Systems Biology

Dietary saturated fatty acids (SFAs) are upregulated in the blood circulation following digestion. A variety of circulating lipid species have been implicated in metabolic and inflammatory diseases; however, due to the extreme variability in serum or plasma lipid concentrations found in human studies, established reference ranges are still lacking, in addition to lipid specificity and diagnostic biomarkers. Mass spectrometry is widely used for identification of lipid species in the plasma, and there are many differences in sample extraction methods within the literature. We used ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS) to compare relative peak abundance of specific lipid species within the following lipid classes: free fatty acids (FFAs), triglycerides (TAGs), phosphatidylcholines (PCs), and sphingolipids (SGs), in the plasma of mice fed a standard chow (SC; low in SFAs) or ketogenic diet (KD; high in SFAs) for two weeks. In this protocol, we used Principal Component Analysis (PCA) and R to visualize how individual mice clustered together according to their diet, and we found that KD-fed mice displayed unique blood profiles for many lipid species identified within each lipid class compared to SC-fed mice. We conclude that two weeks of KD feeding is sufficient to significantly alter circulating lipids, with PCs being the most altered lipid class, followed by SGs, TAGs, and FFAs, including palmitic acid (PA) and PA-saturated lipids. This protocol is needed to advance knowledge on the impact that SFA-enriched diets have on concentrations of specific lipids in the blood that are known to be associated with metabolic and inflammatory diseases.

Key features

• Analysis of relative plasma lipid concentrations from mice on different diets using R.

• Lipidomics data collected via ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS).

• Allows for a comprehensive comparison of diet-dependent plasma lipid profiles, including a variety of specific lipid species within several different lipid classes.

• Accumulation of certain free fatty acids, phosphatidylcholines, triglycerides, and sphingolipids are associated with metabolic and inflammatory diseases, and plasma concentrations may be clinically useful.

Graphical overview

Non-alcoholic steatohepatitis (NASH) is a condition characterized by inflammation and hepatic injury/fibrosis caused by the accumulation of ectopic fats in the liver. Recent advances in lipidomics have allowed the identification and characterization of lipid species and have revealed signature patterns of various diseases. Here, we describe a lipidomics workflow to assess the lipid profiles of liver homogenates taken from a NASH mouse model. The protocol described below was used to extract and analyze the metabolites from the livers of mice with NASH by liquid chromatography–mass spectrometry (LC-MS); however, it can be applied to other tissue homogenate samples. Using this method, over 1,000 species of lipids from five classes can be analyzed in a single run on the LC-MS. Also, partial elucidation of the identity of neutral lipid (triacylglycerides and diacylglycerides) aliphatic chains can be performed with this simple LC-MS setup.

Key features

• Over 1,000 lipid species (sphingolipids, cholesteryl esters, neutral lipids, phospholipids, fatty acids) are analyzed in one run.

• Analysis of liver lipids in non-alcoholic steatohepatitis (NASH) mouse model.

• Normal-phase chromatography coupled to a triple quadrupole mass spectrometer.

Graphical overview

Schematic procedure for the homogenization and extraction of mouse liver tissue in preparation for LC-MS analysis (Created with BioRender.com)

Magnetic resonance spectroscopy (MRS) can be used to measure in vivo concentrations of neurometabolites. This information can be used to identify neurotransmitter involvement in healthy (e.g., perceptual and cognitive processes) and unhealthy brain function (e.g., neurological and psychiatric illnesses). The standard approach for analyzing MRS data is to combine spectral transients acquired over a ~10 min scan to yield a single estimate that reflects the average metabolite concentration during that period. The temporal resolution of metabolite measurements is sacrificed in this manner to achieve a sufficient signal-to-noise ratio to produce a reliable estimate. Here we introduce two analyses that can be used to increase the temporal resolution of neurometabolite estimates produced from MRS measurements. The first analysis uses a sliding window approach to create a smoothed trace of neurometabolite concentration for each MRS scan. The second analysis combines transients across participants, rather than time, producing a single “group trace” with the highest possible temporal resolution achievable with the data. These analyses advance MRS beyond the current “static” application by allowing researchers to measure dynamic changes in neurometabolite concentration and expanding the types of questions that the technique can be used to address.

Macrophages are highly plastic immune cells that are capable of adopting a wide array of functional phenotypes in response to environmental stimuli. The changes in macrophage function are often supported and regulated by changes in cellular metabolism. Capturing a comprehensive picture of metabolism is vital for understanding the role of metabolic rewiring in the immune response. Here we present a method for systematically quantifying the abundance of metabolites and lipids in primary murine bone marrow derived macrophages (BMDMs). This method simultaneously extracts polar metabolites and lipids from BMDMs using a rapid two-phase extraction procedure. The polar metabolite fraction and lipid fraction are subsequently analyzed by separate liquid chromatography-mass spectrometry (LC-MS) methods for optimized coverage and quantification. This allows for a comprehensive characterization of cellular metabolism that can be used to understand the impact of a variety of environmental stimuli on macrophage metabolism and function.

Acclimation of leaf traits to fluctuating environments is a key mechanism to maximize fitness. One of the most important strategies in acclimation to changing light is to maintain efficient utilization of nitrogen in the photosynthetic apparatus by continuous modifications of between-leaf distribution along the canopy depth and within-leaf partitioning between photosynthetic functions according to local light availability. Between-leaf nitrogen distribution has been intensively studied over the last three decades, where proportional coordination between nitrogen concentration and light gradient was considered optimal in terms of maximizing canopy photosynthesis, without taking other canopy structural and physiological factors into account. We proposed a mechanistic model of protein turnover dynamics in different photosynthetic functions, which can be parameterized using leaves grown under different levels of constant light. By integrating this dynamic model into a multi-layer canopy model, constructed using data collected from a greenhouse experiment, it allowed us to test in silico the degree of optimality in photosynthetic nitrogen use for maximizing canopy carbon assimilation under given light environments.

Cancer is a disease characterized by altered metabolism, and there has been renewed interest in understanding the metabolism of tumors. Even though nutrient availability is a critical determinant of tumor metabolism, there has been little systematic study of the nutrients directly available to cancer cells in the tumor microenvironment. Previous work characterizing the metabolites present in the tumor interstitial fluid has been restricted to the measurement of a small number of nutrients such as glucose and lactate in a limited number of samples. Here we adapt a centrifugation-based method of tumor interstitial fluid isolation readily applicable to a number of sample types and a mass spectrometry-based method for the absolute quantitation of many metabolites in interstitial fluid samples. In this method, tumor interstitial fluid (TIF) is analyzed by liquid chromatography-mass spectrometry (LC/MS) using both isotope dilution and external standard calibration to derive absolute concentrations of targeted metabolites present in interstitial fluid. The use of isotope dilution allows for accurate absolute quantitation of metabolites, as other methods of quantitation are inadequate for determining nutrient concentrations in biological fluids due to matrix effects that alter the apparent concentration of metabolites depending on the composition of the fluid in which they are contained. This method therefore can be applied to measure the absolute concentrations of many metabolites in interstitial fluid from diverse tumor types, as well as most other biological fluids, allowing for characterization of nutrient levels in the microenvironment of solid tumors.

The accurate determination of metabolite distribution in subcellular compartments is still challenging in plant science. Various methodologies, such as fluorescence resonance energy transfer-based technology, nuclear magnetic resonance spectroscopy and protoplast fractionation allow the study of metabolite compartmentation. However, large changes in metabolite levels occur during such procedures. Therefore, the non-aqueous fractionation (NAF) technique is currently the best method for the study of in-vivo metabolite distribution. Our protocol presents a detailed workflow including the NAF procedure and quantification of compartment-specific markers for three subcellular compartments: ADP glucose pyrophosphorylase (AGPase) as plastidic marker, phosphoenolpyruvate carboxylase (PEPC) as cytosolic marker, and nitrate and acid invertase as vacuolar markers.

Short-Chain Fatty Acids (SCFAs) are a product of the fermentation of resistant starches and dietary fibers by the gut microbiota. The most important SCFA are acetate (C2), propionate (C3) and butyrate (C4). These metabolites are formed and absorbed in the colon and then transported through the hepatic vein to the liver. SCFAs are more concentrated in the intestinal lumen than in the serum. Butyrate is largely consumed in the gut epithelium, propionate in the liver and acetate in the periphery. SCFAs act on many cells including components of the immune system and epithelial cells by two main mechanisms: activation of G-protein coupled receptors (GPCRs) and inhibition of histone deacetylase. Considering the association between changes in SCFA concentrations and the development of diseases, methods to quantify these acids in different biological samples are important. In this study, we describe a protocol using gas chromatography to quantify SCFAs in the serum, feces and colonic luminal content. Separation of compounds was performed using a DB-23 column (60 m x 0.25 mm internal diameter [i.d.]) coated with a 0.15 µm thick layer of 80.2% 1-methylnaphatalene. This method has a good linear range (15-10,000 µg/ml). The precision (relative standard deviation [RSD]) is less than 15.0% and the accuracy (error relative [ER]) is within ± 15.0%. The extraction efficiency was higher than 97.0%. Therefore, this is cost effective and reproducible method for SCFA measurement in feces and serum.

Stable-isotope labeled metabolic analysis is an essential methodology to characterize metabolic regulation during biological processes. However, the method using stable-isotope-labeled tracer (e.g., ¹³C-glucose) in live animal is only beginning to be developed. Here, we contribute a qualitative metabolic labeling experiment protocol in Drosophila melanogaster using stable-isotope-labeled ¹³C-glucose tracer followed by liquid chromatography-mass spectrometry (LC-MS) analysis. Detailed experimental setup, data acquisition and analysis are provided to facilitate the application of in vivo metabolic labeling analysis that might be applied in a wide range of biological studies.

Modern triple quadrupole mass spectrometers provide the ability to detect and quantify a large number of metabolites using tandem mass spectrometry (MS/MS). Liquid chromatography (LC) is advantageous, as it does not require derivatization procedures and a large diversity in physiochemical characteristics of analytes can be accommodated through a variety of column chemistries. Recently, the comprehensive optimization of LC-MS metabolomics using design of experiments (COLMeD) approach has been described and used by our group to develop robust LC-MS workflows (Rhoades and Weljie, 2016). The optimized LC-MS/MS method described here has been utilized extensively for metabolomics analysis of polar metabolites. Typically, tissue or biofluid samples are extracted using a modified Bligh-Dyer protocol (Bligh and Dyer, 1959; Tambellini et al., 2013). The protocol described herein describes this workflow using targeted polar metabolite multiple reaction monitoring (MRM) from tissues and biofluids via ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). This workflow has been utilized extensively for chronometabolic analysis (Krishnaiah et al., 2017), with applications generalized to other types of analyses as well (Sengupta et al., 2017; Sivanand et al., 2017).