We found lower total broad lipid levels in damaged tissue, specifically ether-linked phospholipids, lysophospholipids, phosphatidylcholine, and phosphatidylethanolamine. Thirteen individual GP species from four broad GP classes were present in higher amounts in healthy tissue. Six unsaturated GP species were absent in damaged tissue. Our results confirm that P. destructans infection leads to altered lipid profiles. Clinical signs of WNS may include lower lipid levels and lower proportions of unsaturated lipids due to cellular and glandular damage.

The antihyperlipidemic effect of Fu-Ling-Pi is associated with abnormal fatty acid metabolism as assessed by UPLC-HDMS-based lipidomics

The surface layer ofPoria cocos(SLPC), a traditional Chinese medicine, has been commonly used for diuretic and antihyperlipidemia in Asia.

Systems toxicology: from basic research to risk assessment

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.