Assessing the External Exposome Using Wearable Passive Samplers and High-Resolution Mass Spectrometry among South African Children Participating in the VHEMBE Study.

Children in low- and middle-income countries are often exposed to higher levels of chemicals and are more vulnerable to the health effects of air pollution. Little is known about the diversity, toxicity, and dynamics of airborne chemical exposures at the molecular level. We developed a workflow employing state-of-the-art wearable passive sampling technology coupled with high-resolution mass spectrometry to comprehensively measure 147 children's personal exposures to airborne chemicals in Limpopo, South Africa, as part of the Venda Health Examination of Mothers, Babies, and Their Environment (VHEMBE). 637 environmental exposures were detected, many of which have never been measured in this population; of these 50 airborne chemical exposures of concern were detected, including pesticides, plasticizers, organophosphates, dyes, combustion products, and perfumes. Biocides detected in wristbands included p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), propoxur, piperonyl butoxide, and triclosan. Exposures differed across the assessment period with 27% of detected chemicals observed to be either higher or lower in the wet or dry seasons.

FluoroMatch 2.0-making automated and comprehensive non-targeted PFAS annotation a reality.

Because of the pervasiveness, persistence, and toxicity of per- and polyfluoroalkyl substances (PFAS), there is growing concern over PFAS contamination, exposures, and health effects. The diversity of potential PFAS is astounding, with nearly 10,000 PFAS catalogued in databases to date (and growing). The ability to detect the thousands of known PFAS, and discover previously uncatalogued PFAS, is necessary to understand the scope of PFAS contamination and to identify appropriate remediation and regulatory solutions. Current non-targeted methods for PFAS analysis require manual curation and are time-consuming, prone to error, and not comprehensive. FluoroMatch Flow 2.0 is the first software to cover all steps of data processing for PFAS discovery in liquid chromatography-high-resolution tandem mass spectrometry samples. These steps include feature detection, feature blank filtering, exact mass matching to catalogued PFAS, mass defect filtering, homologous series detection, retention time pattern analysis, class-based MS/MS screening, fragment screening, and predicted MS/MS from SMILES structures. In addition, a comprehensive confidence level criterion is implemented to help users understand annotation certainty and integrate various layers of evidence to reduce overreporting. Applying the software to aqueous film forming foam analysis, we discovered over one thousand likely PFAS including previously unreported species. Furthermore, we were able to filter out 96% of features which were likely not PFAS. FluoroMatch Flow 2 increased coverage of likely PFAS by over tenfold compared to the previous release. This software will enable researchers to better characterize PFAS in the environment and in biological systems.

Head, Shoulders, Knees, and Toes: Placement of Wearable Passive Samplers Alters Exposure Profiles Observed.

Chemical exposures are a major risk factor for many diseases. Comprehensive characterization of personal exposures is necessary to highlight chemicals of concern and factors that influence these chemical exposure dynamics. For this purpose, wearable passive samplers can be applied to assess longitudinal personal exposures to airborne contaminants. Questions remain regarding the impact of sampler placement at different locations of the body on the exposure profiles observed and how these placements affect the monitoring of seasonal dynamics in exposures. This study assessed personal air contaminant exposure using passive samplers worn in parallel across 32 participant's wrists, chest, and shoes over 24 h. Samplers were analyzed by thermal desorption gas chromatography high-resolution mass spectrometry. Personal exposure profiles were similar for about one-third of the 275 identified chemicals, irrespective of sampler placement. Signals of certain semivolatile organic compounds (SVOCs) were enhanced in shoes and, to a lesser extent, wrist samplers, as compared to those in chest samplers. Signals of volatile organic compounds were less impacted by sampler placement. Results showed that chest samplers predominantly captured more volatile exposures, as compared to those of particle-bound exposures, which may indicate predominant monitoring of chemicals via the inhalation route of exposure for chest samplers. In contrast, shoe samplers were more sensitive to particle-bound SVOCs. Seventy-one chemicals changed across participants between winter and summer in the same manner for two or more different sampler placements on the body, whereas 122 chemicals were observed to have seasonal differences in only one placement. Hence, the placement in certain cases significantly impacts exposure dynamics observed. This work shows that it is essential in epidemiological studies undertaking exposure assessment to consider the consequence of the placement of exposure monitors.

Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry Metabolomics and Lipidomics Study of Stool from Transgenic Parkinson's Disease Mice Following Immunotherapy.

Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta of the brain, as well as the degeneration of motor and nonmotor circuitries. The cause of neuronal death is currently unknown, although chronic neuroinflammation, aggregated α-synuclein, mitochondrial dysfunction, and oxidative stress have all been implicated. Gliosis has been shown to exacerbate neuroinflammation via secretion of proinflammatory cytokines, and there is a subsequent infiltration of T lymphocytes (T-cells), into the brain of PD patients. Using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), we have observed metabolomic changes in stool samples, thought to be associated with the potential disease-modifying effect of immunotherapy administered to transgenic Parkinsonian (A53T) mice. Significant elevations (p < 0.05) in metabolites associated with immune response (taurine, histamine, and its methylated product, 3-methylhistamine) are identified as being higher in the mice undergoing immunotherapy. Furthermore, a reduction in triacylglycerol (TG) and diacylglycerol (DG) expressions in stool following immunotherapy suggests a regulation of lipid breakdown or biosynthesis with the vaccine. These "omics" markers (among others reported in this article) along with weight gain and increased life expectancy suggest that immunotherapy is positively modifying the disease state.

Toward Comprehensive Per- and Polyfluoroalkyl Substances Annotation Using FluoroMatch Software and Intelligent High-Resolution Tandem Mass Spectrometry Acquisition.

Thousands of per- and polyfluoroalkyl substances (PFAS) exist in the environment and pose a potential health hazard. Suspect and nontarget screening with liquid chromatography (LC)-high-resolution tandem mass spectrometry (HRMS/MS) can be used for comprehensive characterization of PFAS. To date, no automated open source PFAS data analysis software exists to mine these extensive data sets. We introduce FluoroMatch, which automates file conversion, chromatographic peak picking, blank feature filtering, PFAS annotation based on precursor and fragment masses, and annotation ranking. The software library currently contains ∼7 000 PFAS fragmentation patterns based on rules derived from standards and literature, and the software automates a process for users to add additional compounds. The use of intelligent data-acquisition methods (iterative exclusion) nearly doubled the number of annotations. The software application is demonstrated by characterizing PFAS in landfill leachate as well as in leachate foam generated to concentrate the compounds for remediation purposes. FluoroMatch had wide coverage, returning 27 PFAS annotations for landfill leachate samples, explaining 71% of the all-ion fragmentation (CF2)n related fragments. By improving the throughput and coverage of PFAS annotation, FluoroMatch will accelerate the discovery of PFAS posing significant human risk.

Environmental lipidomics: understanding the response of organisms and ecosystems to a changing world.

BACKGROUND: Understanding the interaction between organisms and the environment is important for predicting and mitigating the effects of global phenomena such as climate change, and the fate, transport, and health effects of anthropogenic pollutants. By understanding organism and ecosystem responses to environmental stressors at the molecular level, mechanisms of toxicity and adaptation can be determined. This information has important implications in human and environmental health, engineering biotechnologies, and understanding the interaction between anthropogenic induced changes and the biosphere. One class of molecules with unique promise for environmental science are lipids; lipids are highly abundant and ubiquitous across nearly all organisms, and lipid profiles often change drastically in response to external stimuli. These changes allow organisms to maintain essential biological functions, for example, membrane fluidity, as they adapt to a changing climate and chemical environment. Lipidomics can help scientists understand the historical and present biofeedback processes in climate change and the biogeochemical processes affecting nutrient cycles. Lipids can also be used to understand how ecosystems respond to historical environmental changes with lipid signatures dating back to hundreds of millions of years, which can help predict similar changes in the future. In addition, lipids are direct targets of environmental stressors, for example, lipids are easily prone to oxidative damage, which occurs during exposure to most toxins. AIM OF REVIEW: This is the first review to summarize the current efforts to comprehensively measure lipids to better understand the interaction between organisms and their environment. This review focuses on lipidomic applications in the arenas of environmental toxicology and exposure assessment, xenobiotic exposures and health (e.g., obesity), global climate change, and nutrient cycles. Moreover, this review summarizes the use of and the potential for lipidomics in engineering biotechnologies for the remediation of persistent compounds and biofuel production. KEY SCIENTIFIC CONCEPT: With the preservation of certain lipids across millions of years and our ever-increasing understanding of their diverse biological roles, lipidomic-based approaches provide a unique utility to increase our understanding of the contemporary and historical interactions between organisms, ecosystems, and anthropogenically-induced environmental changes.

A histological evaluation of pansteatitis-affected Mozambique tilapia, Oreochromis mossambicus (Peters 1852), from different geographical locations in South Africa.

Pansteatitis is the leading cause for the decline in Nile crocodile populations and the sporadic mortality of fish in the Olifants River System, South Africa. To determine the prevalence of this disease in lentic systems, Mozambique tilapia, Oreochromis mossambicus, were collected from Lake Loskop, Lake Flag Boshielo, Phalaborwa Barrage and Lake Luphephe-Nwanedi. The former three impoundments are located within the main stem of the Olifants River, while the latter, which is geographically isolated and situated in the Limpopo River System, served as a reference site. Mesenteric adipose, liver, serosa of the swim bladder, gill and the skeletal muscle of fish sampled were examined for gross and microscopic evidence of pansteatitis. Microscopically observed changes were used to statistically compare pansteatitis prevalence between samples and sites. Based on histopathological evaluation, the adipose tissue in the liver, swim bladder serosa and coelom from severely debilitated individuals showed the most significant pathological changes. Lesions indicative of steatitis were observed in fish collected from Lake Loskop (75%), Lake Flag Boshielo (22%) and Lake Luphephe-Nwanedi (15%). Further investigation is warranted to understand the pervasiveness and mechanisms driving pathological changes of pansteatitis at Lake Flag Boshielo, Phalaborwa Barrage and Lake Luphephe-Nwanedi.

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values.

BACKGROUND: Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows. RESULTS: LMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine. CONCLUSIONS: LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

Chronic maternal cortisol excess during late gestation leads to metabolic alterations in the newborn heart.

Our laboratory has previously shown in an ovine model of pregnancy that abnormal elevations in maternal cortisol during late gestation lead to increased fetal cardiac arrhythmias and mortality during peripartum. Furthermore, transcriptomic analysis of the fetal heart suggested alterations in TCA cycle intermediates and lipid metabolites in animals exposed to excess cortisol in utero. Therefore, we utilized a sheep model of pregnancy to determine how chronic increases in maternal cortisol alter maternal and fetal serum before birth and neonatal cardiac metabolites and lipids at term. Ewes were either infused with 1 mg·kg-1·day-1 of cortisol starting at gestational day 115 ( n = 9) or untreated ( n = 6). Serum was collected from the mother and fetus (gestational day 125), and hearts were collected following birth. Proton nuclear magnetic resonance (1H-NMR) spectroscopy was conducted to measure metabolic profiles of newborn heart specimens as well as fetal and maternal serum specimens. Mass spectrometry was conducted to measure lipid profiles of newborn heart specimens. We observed alterations in amino acid and TCA cycle metabolism as well as lipid and glycerophospholipid metabolism in newborn hearts after excess maternal cortisol in late gestation. In addition, we observed alterations in amino acid and TCA cycle metabolites in fetal but not in maternal serum during late gestation. These results suggest that fetal exposure to excess maternal cortisol alters placental and fetal metabolism before birth and limits normal cardiac metabolic maturation, which may contribute to increased risk of peripartum cardiac arrhythmias observed in these animals or later life cardiomyopathies.

Effective Liquid Chromatography-Trapped Ion Mobility Spectrometry-Mass Spectrometry Separation of Isomeric Lipid Species.

Lipids are a major class of molecules that play key roles in different biological processes. Understanding their biological roles and mechanisms remains analytically challenging due to their high isomeric content (e.g., varying acyl chain positions and/or double bond locations/geometries) in eukaryotic cells. In the present work, a combination of liquid chromatography (LC) followed by high resolution trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) was used to investigate common isomeric glycerophosphocholine (PC) and diacylglycerol (DG) lipid species from human plasma. The LC dimension was effective for the separation of isomeric lipid species presenting distinct double bond locations or geometries but was not able to differentiate lipid isomers with distinct acyl chain positions. High resolution TIMS-MS resulted in the identification of lipid isomers that differ in the double bond locations/geometries as well as in the position of the acyl chain with resolving power ( R) up to ∼410 ( R ∼ 320 needed on average). Extremely small structural differences exhibiting collision cross sections (CCS) of less than 1% (down to 0.2%) are sufficient for the discrimination of the isomeric lipid species using TIMS-MS. The same level of performance was maintained in the complex biological mixture for the biologically relevant PC 16:0/18:1 lipid isomers. These results suggest several advantages of using complementary LC-TIMS-MS separations for regular lipidomic analysis, with the main emphasis in the elucidation of isomer-specific lipid biological activities.

Lipidomics for wildlife disease etiology and biomarker discovery: a case study of pansteatitis outbreak in South Africa.

INTRODUCTION: Lipidomics is an emerging field with great promise for biomarker and mechanistic studies due to lipids diverse biological roles. Clinical research applying lipidomics is drastically increasing, with research methods and tools developed for clinical applications equally promising for wildlife studies. OBJECTIVES: Limited research to date has applied lipidomics, especially of the intact lipidome, to wildlife studies. Therefore, we examine the application of lipidomics for in situ studies on Mozambique tilapia (Oreochromis mossambicus) in Loskop Dam, South Africa. Wide-scale mortality events of aquatic life associated with an environmentally-derived inflammatory disease, pansteatitis, have occurred in this area. METHODS: The lipidome of adipose tissue (n = 31) and plasma (n = 51) from tilapia collected from Loskop Dam were characterized using state of the art liquid chromatography coupled to high-resolution tandem mass spectrometry. RESULTS: Lipid profiles reflected pansteatitis severity and were significantly different between diseased and healthy individuals. Over 13 classes of lipids associated with inflammation, cell death, and/or oxidative damage were upregulated in pansteatitis-affected adipose tissue, including ether-lipids, short-chained triglyceride oxidation products, sphingolipids, and acylcarnitines. Ceramides showed a 1000-fold increase in the most affected adipose tissues and were sensitive to disease severity. In plasma, triglycerides were found to be downregulated in pansteatitis-affected tilapia. CONCLUSION: Intact lipidomics provided useful mechanistic data and possible biomarkers of pansteatitis. Lipids pointed to upregulated inflammatory pathways, and ceramides serve as promising biomarker candidates for pansteatitis. As comprehensive coverage of the lipidome aids in the elucidation of possible disease mechanisms, application of lipidomics could be applied to the understanding of other environmentally-derived inflammatory conditions, such as those caused by obesogens.

Multiomics approach reveals metabolic changes in the heart at birth.

During late gestation, the fetal heart primarily relies on glucose and lactate to support rapid growth and development. Although numerous studies describe changes in heart metabolism to utilize fatty acids preferentially a few weeks after birth, little is known about metabolic changes of the heart within the first day following birth. Therefore, we used the ovine model of pregnancy to investigate metabolic differences between the near-term fetal and the newborn heart. Heart tissue was collected for metabolomic, lipidomic, and transcriptomic approaches from the left and right ventricles and intraventricular septum in 7 fetuses at gestational day 142 and 7 newborn lambs on the day of birth. Significant metabolites and lipids were identified using a Student's t-test, whereas differentially expressed genes were identified using a moderated t-test with empirical Bayes method [false discovery rate (FDR)-corrected P < 0.10]. Single-sample gene set enrichment analysis (ssGSEA) was used to identify pathways enriched on a transcriptomic level (FDR-corrected P < 0.05), whereas overrepresentation enrichment analysis was used to identify pathways enriched on a metabolomic level ( P < 0.05). We observed greater abundance of metabolites involved in butanoate and propanoate metabolism, and glycolysis in the term fetal heart and differential expression in these pathways were confirmed with ssGSEA. Immediately following birth, newborn hearts displayed enrichment in purine, fatty acid, and glycerophospholipid metabolic pathways as well as oxidative phosphorylation with significant alterations in both lipids and metabolites to support transcriptomic findings. A better understanding of metabolic alterations that occur in the heart following birth may improve treatment of neonates at risk for heart failure.

Pioglitazone improves hepatic mitochondrial function in a mouse model of nonalcoholic steatohepatitis.

Pioglitazone is effective in improving insulin resistance and liver histology in patients with nonalcoholic steatohepatitis (NASH). Because dysfunctional mitochondrial metabolism is a central feature of NASH, we hypothesized that an important target of pioglitazone would be alleviating mitochondrial oxidative dysfunction. To this end, we studied hepatic mitochondrial metabolism in mice fed high-fructose high-transfat diet (TFD) supplemented with pioglitazone for 20 wk, using nuclear magnetic resonance-based 13C isotopomer analysis. Pioglitazone improved whole body and adipose insulin sensitivity in TFD-fed mice. Furthermore, pioglitazone reduced intrahepatic triglyceride content and fed plasma ketones and hepatic TCA cycle flux, anaplerosis, and pyruvate cycling in mice with NASH. This was associated with a marked reduction in most intrahepatic diacylglycerol classes and, to a lesser extent, some ceramide species (C22:1, C23:0). Considering the cross-talk between mitochondrial function and branched-chain amino acid (BCAA) metabolism, pioglitazone's impact on plasma BCAA profile was determined in a cohort of human subjects. Pioglitazone improved the plasma BCAA concentration profile in patients with NASH. This appeared to be related to an improvement in BCAA degradation in multiple tissues. These results provide evidence that pioglitazone-induced changes in NASH are related to improvements in hepatic mitochondrial oxidative dysfunction and changes in whole body BCAA metabolism.

Mass Spectrometric Methodologies for Investigating the Metabolic Signatures of Parkinson's Disease: Current Progress and Future Perspectives.

Parkinson's disease (PD) is a neurodegenerative disorder resulting from the loss of dopaminergic neurons of the substantia nigra as well as degeneration of motor and nonmotor basal ganglia circuitries. Typically known for classical motor deficits (tremor, rigidity, bradykinesia), early stages of the disease are associated with a large nonmotor component (depression, anxiety, apathy, etc.). Currently, there are no definitive biomarkers of PD, and the measurement of dopamine metabolites does not allow for detection of prodromal PD nor does it aid in long-term monitoring of disease progression. Given that PD is increasingly recognized as complex and heterogeneous, involving several neurotransmitters and proteins, it is of importance that we advance interdisciplinary studies to further our knowledge of the molecular and cellular pathways that are affected in PD. This approach will possibly yield useful biomarkers for early diagnosis and may assist in the development of disease-modifying therapies. Here, we discuss preanalytical factors associated with metabolomics studies, summarize current mass spectrometric methodologies used to evaluate the metabolic signature of PD, and provide future perspectives of the rapidly developing field of MS in the context of PD.

Optimization of Electrospray Ionization Source Parameters for Lipidomics To Reduce Misannotation of In-Source Fragments as Precursor Ions.

Lipidomics requires the accurate annotation of lipids in complex samples to enable determination of their biological relevance. We demonstrate that unintentional in-source fragmentation (ISF, common in lipidomics) generates ions that have identical masses to other lipids. Lysophosphatidylcholines (LPC), for example, generate in-source fragments with the same mass as free fatty acids and lysophosphatidylethanolamines (LPE). The misannotation of in-source fragments as true lipids is particularly insidious in complex matrixes since most masses are initially unannotated and comprehensive lipid standards are unavailable. Indeed, we show such LPE/LPC misannotations are incorporated in the data submitted to the National Institute of Standards and Technology (NIST) interlaboratory comparison exercise. Computer simulations exhaustively identified potential misannotations. The selection of in-source fragments of highly abundant lipids as features, instead of the correct recognition of trace lipids, can potentially lead to (i) missing the biologically relevant lipids (i.e., a false negative) and/or (ii) incorrect assignation of a phenotype to an incorrect lipid (i.e., false positive). When ISF is not eliminated in the negative ion mode, ∼40% of the 100 most abundant masses corresponding to unique phospholipids measured in plasma were artifacts from ISF. We show that chromatographic separation and ion intensity considerations assist in distinguishing precursor ions from in-source fragments, suggesting ISF may be especially problematic when complex samples are analyzed via shotgun lipidomics. We also conduct a systematic evaluation of electrospray ionization (ESI) source parameters on an Exactive equipped with a heated electrospray ionization (HESI-II) source with the objective of obtaining uniformly appropriate source conditions for a wide range of lipids, while, at the same time, reducing in-source fragmentation.

NIST lipidomics workflow questionnaire: an assessment of community-wide methodologies and perspectives.

INTRODUCTION: Efforts to harmonize lipidomic methodologies have been limited within the community. Here, we aimed to capitalize on the recent National Institute of Standards and Technology lipidomics interlaboratory comparison exercise by implementing a questionnaire that assessed current methodologies, quantitation strategies, standard operating procedures (SOPs), and quality control activities employed by the lipidomics community. OBJECTIVES: Lipidomics is a rapidly developing field with diverse applications. At present, there are no community-vetted methods to assess measurement comparability or data quality. Thus, a major impetus of this questionnaire was to profile current efforts, highlight areas of need, and establish future objectives in an effort to harmonize lipidomics workflows. METHODS: The 54-question survey inquired about laboratory demographics, lipidomic methodologies and SOPs, analytical platforms, quantitation, reference materials, quality control procedures, and opinions regarding challenges existing within the community. RESULTS: A total of 125 laboratories participated in the questionnaire. A broad overview of results highlighted a wide methodological diversity within current lipidomic workflows. The impact of this diversity on lipid measurement and quantitation is currently unknown and needs to be explored further. While some laboratories do incorporate SOPs and quality control activities, these concepts have not been fully embraced by the community. The top five perceived challenges within the lipidomics community were a lack of standardization amongst methods/protocols, lack of lipid standards, software/data handling and quantification, and over-reporting/false positives. CONCLUSION: The questionnaire provided an overview of current lipidomics methodologies and further promoted the need for community-accepted guidelines and protocols. The questionnaire also served as a platform to help determine and prioritize metrological issues to be investigated.

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data.

BACKGROUND: Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. RESULTS: We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. CONCLUSIONS: LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules.

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

Tissue distribution of perfluoroalkyl acids and health status in wild Mozambique tilapia (Oreochromis mossambicus) from Loskop Dam, Mpumalanga, South Africa.

This study examined concentrations of 15 perfluoroalkyl acids (PFAAs) in tissues from male Mozambique tilapia (Oreochromis mossambicus) collected at Loskop Dam, Mpumalanga, South Africa in 2014 and 2016. Nine of the 15 PFAAs were detected frequently and were included in statistical analysis and included two of the most commonly known PFAAs, perfluorooctanesulfonic acid (PFOS) (median, 41.6ng/g) and perfluorooctanoic acid (PFOA) (median, 0.0825ng/g). Of the tissues measured, plasma (2016 and 2014 median, 22.2ng/g) contained the highest PFAA burden followed by (in descending order): liver (median, 11.6ng/g), kidney (median, 9.04ng/g), spleen (median, 5.92ng/g), adipose (median, 2.54ng/g), and muscle (median, 1.11ng/g). Loskop Dam tilapia have been affected by an inflammatory disease of the adipose tissue known as pansteatitis, so this study also aimed to investigate relationships between PFAA tissue concentrations and incidence of pansteatitis or fish health status. Results revealed that healthy tilapia exhibited an overall higher (p-value<0.05) PFAA burden than pansteatitis-affected tilapia across all tissues. Further analysis showed that organs previously noted in the literature to contain the highest PFAA concentrations, such as kidney, liver, and plasma, were the organs driving the difference in PFAA burden between the two tilapia groups. Care must be taken in the interpretations we draw from not only the results of our study, but also other PFAA measurements made on populations (human and wildlife alike) under differing health status.