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Development of an R script for simple lipidomic and metabolomic data analysis

Background: Metabolomic and lipidomic studies generate vast quantities of data that are often analysed in a closed software environment with little to no access to the underlying algorithms. As a result, data processed via different software pipelines yield different results thus leading to a widespread problem of low reproducibility within these fields. To address this problem, we are developing LipidAnalyst; an R based lipidomics software pipeline. As a part of this project, we are creating a simple statistical analysis and graphing module in R to generate accurate, reproducible, high-resolution figures. Methods: R scripts were developed under version 3.5.3 with the capability to undertake statistical analyses (e.g. ANOVA) and post-hoc tests (e.g. Tukey). Additional code plotted resultant information as high resolution violin and box plots that depicted statistical significance. Thereafter, lipidomic and metabolomic data were analysed by this code and compared against commercial software and Metaboanalyst, a primary software used in metabolomic and lipidomic research. Results: Code generated in house demonstrated the same results as those generated using commercial software (e.g. JMP 14.0 Pro) but were different from results obtained by using the MetaboAnalyst pipeline. Conclusions: This study demonstrated the prevalent danger of using closed-source software pipelines for the analysis of lipidomic and metabolomic data without validating the analysis outcomes via open-source software. Open source software such as LipidAnalyst, that has also been independently validated using multiple data sets, can then be published with the results to enable transparency of data analysis and improve the replicability of results across different labs.https://scholarscompass.vcu.edu/gradposters/1092/thumbnail.jp

Untargeted Lipidomic Analysis to Broadly Characterize the Effects of Pathogenic and Non-Pathogenic Staphylococci on Mammalian Lipids

Modification of the host lipidome via secreted enzymes is an integral, but often overlooked aspect of bacterial pathogenesis. In the current era of prevalent antibiotic resistance, knowledge regarding critical host pathogen lipid interactions has the potential for use in developing novel antibacterial agents. While most studies to date on this matter have focused on specific lipids, or select lipid classes, this provides an incomplete picture. Modern methods of untargeted lipidomics have the capacity to overcome these gaps in knowledge and provide a comprehensive understanding of the role of lipid metabolism in the pathogenesis of infections. In an attempt to determine the role of lipid modifying enzymes produced by staphylococci, we exposed bovine heart lipids, a standardized model for the mammalian lipidome, to spent medium from staphylococcal cultures, and analyzed lipid molecular changes by MS/MSALLshotgun lipidomics. We elucidate distinct effects of different staphylococcal isolates, including 4 clinical isolates of the pathogenic species Staphylococcus aureus, a clinical isolate of the normally commensal species S. epidermidis, and the non-pathogenic species S. carnosus. Two highly virulent strains of S. aureus had a more profound effect on mammalian lipids and modified more lipid classes than the other staphylococcal strains. Our studies demonstrate the utility of the applied untargeted lipidomics methodology to profile lipid changes induced by different bacterial secretomes. Finally, we demonstrate the promise of this lipidomics approach in assessing the specificity of bacterial enzymes for mammalian lipid classes. Our data suggests that there may be a correlation between the bacterial expression of lipid-modifying enzymes and virulence, and could facilitate the guided discovery of lipid pathways required for bacterial infections caused by S. aureus and thereby provide insights into the generation of novel antibacterial agents

A Preliminary Investigation towards the Risk Stratification of Allogeneic Stem Cell Recipients with Respect to the Potential for Development of GVHD via Their Pre-Transplant Plasma Lipid and Metabolic Signature

The clinical outcome of allogeneic hematopoietic stem cell transplantation (SCT) may be influenced by the metabolic status of the recipient following conditioning, which in turn may enable risk stratification with respect to the development of transplant-associated complications such as graft vs. host disease (GVHD). To better understand the impact of the metabolic profile of transplant recipients on post-transplant alloreactivity, we investigated the metabolic signature of 14 patients undergoing myeloablative conditioning followed by either human leukocyte antigen (HLA)-matched related or unrelated donor SCT, or autologous SCT. Blood samples were taken following conditioning and prior to transplant on day 0 and the plasma was comprehensively characterized with respect to its lipidome and metabolome via liquid chromatography/mass spectrometry (LCMS) and gas chromatography/mass spectrometry (GCMS). A pro-inflammatory metabolic profile was observed in patients who eventually developed GVHD. Five potential pre-transplant biomarkers, 2-aminobutyric acid, 1-monopalmitin, diacylglycerols (DG 38:5, DG 38:6), and fatty acid FA 20:1 demonstrated high sensitivity and specificity towards predicting post-transplant GVHD. The resulting predictive model demonstrated an estimated predictive accuracy of risk stratification of 100%, with area under the curve of the ROC of 0.995. The likelihood ratio of 1-monopalmitin (infinity), DG 38:5 (6.0), and DG 38:6 (6.0) also demonstrated that a patient with a positive test result for these biomarkers following conditioning and prior to transplant will be at risk of developing GVHD. Collectively, the data suggest the possibility that pre-transplant metabolic signature may be used for risk stratification of SCT recipients with respect to development of alloreactivity

Metabolic Modulation Predicts Heart Failure Tests Performance

The metabolic changes that accompany changes in Cardiopulmonary testing (CPET) and heart failure biomarkers (HFbio) are not well known. We undertook metabolomic and lipidomic phenotyping of a cohort of heart failure (HF) patients and utilized Multiple Regression Analysis (MRA) to identify associations to CPET and HFBio test performance (peak oxygen consumption (Peak VO2), oxygen uptake efficiency slope (OUES), exercise duration, and minute ventilation-carbon dioxide production slope (VE/VCO2 slope), as well as the established HF biomarkers of inflammation C-reactive protein (CRP), beta-galactoside-binding protein (galectin-3), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP)). A cohort of 49 patients with a left ventricular ejection fraction \u3c 50%, predominantly males African American, presenting a high frequency of diabetes, hyperlipidemia, and hypertension were used in the study. MRA revealed that metabolic models for VE/VCO2 and Peak VO2 were the most fitted models, and the highest predictors’ coefficients were from Acylcarnitine C18:2, palmitic acid, citric acid, asparagine, and 3-hydroxybutiric acid. Metabolic Pathway Analysis (MetPA) used predictors to identify the most relevant metabolic pathways associated to the study, aminoacyl-tRNA and amino acid biosynthesis, amino acid metabolism, nitrogen metabolism, pantothenate and CoA biosynthesis, sphingolipid and glycerolipid metabolism, fatty acid biosynthesis, glutathione metabolism, and pentose phosphate pathway (PPP). Metabolite Set Enrichment Analysis (MSEA) found associations of our findings with pre-existing biological knowledge from studies of human plasma metabolism as brain dysfunction and enzyme deficiencies associated with lactic acidosis. Our results indicate a profile of oxidative stress, lactic acidosis, and metabolic syndrome coupled with mitochondria dysfunction in patients with HF tests poor performance. The insights resulting from this study coincides with what has previously been discussed in existing literature thereby supporting the validity of our findings while at the same time characterizing the metabolic underpinning of CPET and HFBio

Molecular Predictors of Anakinra Treatment Success in Heart Failure Patients with Reduced Ejection Fraction

Background. Kineret (Anakinra) is an interleukin-1 antagonist that is under investigation for its novel clinical application treating patients that have heart failure with reduced (\u3c50%) ejection fraction (HFrEF). A prior study from our group indicated that Anakinra may restore heart function by addressing dysregulations in HFrEF metabolic pathways. Herein, we attempt to elicit Anakinra’s effects on both metabolome and lipidome. Methods. Lipids and metabolites that had previously been quantified by mass spectrometry (MS) from patients (n=49) who had ≥2 mg/L of high-sensitivity C-reactive protein (hs-CRP) were mTIC normalized and transformed. We conducted a stepwise Linear Discriminant Analysis (r- LDA) to test Anakinra (2 and 12 weeks) vs placebo for separation from combined baseline. Metabolic pathway analysis was performed with Fisher’s exact test algorithm for detection of over-represented and enriched analytes. Univariate analysis (one tailed t-test p\u3c0.05) compared placebo and Anakinra after 12-weeks for effect(s). Metaboanalyst 4.0, JMP Pro 14.0, and a proprietary package in R (version 3.4.4) were the software for all analyses and data wrangling. Results. Analytes such as acylcarnitines C10:0 and C16:0 and hsCRP showed significant improvements after 12 weeks of Anakinra, leading to improved mitochondrial function, reduced inflammation, and overall better health outcomes. Statistically significant (p\u3c0.05) pathways including the citrate cycle, cysteine and methionine metabolism, galactose metabolism among others were associated with treatment. Conclusions. We were able to determine significant alterations to metabolomic and lipidomic concentrations after 12 weeks of Anakinra therapy. Our biochemical analyses verifies that Anakinra did improve heart function within our HFrEF pilot cohort.https://scholarscompass.vcu.edu/gradposters/1081/thumbnail.jp

Antihypertensive Treatment Differentially Affects Vascular Sphingolipid Biology in Spontaneously Hypertensive Rats

We have previously shown that essential hypertension in humans and spontaneously hypertensive rats (SHR), is associated with increased levels of ceramide and marked alterations in sphingolipid biology. Pharmacological elevation of ceramide in isolated carotid arteries of SHR leads to vasoconstriction via a calcium-independent phospholipase A2, cyclooxygenase-1 and thromboxane synthase-dependent release of thromboxane A2. This phenomenon is almost absent in vessels from normotensive Wistar Kyoto (WKY) rats. Here we investigated whether lowering of blood pressure can reverse elevated ceramide levels and reduce ceramide-mediated contractions in SHR. Methods and Findings For this purpose SHR were treated for 4 weeks with the angiotensin II type 1 receptor antagonist losartan or the vasodilator hydralazine. Both drugs decreased blood pressure equally (SBP untreated SHR: 191±7 mmHg, losartan: 125±5 mmHg and hydralazine: 113±14 mmHg). The blood pressure lowering was associated with a 20–25% reduction in vascular ceramide levels and improved endothelial function of isolated carotid arteries in both groups. Interestingly, losartan, but not hydralazine treatment, markedly reduced sphingomyelinase-induced contractions. While both drugs lowered cyclooxygenase-1 expression, only losartan and not hydralazine, reduced the endothelial expression of calcium-independent phospholipase A2. The latter finding may explain the effect of losartan treatment on sphingomyelinase-induced vascular contraction. Conclusion In summary, this study corroborates the importance of sphingolipid biology in blood pressure control and specifically shows that blood pressure lowering reduces vascular ceramide levels in SHR and that losartan treatment, but not blood pressure lowering per se, reduces ceramide-mediated arterial contractions

Hypertension Is Associated with Marked Alterations in Sphingolipid Biology: A Potential Role for Ceramide

Background Hypertension is, amongst others, characterized by endothelial dysfunction and vascular remodeling. As sphingolipids have been implicated in both the regulation of vascular contractility and growth, we investigated whether sphingolipid biology is altered in hypertension and whether this is reflected in altered vascular function. Methods and Findings In isolated carotid arteries from spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto (WKY) rats, shifting the ceramide/S1P ratio towards ceramide dominance by administration of a sphingosine kinase inhibitor (dimethylsphingosine) or exogenous application of sphingomyelinase, induced marked endothelium-dependent contractions in SHR vessels (DMS: 1.4±0.4 and SMase: 2.1±0.1 mN/mm; n = 10), that were virtually absent in WKY vessels (DMS: 0.0±0.0 and SMase: 0.6±0.1 mN/mm; n = 9, p Conclusions Hypertension is associated with marked alterations in vascular sphingolipid biology such as elevated ceramide levels and signaling, that contribute to increased vascular tone

Multivariate Curve Resolution-Alternating Least Squares Analysis of High-Resolution Liquid Chromatography–Mass Spectrometry Data

Methods such as liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) are crucial for differentiating compounds with highly similar masses. This is a necessity when analyzing highly complex samples; however, the size of high-resolution LC-HRMS data sets can cause difficulties when applying advanced data analysis techniques. In this work, LC-HRMS analyses of known amphetamine samples and unknown bacterial lipid samples were carried out, and multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the data to obtain mathematical separation of overlapped analyte signals. In order to minimize computational strain, a novel strategy was developed which minimizes the number of irrelevant masses analyzed at full resolution. To do this, data were first binned to unit mass resolution, and MCR-ALS was performed. This provided mathematical components for each analyte present plus background components. In the resolved spectral profiles of analyte components, masses above a preset intensity threshold were extracted, discarding all other masses, and expanded to successively higher levels of resolution, applying MCR-ALS at each level. These steps were repeated until 0.001 amu resolution was achieved, as dictated by the resolution of the instrumentin this case, a time-of-flight mass spectrometer. This strategy allowed for the accurate recovery of all known amphetamine compounds and select bacterial lipid extracts while minimizing the size of the data, therefore minimizing computational analysis time and data storage requirements. This relatively simple strategy enables the effective coupling of LC-HRMS with MCR-ALS

Prospective clinical biomarkers of caspase-mediated apoptosis associated with neuronal and neurovascular damage following stroke and other severe brain injuries: Implications for chronic neurodegeneration

Acute brain injuries, including ischemic and hemorrhagic stroke, as well as traumatic brain injury (TBI), are major worldwide health concerns with very limited options for effective diagnosis and treatment. Stroke and TBI pose an increased risk for the development of chronic neurodegenerative diseases, notably chronic traumatic encephalopathy, Alzheimer's disease, and Parkinson's disease. The existence of premorbid neurodegenerative diseases can exacerbate the severity and prognosis of acute brain injuries. Apoptosis involving caspase-3 is one of the most common mechanisms involved in the etiopathology of both acute and chronic neurological and neurodegenerative diseases, suggesting a relationship between these disorders. Over the past two decades, several clinical biomarkers of apoptosis have been identified in cerebrospinal fluid and peripheral blood following ischemic stroke, intracerebral and subarachnoid hemorrhage, and TBI. These biomarkers include selected caspases, notably caspase-3 and its specific cleavage products such as caspase-cleaved cytokeratin-18, caspase-cleaved tau, and a caspase-specific 120 kDa αII-spectrin breakdown product. The levels of these biomarkers might be a valuable tool for the identification of pathological pathways such as apoptosis and inflammation involved in injury progression, assessment of injury severity, and prediction of clinical outcomes. This review focuses on clinical studies involving biomarkers of caspase-3-mediated pathways, following stroke and TBI. The review further examines their prospective diagnostic utility, as well as clinical utility for improved personalized treatment of stroke and TBI patients and the development of prophylactic treatment chronic neurodegenerative disease