Lipidomics Reveals Changes in Metabolism, Indicative of Anesthetic

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Review

Lipidomics reveals changes in metabolism, indicative of anesthetic-induced neurotoxicity in developing brains Chunyan Wang, Cheng Wang, Fang Liu, Shuo Rainosek, Tucker A Patterson, William Slikker, and Xianlin Han Chem. Res. Toxicol., Just Accepted Manuscript • DOI: 10.1021/acs.chemrestox.8b00186 • Publication Date (Web): 22 Aug 2018 Downloaded from http://pubs.acs.org on August 23, 2018

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Chemical Research in Toxicology

Lipidomics reveals changes in metabolism, indicative of anesthetic-induced neurotoxicity in developing brains

Chunyan Wang†, Cheng Wang‡, Fang Liu‡, Shuo Rainosek^, Tucker A. Patterson§, William Slikker, Jr.§ and Xianlin Han†,#,*

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Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, TX 78229, USA ‡ Division of Neurotoxicology, National Center for Toxicological Research/Food and Drug Administration, Jefferson, AR 72079, USA ^ Department of Anesthesiology, Central Arkansas Veterans Health System, 4300 W 7th Street, VA 704-110, Little Rock AR 72205, USA § Office of the Director, National Center for Toxicological Research/Food and Drug Administration, Jefferson, AR 72079, USA # Department of Medicine, University of Texas Health Science Center at San Antonio, TX 78229, USA

*To whom correspondence should be addressed: [email protected]

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TOC Graphic

Anesthetic exposure

Mechanism/Biomarkers Lipidomics Analysis

Neonatal Animal Model Neurotoxicity

Brain/Serum Samples

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Abstract Numerous studies have demonstrated that treatment with high dose anesthetics for a prolonged duration induces brain injury in infants. However, whether anesthetic treatment leading to neurotoxicity is associated with alterations in lipid metabolism and homeostasis is still unclear. This review first outlines the lipidomics tools for analysis of lipid molecular species which can inform alterations in lipid species after anesthetic exposure. Then, the available data indicating anesthetics cause changes in lipid profiles in the brain and serum of infant monkeys in preclinical studies are summarized, and the potential mechanisms leading to the altered lipid metabolism and their association with anesthetic-induced brain injury are also discussed. Finally, whether lipid changes identified in serum of infant monkeys can serve as indicators for the early detection of anesthetic-induced brain injury is described. We believe extensive studies on alterations in lipids after exposure to anesthetics will allow us to better understand anestheticinduced neurotoxicity, unravel its underlying biochemical mechanisms, and develop powerful biomarkers for early detection/monitoring of the toxicity.

Key words: Anesthesia, anesthetic-induced neurotoxicity, lipid homeostasis, lipid metabolism, lipidomics, sevoflurane, shotgun lipidomics

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1. Introduction Numerous preclinical studies with different models, from mice to nonhuman primates, have showed the existence of developing brain injury after treatment with general anesthetics in high doses and/or for a prolonged duration1-9. These studies clearly raised concerns regarding the utility of anesthetics in infants, but the molecular mechanisms leading to the observed neuronal injury remain elusive. In addition, marker(s) for the clinical detection of brain injury, whether associated with general anesthetic exposure, are needed. To this end, studying lipid metabolism and identifying the changes of lipid homeostasis could be effective ways to reveal the molecular mechanisms associated with lipids and identify the changed lipids as biomarkers, respectively. This is largely due to the crucial roles that lipids play and the broad networks that lipids are involved as outlined in the following paragraphs. Lipids are very complex. Thousands of lipid species are present in biological samples10-12. This complexity is mainly due to the presence of a variety of aliphatic chains composed of different numbers of carbon atoms, and different numbers and locations of double bonds, etc. However, these lipid species can be classified into a limited number of classes and subclasses based on their different polar head groups and the linkages of the aliphatic chains to the head groups, respectively13. The complexities are also due to other factors. For instance, individual lipid species and their content vary from species, cell types, cellular organelles, subcellular membranes, and membrane microdomains (e.g., caveola and/or rafts)14-16. Moreover, environmental changes17 or cell growth18-20 can dynamically influence the complexity of cellular lipid molecular species. Furthermore, lipids become further complex when they are conjugated with carbohydrates and

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peptides as cellular processes. These conjugated lipids are known as lipopolysaccharides21 and lipopeptides22, respectively. Lipids involve many essential cellular functions in an organism, such as constituting cellular membranes and lipoprotein cargoes, serving as an optimal matrix for transmembrane proteins, providing fuel storage and/or supplement, and regulating cell growth and survival as signaling molecules23. Moreover, with the development of genomics, proteomics, and molecular biology, more and more vital functions of lipids are being discovered, including anti-diabetes and anti-inflammatory effects, regulation of mitochondrial ATP release, etc.24-25. Accumulated evidence demonstrates that aberrant lipid metabolism and homeostasis are involved in the pathogenesis of many major human diseases at the era of post-industrialization (e.g., obesity and diabetes, cardiovascular disease, cancer, neurodegenerative disorders, and autoimmune diseases)23, 26-30. Therefore, determination of lipid homeostasis under different physiological and/or pathological conditions could assist us in understanding the underlying mechanism(s) of diseases, discovering potential biomarkers for early diagnosis, and developing novel drug targets. The brain represents one of the organs containing the highest ratio of lipid-to-protein masses (next to the adipose tissue) and the brain lipidome is comprised of the most complex lipid classes and molecular species31. Therefore, it is anticipated that lipid metabolism and homeostasis are changed, and lipid signaling is involved in cellular processes after any insult leading to brain injury (e.g., anesthetic-induced neurotoxicity). Measurements of alterations in cellular lipid molecular species should provide deep insights into the molecular mechanisms leading to brain injury and molecular markers for monitoring the injury if changed lipids can be determined from peripheral tissue biopsies (e.g., muscle or sciatic nerve) or body fluid (e.g.,

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plasma, urine, saliva, etc.). This is a perfect case of lipidomics as examined in the following section. Collectively, this review first gives an overview of lipidomics and lipidomics tools used in the field. Then, we summarize the available data from the studies on anesthetic-induced alterations of lipid profiles in brain and serum samples of infant monkeys treated with an anesthetic (i.e., sevoflurane). From the data, potential mechanisms leading to the altered lipid metabolism and their association with anesthetic-induced brain injury are discussed and serum lipids serving as potential markers for early monitoring of anesthetic-induced neurotoxicity is also described. It should be noted that only available lipidomics studies on anesthetic-induced neurotoxicity are from our laboratory and thus, only these studies are reviewed herein. To date, significant progresses have been made in the techniques including calcium imaging32 and molecular imaging8, 33 that have revolutionized our capability of studying anesthetic-induced neuronal injury. Therefore, the utilization of highly relevant preclinical dynamic imaging approaches8, 33, when combined with specific lipid biomarkers, may provide tools to bridge the gap between preclinical and clinical (human conditions) research. 2. Lipidomics and Lipidomics Tools 2.1. Lipidomics The entire spectrum of cellular lipids aforementioned has been termed a lipidome34. Similar to other “omics”, studying lipidomes in a large scale utilizing analytical chemistry principles and technologies has been termed as lipidomics, which appeared with different definitions17, 35, demonstrations of technologies17, 36, and biological applications17, 37-38 in 2003. The emergence of lipidomics is largely catalyzed by the recognition that lipid metabolism between lipid classes, subclasses, and molecular species is interwoven11 and should be studied in a systems biology 6


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approach39. The emergence of this emerging discipline is also facilitated by the advancement in necessary technologies for analysis of lipidomes, particularly the development of mass spectrometry. The major aims of lipidomics are: 1) to identify and quantify the changes of cellular lipids (thus understanding the altered metabolism and homeostasis of lipid classes and molecular species) after perturbation or during the life cycle, 2) to investigate the roles and interactions of the involved lipids, and 3) to delineate the biochemical mechanism underpinning alterations in lipids under patho(physio)logical conditions17. The latter task of lipidomics connects lipid metabolism to biology and other omics40-41, which is very important for translational research. Although the discipline of lipidomics has evolved over the last 15 yrs17, the broad coverage of lipidomics studies has been well demonstrated and documented in recent review articles23, 40, 42-47.

2.2. Developed Analytical Workflows for Lipidomics 2.2.1. LC-MS Based Approaches Many modern analytical technologies, such as mass spectrometry (MS), nuclear magnetic resonance spectroscopy, and microfluidic devices have been used to investigate lipid metabolism, signaling, homeostasis, and interactions48. Among these technologies, electrospray ionization mass spectrometry (ESI-MS)-based approaches are the most promising and have been shown to be the most powerful for lipidomics due to the sensitivity and specificity of ESI-MS (see our recent reviews23, 49 on the topic). Due to recent advances in ultrahigh resolution/accuracy mass spectrometry, development of lipidomics with respect to the coverage and high throughput of lipid analysis has been accomplished50. Generally, depending on whether chromatographic separation is coupled to an MS instrument, the MS-based lipidomics approaches can be classified into two major categories: 1) 7



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liquid chromatography (LC)-MS based lipidomics, in which lipid concentration after LC separation is constantly changing, and 2) direct infusion-based lipidomics (which is also termed shotgun lipidomics51), where the lipid solution is directly delivered into an MS ion source continuously and its concentration is kept constant. Complex lipid mixtures are separated based on chemistry and/or physics of lipids before entering an MS instrument in all LC-based approaches. For instance, isobaric species of lipids can be resolved and elution time can be exploited for identification of these species. A mobile phase passing through a type of column packed with a stationary phase is applied in the LC-MS system. Many types of columns applying various physiochemical features are developed. Considering the hydrophobic nature of lipids, reversed-phase chromatography with a C18 column has been commonly used, particularly after isolation of individual lipid class52-53. Once lipids are loaded, the stationary phase of a C18 column interacts with lipids which are eluted based on their partitioning between the stationary and mobile phases. Thus, maximal separation of lipid species can be achieved through formulating mobile phase composition or using a gradient of different solvents46, 54. Other stationary phases, such as normal-phase and hydrophilic interaction columns (HILIC), are also commonly applied in LC-MS based lipidomics. These types of columns exploit polar stationary phases, thus polar lipids are more strongly interacted with the stationary phase. The polarity of lipid head groups dominates elution on HILIC columns55-56. Thus, different lipid classes can be efficiently resolved with a HILIC column, but not with reverse phase columns. In fact, separation of lipids with using both normal phase and HILIC columns is highly orthogonal to the reverse phase mode, leading to very different elution profiles55. This feature allows scientists to develop two-dimensional LC methods for lipidomics57-58, which greatly improves 8


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the confidence in analysis of lipid species. This approach is very useful for comprehensive characterization of lipid mixtures. Recently, utilization of supercritical fluid chromatography has demonstrated great promise as an alternative choice for LC-MS analysis of lipidomes59. CO2 is the most common supercritical fluid employed in this type of application with methanol as a mobile phase60. It has been shown that fast resolution of lipid classes can be readily achieved by applying supercritical fluid chromatography61-62. Thus, it should be useful for high-throughput lipidomics. The choices of LC settings, including the type of columns, the constitution or gradient of mobile phases, and running time, largely depend on the goal of the experiment. It should be noted that the ion responses of analytes could be affected by the solvent composition eluting from the column. This makes accurate quantitation challenging if an analyte and its internal standard elute with a different solvent composition63. 2.2.2. Shotgun Lipidomics Direct infusion-based approaches were originally employed to eliminate alterations in concentration, chromatographic anomalies, and ion-pairing alterations in order to efficiently analyze lipid species in the early 1990’s64-67. Around 2004, the approaches developed following direct infusion have been separately called “shotgun lipidomics” by Han and Gross68 and Ejsing et al.69. Since then shotgun lipidomics has become one of the broadly-employed technologies in lipidomics, particularly in a high-throughput fashion51, 68, 70-75. Shotgun lipidomics possesses numerous advantages over other lipidomics approaches. Its key feature is that the lipid concentration during analysis is kept constant. Thus, many factors which may complicate lipidomics analysis of individual lipid species can be eliminated /minimized under constant concentration conditions. First, interactions between lipid species of 9



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any classes are maintained constant under those conditions. Thus, the attribution of each lipid molecule to the total ion current in an ESI source keeps unchanged so that an unaffected ratio between ion peaks of lipid species of any class can be maintained regardless of changes in ionization conditions76. This feature is crucial for quantification of lipid species of a class with a selected internal standard of the class. Such a constant ratio can be maintained under various experimental conditions, with different type of MS instruments, and in different laboratories if a lipid concentration can be kept unchanged73 and in the low region to avoid occurrence of lipid aggregation77. Also maintaining a constant lipid concentration makes any ion suppression between lipid classes unvaried and any potential lipid aggregation readily controlled or eliminated in shotgun lipidomics. The latter is a big concern for accurate quantification of lipid species77. Finally, this feature allows researchers to have much longer time to improve the mass spectral signals, to conduct a variety of MS/MS analyses in various modes, such as precursor-ion scan (PIS), neutral loss scan (NLS), and multi-stage tandem MS analyses, and to ramp a variety of instrumental variables (e.g., collision energies, collision gas pressure, ion-mobility parameters, etc.). Such experiments are unable to be readily conducted with LC-MS based approaches, for which concentration changes and time constraints are present during chromatographic elution. A full mass spectrum in the survey scan mode can be readily acquired in shotgun lipidomics to display all the molecular ions of a lipid class of interest. This is another major feature of shotgun lipidomics and important for analysis of lipids of a class. This is because the feature makes these lipid species easily visualized and allows researchers to readily perform PIS and/or NLS for analysis of a lipid class or a category of lipid classes for their identification and quantification since both PIS and NLS separately identify individual building blocks of these lipids without time constraints12, 51. We have previously summarized some building blocks of 10


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many lipid classes, which can be analyzed by PIS and/or NLS12. Moreover, acquisition of the full mass spectrum of a lipid class makes the lipid species of the class easily quantified in direct comparison of ion peak intensities with their selected internal standard(s) (i.e., ratiometric comparison) after 13C deisotoping68. Based on these unique features, at least three varieties of shotgun lipidomics have been advanced and broadly applied for analysis of cellular lipidomes, which include MS/MS-based shotgun lipidomics78-84, high mass accuracy/resolution instrument-based shotgun lipidomics71, 85, and multi-dimensional MS-based shotgun lipidomics (MDMS-SL)12, 51, 68, 73-75. Because

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MDMS-SL was used in the studies reviewed below, this platform is discussed in more detail. In MDMS-SL the differential charge properties of varied lipid classes (the head groups of polar lipid classes mainly contribute to the charge properties) are used to selectively ionize a certain category of lipid classes under different experimental conditions to achieve separation of different lipid classes in the ion source (which has been termed as “intrasource separation”)76. Then, mapping of the building blocks of a lipid class or a category of lipid classes which constitutes a 2D mass spectrum51, allows researchers to identify all the lipid species of the class or the category of lipid classes including aliphatic chains (i.e., structural isomers), chain linkages (i.e., subclasses), chain positions (i.e., regioisomers), etc.12. MDMS-SL enables us to identify and quantify all molecular species of lipids present in all kinds of biological samples in a quantitative and unbiased manner. Notably, the analyses can be achieved with a small amount of biological material (e.g., 10-50 mg tissue, 106 cells, 200 µl body fluid) in a relatively high-throughput manner. After multiplexed lipid extraction of biological samples or facile derivatization, lipid class-selective ionization in the positive- and negative-ion modes under a variety of acidic/basic conditions (i.e., intrasource separation76) and 11



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subsequent MDMS analysis12, quantitative analysis of individual molecular species of all major and many minor lipid classes that constitute the cellular lipidome can be accomplished. Overall, these analyzed lipid species account for >95% of the total lipid masses and thousands of molecular species12. MDMS-SL has been widely applied for preclinical and translational studies on neurological diseases and models38, 93-99. Specifically, shotgun lipidomics has revealed that sulfatide reduction is present at the earliest clinical stages of Alzheimer’s disease (AD)95 and even in the preclinical stage of AD98. CSF sulfatide levels are also lower in very early stages of AD relative to controls99. Sulfatide levels in postmortem brain samples from individuals with other types of neurodegenerative diseases (e.g., Parkinson’s dementia, Lewy bodies dementia, and multiple sclerosis) have also been examined38, and the studies showed that sulfatide reduction is specific to AD. It has also been demonstrated that sulfatide deficiency occurs in AD mouse models96. These studies suggest that sulfatide has a major impact on AD pathogenesis100101

. Recently, MDMS-SL has been employed to measure the contents of over 800 lipid species

present in plasma samples from 26 AD patients and 26 cognitively normal controls in a nontargeted approach97. It has been demonstrated that the levels of sphingolipids are significantly changed in plasma samples from patients with AD. Of the 33 sphingomyelin species determined, 8 species, particularly those containing long aliphatic chains such as 22 and 24 carbon atoms, are significantly lower (p < 0.05) in AD individuals compared to normal cognitive controls. In practice, automation with direct infusion can be accomplished by employing robotic nanoflow ion sources (e.g., NanoMate device) which can also dramatically reduce the sample size and cross-contamination71, 102. A detail protocol for use of the NanoMate device has been previously described71, 103. Under the experimental conditions, infusing 5 to 10 µL sample 12


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solution is sufficient to facilitate the analysis with a stable spray for nearly an hour. Thus, high reproducibility, sequential runs of a series of requested mass spectra, and accurate quantitation can be readily accomplished with the workflow71, 102. 3. Lipid Changes in the Developing Brain after Treatment with Anesthetics Lipids are important cellular constituents and play numerous essential roles in biological functions. Small perturbations of nervous systems can result in alterations in lipid contents and/or composition in signaling transduction, metabolism pathways, and cellular structures. Numerous previous lipidomics studies104-114 have shown significant lipid changes present in multiple neurodegenerative diseases, suggesting that lipid changes happen at early time points of pathogenesis and may serve as more effective indicators of brain injury after exposure to anesthetics than other neurotoxicological measurements. Importantly, Alterations in the content or composition of lipids in the developing brain could significantly affect the cellular structure and function, and thus viability115. This is consistent with that changed lipid levels are present at the earliest diagnostic stages of several neurodegenerative disorders aforementioned, suggesting that aberrant lipid metabolism and homeostasis greatly impact on neuronal injury. One of our recent studies4 has revealed that significant lipid changes are present in the brain of infant monkeys after prolonged treatment with anesthetic (i.e., sevoflurane). Specifically, the contents of phosphatidylserine, ethanolamine glycerophospholipid, and phosphatidylglycerol are significantly decreased in the brain of monkeys after prolonged exposure to sevoflurane4. This finding is consistent with the data obtained from DNA microarray analysis and neuronal injury monitoring. We found that changes of phosphatidylserine (a critical element associated with cellular apoptosis and a class of signaling lipids mainly reside on mitochondrial and cytoplasmic membranes116-119), ethanolamine glycerophospholipid (one class 13



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of the most abundant mitochondrial phospholipids120), and phosphatidylglycerol (present in mitochondrial membranes and serves as a substrate for biosynthesis of cardiolipin121) clearly indicate that not only altered neuronal membrane phospholipid metabolism and content occur, but also mitochondria are a nervous system target of sevoflurane-induced neurotoxicity in infant monkeys. In contrast to the decreased levels of membrane phospholipids, the amounts of 4hydroxynenoal and lysophosphatidylethanolamines are markedly increased in infant monkeys after prolonged sevoflurane exposure4. 4-Hydroxynenoal is an aldehydic product of cellular lipid peroxidation, is toxic to brain mitochondrial complexes II and III, and involves signaling propagation of oxidative stress122. Increased lysophosphatidylethanolamines are likely due to the oxidative degradation of plasmalogens (a subclass of ethanolamine glycerophospholipid) which play an active role in anti-oxidation123-124. These observations strongly suggest that generation of reactive oxygen species might be a potential mechanism underlying anesthetic-induced neuronal cell death9. Disruption of membrane integrity in the nerve systems can lead to cytokine secretion from microglia and cause neuronal injury in many neurodegenerative diseases125. Cytokines play important signaling roles in many biological processes and their malfunction can result in various disorders126-128. Our study has also shown that the amounts of interleukin (IL)-17, macrophage inflammatory protein (MIP)-1α, epidermal growth factor (EGF) and monokine induced by gamma interferon (MIG) significantly increased in the brains of infant monkeys exposure to sevoflurane. The increased concentrations of IL-17, MIP and MIG indicate that sevoflurane treatment stimulates an inflammatory process in the central nervous system (CNS). Notably, increased brain injury as detected by Fluoro-Jade C is consistent with the elevated 14


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cytokine content determined4. Fluoro-Jade C is an anionic fluorescent probe that can detect degenerating neurons in brain slides129. Taken together, increased reactive oxygen species generation, changed lipid content, and elevated cytokine secretion or leakage may be critical in the development of anesthetic-induced neurotoxicity after prolonged exposure to anesthetics. 4. Determination of Altered Serum Lipids Provides Insights into the Molecular Mechanisms Underpinning Neuronal Injury and the Altered Lipids may Serve as Potential Indicators for Anesthetic-induced Neurotoxicity Development of lipid markers in bio-fluids such as serum has great potential for early diagnosis of CNS diseases and disorders. Numerous studies have demonstrated that plasma lipids could be the resource of biomarkers for early detection of many neurological disorders130-134. Therefore, we have hypothesized that alterations of lipid species present in serum samples may serve as effective indicators for the early detection of neuronal injury induced by anesthetic treatment in animal models4, as well as in human neonates and infants. Determining changes of lipid species in brain samples should be very useful for detecting anesthetic-induced neurotoxicity and can provide deep insights into the molecular mechanism(s) leading to the neuronal injury. However, brain samples are not a good source for development of biomarkers for detection of the neurotoxicity due to its inaccessibility in humans. We hypothesized that the changes of brain lipids induced by anesthetic exposure4 might also be reflected in the periphery as alterations of lipid content and composition in serum (plasma). Such alterations could be used as indicators for early detection of brain injury after exposure to general anesthetics as a class, and sevoflurane in particular. In addition, determination of varied lipid homeostasis and metabolism should provide insights into the molecular mechanisms underpinning anesthetic-induced neuronal damage40. Although alterations of lipid content and composition in serum might only be indicative of 15



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changes arising from peripheral organs (e.g., the liver), these changes may still assist in the early detection of anesthetic-induced neurotoxicity. Identification of such indicators should be useful and powerful for safety evaluations. To determine whether changes of lipid level can used as effective indicators for general anesthetic-induced neuronal injury, serum samples have recently been harvested from infant monkeys after exposure to sevoflurane at two-hour intervals and lipidomics analysis of the serum samples has been performed and compared to controls135. It has been found that at least three areas of changes are present in serum lipids of treated animals compared to control as outlined below. 4.1. Changed Serum Lipids Suggest the Existence of an Oxidative Stress State Consistent with the changes of lipid species from brain samples4, it has been found that the content of 4-hydroxynenoal is markedly elevated after prolonged treatment with sevoflurane in comparison to controls135. Moreover, MDMS-SL analysis has revealed that the amounts of nonesterified polyunsaturated fatty acids (PUFA) are markedly decreased at the earliest time point (i.e., 2 h) determined after treatment. In brief, the masses of 22:6, 22:5, and 22:4 fatty acids decrease markedly after exposure for 2 h and these fatty acids are further reduced after exposure for longer periods. Similar to the reduction of non-esterified PUFA, the levels of PUFAcontaining phospholipids are also reduced, particularly those in the class of choline glycerophospholipids. 4.2. Severe Deficiency in Serum Free Carnitine and Acylcarnitines, Indicative of Brain Energy Deficiency after Exposure to Sevoflurane Lipidomics analysis of serum samples from treated infant monkeys has also uncovered marked decreases in the masses of short, medium, and long fatty acylcarnities after infant monkeys are treated with sevoflurane for as short as 2 h. The most changed acylcarnitine species are those 16


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containing 2 to 12 carbon atoms. These observations indicate that the use of fatty acids for βoxidation and amino acids is significantly reduced in the exposed group as the experiment progressed, compared to controls since acylcarnitines containing more than six carbon atoms are largely yielded from fatty acid β-oxidation whereas those containing three to six carbon atoms might be from amino acids. The decreases in acylcarnitine masses in the serum of the exposed group strongly suggests a severe disturbance of energy metabolism in the liver, which subsequently affects the availability of energy substrates in the brains of the exposed infant monkeys, as indicated with a reduced level of serum ketone bodies in the exposed group regardless of keeping the blood glucose concentration constant. For instance, the concentration of β-hydroxybutyrate as a representative of ketone bodies is 2.8 ± 0.1 mM in control vs. 0.9 ± 0.1 mM in treated animals (p = 0.002). To unravel the possible biochemical mechanisms underlying the reduced masses of acylcarnitine species the level of free carnitine in serum has also been determined in the study135 and found to be markedly decreased after exposure for 4 h. This finding suggests that the reduced level of free carnitine in serum might be one of the causal factors resulting in the decreased masses of all acylcarnitine species present in the serum of infant monkeys exposed to sevoflurane since carnitine deficiency should lead to the aberrant energy metabolism. Further experiments have also demonstrated that the disrupted state of energy metabolism occurred in the circulation system is also present in the CNS as the masses of free carnitine and acylcarnitine species in the brain samples and cerebrospinal fluid are lower in the treated animals compared to the controls. Specifically, the short-chain acylcarnitine species such as hydroxybutyryl, acetyl, and free carnitines are markedly decreased in the brain samples of exposed infant monkeys. In addition, the masses of free and acetyl carnitines in cerebrospinal 17



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fluid are markedly reduced in comparison to those of controls. It is well known that acetyl carnitine is a key and sensitive indicator of mitochondrial metabolism associated with all energy substrates since that the content of acetyl carnitine reflects the amount of acetyl-CoA in mitochondria. The determined results clearly suggest the deficiency of energy in the brain regardless of that the concentration of glucose in the circulation system was maintained unchanged. The decreased masses of propionyl, butyryl, and hydroxybutyryl carnitines strongly suggest that the use of amino acids as energy substrates is disrupted in addition to ketone bodies, thus contributing to an energy-deficient state. 4.3. Alterations in Fatty Acid Metabolism and Storage are present in the Treated Group Another finding from the lipidomics study of serum samples from the treated monkeys is the differential alterations of the total blood triacylglycerol (TAG) content and of the composition of fatty acyls present in the TAG pools135. Specifically, the blood TAG level in the unexposed group decreases to around 50 and 25% of the pre-exposure amounts after 4 and 9 h, respectively. This is consistent with facts that under starvation states, fatty acids become the major energy substrates and that blood ketone bodies are elevated in control monkeys. However, the amounts of blood TAG in exposed monkeys are essentially unchanged, suggesting that fatty acids as energy substrates in the circulation system was disrupted. Therefore, the levels of blood TAG in the sevoflurane-treated groups relative to controls are significantly higher at the later time points of exposure (i.e., 8 and 9 h) (Figure 1A). Moreover, the determined profiles of fatty acyl chains in TAG pools have further provided the evidence of differences between the control and exposed monkeys (Figure 1B). In brief, all fatty acyls in TAG pools were systematically decreased in control monkeys. For example, the masses of 16:0, 18:2, 18:1, and 18:0 fatty acyls present in blood TAG pools at 9 h 18


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were reduced around 40% compared to those at 8 h (compared Figure 1B). In contrast, the masses of 16:0 and 18:1 fatty acyls in blood TAG in the treated group were markedly elevated (i.e., from 126.3 ± 32.2 and 137.0 ± 33.8 to 209.8 ± 44.0 and 203.1 ± 52.1 nmol/ml serum, respectively) (Figure 1B) in spite of no changes of TAG masses in the treated monkeys between 8 and 9 h after exposure. The increases in 16:0 and 18:1 fatty acyl masses in blood TAG in the exposed group further support the decreases in the use of these fatty acids as energy substrates since these fatty acids are the preferable compounds to be transported to mitochondria through the carnitine palmitoyltransferease machinery. Alternatively, the increased masses of these fatty acyls might also due to enhanced fatty acid biosynthesis using glucose as the major substrate through the fatty acid synthase/desaturase pathway. Either possibility represents a pathway contributing to the energy-deficient state in the brain under the conditions. 4.4. Changed Serum Lipids as Potential Biomarkers of Anesthetic-Induced Neurotoxicity Multivariate analysis of determined serum lipid changes induced by sevoflurane exposure indicate that the clusters between the exposed and control monkeys can be readily separated without inclusion of TAG data at 2 h after exposure (Figure 2). The loading plot (Figure 2B and D) from partial least squares discriminant analysis indicates that numerous lipids greatly contribute to the clustering between the monkeys. This primary analysis strongly suggests that changed serum lipids could be used as potential indicators of anesthetic-induced neuronal damage. 5. Conclusion and Perspectives This review briefly introduces the expanding field of lipidomics, presents an overview of the available mass spectrometry-based lipidomics tools for lipid analysis, and summarizes the available studies on lipidomics from our laboratories. Even though lipidomics studies on lipid 19



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changes induced by general anesthetics are very limited, the available data clearly indicate that altered energy metabolism and the oxidative stress induced by anesthetics may be causal factors for brain injury associated with prolonged exposure to anesthetics during a critical time of development. It has been strongly suggested that changes in serum (or plasma) lipids could serve as useful markers of anesthetic-induced brain injury. It is clear that lipidomics studies on anesthetic-induced neurotoxicity are in its infant stage. Extensive research in this area is needed, including, but not limited to, (1) whether sevoflurane-induced energy deficiency is a common phenotype of general anesthetics; (2) if it is common to general anesthetics, what are the molecular mechanisms leading to the energy deficiency after exposure; (3) whether drug targets to prevent this type of neurotoxicity can be developed from the identified molecular mechanisms; (4) to what extent the altered blood lipids could serve as indicators to early and specifically detect neuronal damage after exposure to anesthetics; and (5) whether other lipidomics techniques such as mass spectrometry imaging and deep lipidomics analysis such as identification of double bond positional isomers could contribute to the research. Taken together, extensive lipidomics studies on anesthetic-induced neurotoxicity may enable us to address many unresolved questions in this area.

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Acknowledgements This work was partly supported by National Institute of General Medical Sciences Grant R01 GM105724, the Methodist Hospital Foundation, UT Health SA intramural institutional research funds, and Mass Spectrometry Core Facility. Disclaimer: The information in these materials is not a formal dissemination of information by the FDA and does not represent agency position or policy.

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Abbreviations AD, Alzheimer’s disease CNS, central nervous system ESI-MS, electrospray ionization mass spectrometry HILIC, hydrophilic interaction liquid chromatography LC, liquid chromatography MDMS-SL, multi-dimensional MS-based shotgun lipidomics MS, mass spectrometry NLS, neutral loss scan PIS, precursor-ion scan PUFA, polyunsaturated fatty acids TAG, triacylglycerol

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Figure Legends Figure 1. Serum triacylglycerol content and levels of representative fatty acyls in the triacylglycerol pool of infant monkeys with or without exposure to sevoflurane. Lipid extracts from monkey serum were prepared using a modified procedure of Bligh and Dyer42. Triacylglycerol (TAG) content and fatty acyl levels were analyzed directly from lipid extracts using MDMS-SL as previously described136. The levels of serum TAG (A) and selected fatty acyls in the TAG pool after 8 and 9 (B) were compared between the sevoflurane-treated and control groups. The data represent means ± SEM (n = 4 per group) from different monkeys. *p < 0.05 and **p < 0.01 compared to controls. The abbreviations used are AC, acylcarnitine; HNE, 4-hydroxynonenal; PC, phosphatidylcholine; pPC, plasmalogen PC; PI, phosphatidylinositol; LPC, lysoPC; LPE, lysophosphatidylethanolamine; LPG, lysophosphatidylglycerol; LPI, lysoPI; NEFA, nonesterified fatty acid; and SM, sphingomyelin. Reprinted from Wang et al.135 with modification with permission from Elsevier B.V., Copyright 2017. Figure 2. Multivariate analysis of lipidomics data. The PLS-DA score (A and C) and loading (B and D) plots were obtained based on the mass levels of all lipid species of sera except TAG species from sevoflurane-exposed (black squares) and control (open circles) monkeys at 2 (A) and 4 (C) h. The loading plots at 2 (B) and 4 (D) h indicate the variables which were important in explaining both the X- and Y-data in the score plot. Reprinted from Wang et al.135 with modification with permission from Elsevier B.V., Copyright 2017.

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Figure 1

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Figure 2

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Dr. Chunyan Wang Chunyan Wang, Ph.D. is a Research Scientist at the Barshop Institute for Longevity and Aging Studies at the University of Texas Health Science Center at San Antonio, studying alterations in lipid metabolism and homeostasis under disease states by lipidomics. She has authored or co-authored over 30 peer-reviewed scientific articles and book chapters. Dr. Cheng Wang Cheng Wang, M.D., Ph.D. is a Senior Scientist at the National Center for Toxicological Research (NCTR)/US Food and Drug Administration (FDA). He is also an Adjunct Faculty member in the Department of Pharmacology and Toxicology, University of Arkansas for Medical Sciences (UAMS). Dr. Wang has authored or co-authored over 110 peer-reviewed scientific articles and book chapters in the areas of pharmacology, toxicology, genomics and neuroscience. Dr. Wang is a co-Editor-in-chief of 3 books entitled “Developmental Neurotoxicology Research”, “Neural Cell Biology” and “Handbook of Developmental Neurotoxicology-2nd Edition”. Dr. Fang Liu Dr. Fang Liu is a research scientist at the Division of Neurotoxicology, National Center for Toxicological Research (NCTR)/Food and Drug Administration (FDA). Her research work focuses on evaluating developmental neurotoxic effects of FDA-regulated products. One of her research goals is to identify biomarkers from easily accessible biofluids to predict neurotoxic effects of regulated products. Dr. Shuo K. Rainose Shuo K. Rainosek, M.D. is an Anesthesiologist working at the Central Arkansas Veterans Healthcare System in Little Rock, as well as an Assistant Professor in the department of Anesthesiology at the University of Arkansas for Medical Sciences (UAMS). Dr. Rainosek completed medical school, and residency in Anesthesiology at UAMS. Her research interests include neurotoxicity of Anesthetic inhalational agents, and common Anesthetic medications. Dr. Tucker A. Patterson Tucker A. Patterson, Ph.D. is Associate Director for Science & Policy at the National Center for Toxicological Research (NCTR)/U.S. Food & Drug Administration. Dr. Patterson received a B.S. in Chemistry from the University of Arkansas at Fayetteville and a Ph.D. in Pharmacology from the University of South Carolina. Dr. Patterson has been involved in neuroscience and neurotoxicology research for more than thirty years 40


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and has authored or co-authored over 90 peer-reviewed scientific articles and book chapters in the areas of pharmacology, toxicology, behavior and genomics. Dr. William Slikker, Jr. Dr. William Slikker, Jr. is the Director of FDA’s National Center for Toxicological Research (NCTR). He received his Ph.D. in Pharmacology and Toxicology from the University of California at Davis. Dr. Slikker holds adjunct professorships in the Departments of Pediatrics, and Pharmacology/Toxicology at the University of Arkansas for Medical Sciences. He is currently associate editor for NeuroToxicology and Experimental Biology and Medicine. He has served as president of the Academy of Toxicological Sciences, Teratology Society and the Society of Toxicology. Dr. Slikker has co-authored over 350 publications in the areas of transplancental pharmacokinetics, developmental neurotoxicology, systems biology, and risk assessment. Dr. Xianlin Han Xianlin Han, Ph.D. is the Methodist Hospital Foundation Chair in Aging Studies and Research at the Barshop Institute and a Professor of Medicine at the University of Texas Health Science Center at San Antonio. Dr. Han is one of the pioneers in lipidomics and one of the inventors of shotgun lipidomics. He has authored or coauthored over 240 peer-reviewed scientific articles and book chapters with an H-index of 71. He is the author of the book “Lipidomics: Comprehensive Mass Spectrometry of Lipids” and the co-author of the book “Lipid Analysis (4th Edition)” with Dr. William W. Christie.

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Lipidomics Reveals Changes in Metabolism, Indicative of Anesthetic

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