Computational Modeling of Competitive Metabolism between ω3- and ω6-Polyunsaturated Fatty Acids in Inflammatory Macrophages

An adaptable in silico ensemble model of the arachidonic acid cascade

Eicosanoids are a family of bioactive lipids, including derivatives of the ubiquitous fatty acid arachidonic acid (AA). The intimate involvement of eicosanoids in inflammation motivates the development of predictive in silico models for a systems-level exploration of disease mechanisms, drug development and replacement of animal models. Using an ensemble modelling strategy, we developed a computational model of the AA cascade. This approach allows the visualisation of plausible and thermodynamically feasible predictions, overcoming the limitations of fixed-parameter modelling. A quality scoring method was developed to quantify the accuracy of ensemble predictions relative to experimental data, measuring the overall uncertainty of the process. Monte Carlo ensemble modelling was used to quantify the prediction confidence levels. Model applicability was demonstrated using mass spectrometry mediator lipidomics to measure eicosanoids produced by HaCaT epidermal keratinocytes and 46BR.1N dermal fibroblasts, treated with stimuli (calcium ionophore A23187), (ultraviolet radiation, adenosine triphosphate) and a cyclooxygenase inhibitor (indomethacin). Experimentation and predictions were in good qualitative agreement, demonstrating the ability of the model to be adapted to cell types exhibiting differences in AA release and enzyme concentration profiles. The quantitative agreement between experimental and predicted outputs could be improved by expanding network topology to include additional reactions. Overall, our approach generated an adaptable, tuneable ensemble model of the AA cascade that can be tailored to represent different cell types and demonstrated that the integration of in silico and in vitro methods can facilitate a greater understanding of complex biological networks such as the AA cascade.

Mathematical Modeling of Eicosanoid Metabolism in Macrophage Cells: Cybernetic Framework Combined with Novel Information-Theoretic Approaches

Cellular response to inflammatory stimuli leads to the production of eicosanoids—prostanoids (PRs) and leukotrienes (LTs)—and signaling molecules—cytokines and chemokines—by macrophages. Quantitative modeling of the inflammatory response is challenging owing to a lack of knowledge of the complex regulatory processes involved. Cybernetic models address these challenges by utilizing a well-defined cybernetic goal and optimizing a coarse-grained model toward this goal. We developed a cybernetic model to study arachidonic acid (AA) metabolism, which included two branches, PRs and LTs. We utilized a priori biological knowledge to define the branch-specific cybernetic goals for PR and LT branches as the maximization of TNFα and CCL2, respectively. We estimated the model parameters by fitting data from three experimental conditions. With these parameters, we were able to capture a novel fourth independent experimental condition as part of the model validation. The cybernetic model enhanced our understanding of enzyme dynamics by predicting their profiles. The success of the model implies that the cell regulates the synthesis and activity of the associated enzymes, through cybernetic control variables, to accomplish the chosen biological goal. The results indicated that the dominant metabolites are PGD2 (a PR) and LTB4 (an LT), aligning with their corresponding known prominent biological roles during inflammation. Using heuristic arguments, we also infer that eicosanoid overproduction can lead to increased secretion of cytokines/chemokines. This novel model integrates mechanistic knowledge, known biological understanding of signaling pathways, and data-driven methods to study the dynamics of eicosanoid metabolism.

Feasibility of Investigational Procedures and Efficacy of a Personalized Omega-3 Dietary Intervention in Alleviating Pain and Psychoneurological Symptoms in Breast Cancer Survivors

BACKGROUND

Breast cancer survivors (BCS) are at risk for psychoneurological symptoms (PNS) and inflammation for years following cancer treatment. Fish, particularly salmon, provides a rich source of omega-3 long chain fatty acids (omega-3LC), which has an anti-inflammatory effect. However, the benefit of omega-3LC on PNS is not well-known.

AIMS

This study evaluated the feasibility and the initial efficacy of a personalized meal plan with dietary omega-3LC in reducing PNS.

METHODS

A prospective, randomized controlled trial design (n = 46) was used to evaluate the feasibility of a personalized meal plan using two omega-3LC dose levels (high and low omega-3LC) in reducing PNS including pain, depression, fatigue, sleep, and stress.

RESULTS

The recruitment rate was 4.9% with overall retention rate of 74% and 67.1% adherence to personalized meal plan and dietary procedures. Of participants who completed the investigation, 94% completed fish adherence logs and consumed ≥70% of the assigned quantity of fish. Saliva collection was 97.8% at baseline and 100% at follow-up. BCS in the high omega-3LC group had a significant decrease in pain (p < .01), perceived stress (p < .05), sleep (p < .001), depression (p < .001), and fatigue (p < .01) over the course of intervention. There were trends of PNS improvement in the low omega-3LC group but the differences did not reach statistical significance.

CONCLUSION

Our results support the feasibility of our investigational design, procedures, and intervention. The outcomes provide preliminary support for an expanded research effort using fish as a source of omega-3LC and personalized dietary planning as a vehicle for symptom self-management in BCS.

A Soluble Epoxide Hydrolase Inhibitor, 1-TrifluoromethoxyPhenyl-3-(1-Propionylpiperidin-4-yl) Urea, Ameliorates Experimental Autoimmune Encephalomyelitis

Polyunsaturated fatty acids (PUFAs) are essential FAs for human health. Cytochrome P450 oxygenates PUFAs to produce anti-inflammatory and pain-resolving epoxy fatty acids (EpFAs) and other oxylipins whose epoxide ring is opened by the soluble epoxide hydrolase (sEH/Ephx2), resulting in the formation of toxic and pro-inflammatory vicinal diols (dihydroxy-FAs). Pharmacological inhibition of sEH is a promising strategy for the treatment of pain, inflammation, cardiovascular diseases, and other conditions. We tested the efficacy of a potent, selective sEH inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU), in an animal model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE). Prophylactic TPPU treatment significantly ameliorated EAE without affecting circulating white blood cell counts. TPPU accumulated in the spinal cords (SCs), which was correlated with plasma TPPU concentration. Targeted lipidomics in EAE SCs and plasma identified that TPPU blocked production of dihydroxy-FAs efficiently and increased some EpFA species including 12(13)-epoxy-octadecenoic acid (12(13)-EpOME) and 17(18)-epoxy-eicosatrienoic acid (17(18)-EpETE). TPPU did not alter levels of cyclooxygenase (COX-1/2) metabolites, while it increased 12-hydroxyeicosatetraenoic acid (12-HETE) and other 12/15-lipoxygenase metabolites. These analytical results are consistent with sEH inhibitors that reduce neuroinflammation and accelerate anti-inflammatory responses, providing the possibility that sEH inhibitors could be used as a disease modifying therapy, as well as for MS-associated pain relief.

Effects of parental dietary linoleic acid on growth performance, antioxidant capacity, and lipid metabolism in domestic pigeons (Columba livia)

The objective of this study was to evaluate the effects of dietary linoleic acid (LA) on growth performance, antioxidant capacity, and lipid metabolism in pigeon squabs by supplementing LA in their parental diets. A completely randomized design that consisted of a control group, 1% dietary LA addition group (LA1%), 2% dietary LA addition group (LA2%), and 4% dietary LA addition group (LA4%) was used. Six squabs from each treatment were randomly sampled at the day of hatch and days 7, 14, and 21 after hatch. The results showed that parental dietary LA had no significant influence (P > 0.05) on body weight (BW) gain or relative organ weights (% of BW) in squabs. The activities of superoxide dismutase, catalase, and glutathione peroxidase in the LA1% were significantly increased (P < 0.05) compared with those in the control group. The malondialdehyde content in the LA1% was significantly lower (P < 0.05) than that in the control group. The levels of serum triglyceride in the LA1% and LA2% were significantly decreased (P < 0.05) compared with those in the control group, whereas the serum high-density lipoprotein cholesterol level in the LA1% and LA2% and the free fatty acid level in the LA4% were significantly higher (P < 0.05) than those of the control group. The activities of lipoprotein lipase, hepatic lipase, and hormone-sensitive lipase in the LA1% were significantly higher (P < 0.05) than those in the control group. The 3-hydroxy-3-methylglutaryl coenzyme A reductase activity in the LA1% and the hormone-sensitive lipase activity in the LA4% were significantly decreased (P < 0.05) compared with those in the control group. The mRNA expression of carnitine palmitoyltransferase 1, acyl-CoA 1, and peroxisome proliferator-activated receptor α was significantly upregulated (P < 0.05) in the LA1% compared with that in the control group. The Oil Red O staining area in the LA1% and LA2% was significantly reduced compared with that in the control group. The results indicated that although supplemental LA had negligible effects on growth and development in pigeon squabs, parental dietary LA at a concentration of 1% could have beneficial effects on maintaining squabs healthy as reflected by improved antioxidant capacity and lipid metabolism.

Quantitative Kinetic Models from Intravital Microscopy: A Case Study Using Hepatic Transport

The liver performs critical physiological functions, including metabolizing and removing substances, such as toxins and drugs, from the bloodstream. Hepatotoxicity itself is intimately linked to abnormal hepatic transport, and hepatotoxicity remains the primary reason drugs in development fail and approved drugs are withdrawn from the market. For this reason, we propose to analyze, across liver compartments, the transport kinetics of fluorescein-a fluorescent marker used as a proxy for drug molecules-using intravital microscopy data. To resolve the transport kinetics quantitatively from fluorescence data, we account for the effect that different liver compartments (with different chemical properties) have on fluorescein's emission rate. To do so, we develop ordinary differential equation transport models from the data where the kinetics is related to the observable fluorescence levels by "measurement parameters" that vary across different liver compartments. On account of the steep non-linearities in the kinetics and stochasticity inherent to the model, we infer kinetic and measurement parameters by generalizing the method of parameter cascades. For this application, the method of parameter cascades ensures fast and precise parameter estimates from noisy time traces.

A Cybernetic Approach to Modeling Lipid Metabolism in Mammalian Cells

The goal-oriented control policies of cybernetic models have been used to predict metabolic phenomena such as the behavior of gene knockout strains, complex substrate uptake patterns, and dynamic metabolic flux distributions. Cybernetic theory builds on the principle that metabolic regulation is driven towards attaining goals that correspond to an organism’s survival or displaying a specific phenotype in response to a stimulus. Here, we have modeled the prostaglandin (PG) metabolism in mouse bone marrow derived macrophage (BMDM) cells stimulated by Kdo2-Lipid A (KLA) and adenosine triphosphate (ATP), using cybernetic control variables. Prostaglandins are a well characterized set of inflammatory lipids derived from arachidonic acid. The transcriptomic and lipidomic data for prostaglandin biosynthesis and conversion were obtained from the LIPID MAPS database. The model parameters were estimated using a two-step hybrid optimization approach. A genetic algorithm was used to determine the population of near optimal parameter values, and a generalized constrained non-linear optimization employing a gradient search method was used to further refine the parameters. We validated our model by predicting an independent data set, the prostaglandin response of KLA primed ATP stimulated BMDM cells. We show that the cybernetic model captures the complex regulation of PG metabolism and provides a reliable description of PG formation.

Use of quantitative clinical pharmacology to improve early clinical development success in neurodegenerative diseases

INTRODUCTION

The success rate of pharmaceutical Research & Development (R&D) is much lower compared to other industries such as micro-electronics or aeronautics with the probability of a successful clinical development to approval in central nervous system (CNS) disorders hovering in the single digits (7%). Areas covered: Inspired by adjacent engineering-based industries, we argue that quantitative modeling in CNS R&D might improve success rates. We will focus on quantitative techniques in early clinical development, such as PharmacoKinetic-PharmacoDynamic modeling, clinical trial simulation, model-based meta-analysis and the mechanism-based physiology-based pharmacokinetic modeling, and quantitative systems pharmacology. Expert commentary: Mechanism-based computer modeling rely less on existing clinical datasets, therefore can better generalize than Big Data analytics, including prospectively and quantitatively predicting the clinical outcome of new drugs. More specifically, exhaustive post-hoc analysis of failed trials using individual virtual human trial simulation could illuminate underlying causes such as lack of sufficient functional target engagement, negative pharmacodynamic interactions with comedications and genotypes, and mismatched patient population. These insights are beyond the capacity of artificial intelligence (AI) methods as they are many more possible combinations than subjects. Unlike 'black box' approaches in AI, mechanism-based platforms are transparent and based on biologically sound assumptions that can be interrogated.

Cerebrovascular β-amyloid deposition and associated microhemorrhages in a Tg2576 Alzheimer mouse model are reduced with a DHA-enriched diet

Cerebral amyloid angiopathy (CAA) is a major contributor to Alzheimer's disease (AD) pathogenesis. Like AD, CAA is often accompanied by marked inflammation, aggravating associated vasculopathies. No evidence-based prevention or treatment strategies are available. Here, we evaluate the possible beneficial effect of a diet enriched with docosahexaenoic acid (DHA), which is known to attenuate inflammation in CAA. Tg2576 mice, a transgenic model of AD/CAA, were fed a DHA-enriched diet starting at 2 mo of age and ending at 10, 14, or 18 mo of age. β-Amyloid (Aβ)-peptide deposition and bleeding were visualized by immunohistochemistry or histochemistry on coronal sections of the brain. DHA, arachidonic acid, and eicosanoid levels were measured by liquid chromatography/mass spectrometry or GC-MS. DHA-enriched diet throughout aging limits the accumulation of vascular Aβ peptide deposits as well as the likelihood of microhemorrhages. There is a strong correlation between systemic 12-hydroxyeicosatetraenoic acid (HETE) levels and the size of the area affected by both vascular amyloid deposits and hemorrhages. The lowest levels of 12-HETE, a lipid-derived proinflammatory product of 12-lipoxygenase (LOX), were found in DHA-fed mice. In vitro experiments performed on amyloid vascular smooth muscle cells showed that a 12-LOX inhibitor almost completely blocked the Aβ_1-40 peptide-induced apoptosis of these cells. This study yet again highlights the important role of inflammation in CAA pathogenesis and identifies potential new targets for preventive care.-Hur, J., Mateo, V., Amalric, N., Babiak, M., Béréziat, G., Kanony-Truc, C., Clerc, T., Blaise, R., Limon, I. Cerebrovascular β-amyloid deposition and associated microhemorrhages in a Tg2576 Alzheimer mouse model are reduced with a DHA-enriched diet.

Oxidative lipidomics: applications in critical care

PURPOSE OF REVIEW

Lipid peroxidation has long been established as a key player in the pathophysiology of critical illness. Recent developments in oxidative lipidomics have aided in deciphering the molecular mechanisms of lipid oxidation in health and disease. This review discusses recent achievements and recent developments in oxidative lipidomics and its contribution to the understanding of critical illness.

RECENT FINDINGS

Most studies involving acute injury focus on identifying the end products of lipid peroxidation. This misses the early events and targets of peroxidation mechanisms. Recent developments in liquid chromatography tandem mass spectrometry-based oxidative lipidomics have enabled the identification of a wide variety of enzymatically generated lipid oxidation products. Such lipid mediators have been found to play an important role in injury, inflammation, and recovery in disease states such as sepsis or head trauma.

SUMMARY

Multiple lipid oxidation products are formed either through enzymatic pathways or through random chemical reactions. These products are often biologically active and can contribute to the regulation of cellular signaling. Oxidative lipidomics has contributed to the identification and quantification of lipid peroxidation products, the mechanism and time course of their production after injury, and synergistic functioning with other regulatory processes in the body. These advances in knowledge will help guide the future development of interventions in critical illness.

Liberating Chiral Lipid Mediators, Inflammatory Enzymes, and LIPID MAPS from Biological Grease

In 1970, it was well accepted that the central role of lipids was in energy storage and metabolism, and it was assumed that amphipathic lipids simply served a passive structural role as the backbone of biological membranes. As a result, the scientific community was focused on nucleic acids, proteins, and carbohydrates as information-containing molecules. It took considerable effort until scientists accepted that lipids also "encode" specific and unique biological information and play a central role in cell signaling. Along with this realization came the recognition that the enzymes that act on lipid substrates residing in or on membranes and micelles must also have important signaling roles, spurring curiosity into their potentially unique modes of action differing from those acting on water-soluble substrates. This led to the creation of the concept of "surface dilution kinetics" for describing the mechanism of enzymes acting on lipid substrates, as well as the demonstration that lipid enzymes such as phospholipase A₂ (PLA₂) contain allosteric activator sites for specific phospholipids as well as for membranes. As our understanding of phospholipases advanced, so did the understanding that many of the lipids released by these enzymes are chiral information-containing signaling molecules; for example, PLA₂ regulates the generation of precursors for the biosynthesis of eicosanoids and other bioactive lipid mediators of inflammation and resolution underlying disease progression. The creation of the LIPID MAPS initiative in 2003 and the ensuing development of the lipidomics field have revealed that lipid metabolites are central to human metabolism. Today lipids are recognized as key mediators of health and disease as we enter a new era of biomarkers and personalized medicine. This article is my personal "reflection" on these scientific advances.