Assessing compartmentalized flux in lipid metabolism with isotopes

SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism

The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.

Physcomitrium patens response to elevated CO2 is flexible and determined by an interaction between sugar and nitrogen availability

Mosses hold a unique position in plant evolution and are crucial for protecting natural, long-term carbon storage systems such as permafrost and bogs. Due to small stature, mosses grow close to the soil surface and are exposed to high levels of CO2 , produced by soil respiration. However, the impact of elevated CO2 (eCO2 ) levels on mosses remains underexplored. We determined the growth responses of the moss Physcomitrium patens to eCO2 in combination with different nitrogen levels and characterized the underlying physiological and metabolic changes. Three distinct growth characteristics, an early transition to caulonema, the development of longer, highly pigmented rhizoids, and increased biomass, define the phenotypic responses of P. patens to eCO2 . Elevated CO2 impacts growth by enhancing the level of a sugar signaling metabolite, T6P. The quantity and form of nitrogen source influences these metabolic and phenotypic changes. Under eCO2 , P. patens exhibits a diffused growth pattern in the presence of nitrate, but ammonium supplementation results in dense growth with tall gametophores, demonstrating high phenotypic plasticity under different environments. These results provide a framework for comparing the eCO2 responses of P. patens with other plant groups and provide crucial insights into moss growth that may benefit climate change models.

Lipid Metabolism and Improvement in Oilseed Crops: Recent Advances in Multi-Omics Studies

Oilseed crops are rich in plant lipids that not only provide essential fatty acids for the human diet but also play important roles as major sources of biofuels and indispensable raw materials for the chemical industry. The regulation of lipid metabolism genes is a major factor affecting oil production. In this review, we systematically summarize the metabolic pathways related to lipid production and storage in plants and highlight key research advances in characterizing the genes and regulatory factors influencing lipid anabolic metabolism. In addition, we integrate the latest results from multi-omics studies on lipid metabolism to provide a reference to better understand the molecular mechanisms underlying oil anabolism in oilseed crops.

Arabidopsis ACYL CARRIER PROTEIN4 and RHOMBOID LIKE10 act independently in chloroplast phosphatidate synthesis

ACYL CARRIER PROTEIN4 (ACP4) is the most abundant ACP isoform in Arabidopsis (Arabidopsis thaliana) leaves and acts as a scaffold for de novo fatty acid biosynthesis and as a substrate for acyl-ACP-utilizing enzymes. Recently, ACP4 was found to interact with a protein-designated plastid RHOMBOID LIKE10 (RBL10) that affects chloroplast monogalactosyldiacylglycerol (MGDG) biosynthesis, but the cellular function of this interaction remains to be explored. Here, we generated and characterized acp4 rbl10 double mutants to explore whether ACP4 and RBL10 directly interact in influencing chloroplast lipid metabolism. Alterations in the content and molecular species of chloroplast lipids such as MGDG and phosphatidylglycerol were observed in the acp4 and rbl10 mutants, which are likely associated with the changes in the size and profiles of diacylglycerol (DAG), phosphatidic acid (PA), and acyl-ACP precursor pools. ACP4 contributed to the size and profile of the acyl-ACP pool and interacted with acyl-ACP-utilizing enzymes, as expected for its role in fatty acid biosynthesis and chloroplast lipid assembly. RBL10 appeared to be involved in the conversion of PA to DAG precursors for MGDG biosynthesis as evidenced by the increased 34:x PA and decreased 34:x DAG in the rbl10 mutant and the slow turnover of radiolabeled PA in isolated chloroplasts fed with [14C] acetate. Interestingly, the impaired PA turnover in rbl10 was partially reversed in the acp4 rbl10 double mutant. Collectively, this study shows that ACP4 and RBL10 affect chloroplast lipid biosynthesis by modulating substrate precursor pools and appear to act independently.

Genome-Wide Analysis of Glycerol-3-Phosphate Acyltransferase (GPAT) Family in Perilla frutescens and Functional Characterization of PfGPAT9 Crucial for Biosynthesis of Storage Oils Rich in High-Value Lipids

Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the first step in triacylglycerol (TAG) biosynthesis. However, GPAT members and their functions remain poorly understood in Perilla frutescens, a special edible-medicinal plant with its seed oil rich in polyunsaturated fatty acids (mostly α-linolenic acid, ALA). Here, 14 PfGPATs were identified from the P. frutescens genome and classified into three distinct groups according to their phylogenetic relationships. These 14 PfGPAT genes were distributed unevenly across 11 chromosomes. PfGPAT members within the same subfamily had highly conserved gene structures and four signature functional domains, despite considerable variations detected in these conserved motifs between groups. RNA-seq and RT-qPCR combined with dynamic analysis of oil and FA profiles during seed development indicated that PfGPAT9 may play a crucial role in the biosynthesis and accumulation of seed oil and PUFAs. Ex vivo enzymatic assay using the yeast expression system evidenced that PfGPAT9 had a strong GPAT enzyme activity crucial for TAG assembly and also a high substrate preference for oleic acid (OA, C18:1) and ALA (C18:3). Heterogeneous expression of PfGPAT9 significantly increased total oil and UFA (mostly C18:1 and C18:3) levels in both the seeds and leaves of the transgenic tobacco plants. Moreover, these transgenic tobacco lines exhibited no significant negative effect on other agronomic traits, including plant growth and seed germination rate, as well as other morphological and developmental properties. Collectively, our findings provide important insights into understanding PfGPAT functions, demonstrating that PfGPAT9 is the desirable target in metabolic engineering for increasing storage oil enriched with valuable FA profiles in oilseed crops.

Expression of malic enzyme reveals subcellular carbon partitioning for storage reserve production in soybeans

Central metabolism produces amino and fatty acids for protein and lipids that establish seed value. Biosynthesis of storage reserves occurs in multiple organelles that exchange central intermediates including two essential metabolites, malate, and pyruvate that are linked by malic enzyme. Malic enzyme can be active in multiple subcellular compartments, partitioning carbon and reducing equivalents for anabolic and catabolic requirements. Prior studies based on isotopic labeling and steady-state metabolic flux analyses indicated malic enzyme provides carbon for fatty acid biosynthesis in plants, though genetic evidence confirming this role is lacking. We hypothesized that increasing malic enzyme flux would alter carbon partitioning and result in increased lipid levels in soybeans. Homozygous transgenic soybean plants expressing Arabidopsis malic enzyme alleles, targeting the translational products to plastid or outside the plastid during seed development, were verified by transcript and enzyme activity analyses, organelle proteomics, and transient expression assays. Protein, oil, central metabolites, cofactors, and acyl-acyl carrier protein (ACPs) levels were quantified overdevelopment. Amino and fatty acid levels were altered resulting in an increase in lipids by 0.5-2% of seed biomass (i.e. 2-9% change in oil). Subcellular targeting of a single gene product in central metabolism impacts carbon and reducing equivalent partitioning for seed storage reserves in soybeans.

Transcriptional regulation of oil biosynthesis in seed plants: Current understanding, applications, and perspectives

Plants produce and accumulate triacylglycerol (TAG) in their seeds as an energy reservoir to support the processes of seed germination and seedling development. Plant seed oils are vital not only for the human diet but also as renewable feedstocks for industrial use. TAG biosynthesis consists of two major steps: de novo fatty acid biosynthesis in the plastids and TAG assembly in the endoplasmic reticulum. The latest advances in unraveling transcriptional regulation have shed light on the molecular mechanisms of plant oil biosynthesis. We summarize recent progress in understanding the regulatory mechanisms of well-characterized and newly discovered transcription factors and other types of regulators that control plant fatty acid biosynthesis. The emerging picture shows that plant oil biosynthesis responds to developmental and environmental cues that stimulate a network of interacting transcriptional activators and repressors, which in turn fine-tune the spatiotemporal regulation of the pathway genes.

13C-labeling reveals how membrane lipid components contribute to triacylglycerol accumulation in Chlamydomonas

Lipid metabolism in microalgae has attracted much interest due to potential utilization of lipids as feedstocks for biofuels, nutraceuticals, and other high-value compounds. Chlamydomonas reinhardtii is a model organism for characterizing the synthesis of the neutral lipid triacylglycerol (TAG), from which biodiesel is made. While much of TAG accumulation under N-deprivation is the result of de novo fatty acid (FA) synthesis, recent work has revealed that approximately one-third of FAs, especially polyunsaturated FAs (PUFAs), come from preexisting membrane lipids. Here, we used 13C-isotopic labeling and mass spectrometry to analyze the turnover of glycerol backbones, headgroups, FAs, whole molecules, and molecular fragments of individual lipids. About one-third of the glyceryl backbones in TAG are derived from preexisting membrane lipids, as are approximately one-third of FAs. The different moieties of the major galactolipids turn over synchronously, while the FAs of diacylglyceryltrimethylhomoserine (DGTS), the most abundant extraplastidial lipid, turn over independently of the rest of the molecule. The major plastidic lipid monogalactosyldiacylglycerol (MGDG), whose predominant species is 18:3α/16:4, was previously shown to be a major source of PUFAs for TAG synthesis. This study reveals that MGDG turns over as whole molecules, the 18:3α/16:4 species is present in both DAG and TAG, and the positional distribution of these PUFAs is identical in MGDG, DAG, and TAG. We conclude that headgroup removal with subsequent acylation is the mechanism by which the major MGDG species is converted to TAG during N-deprivation. This has noteworthy implications for engineering the composition of microalgal TAG for food, fuel, and other applications.

Metabolic flux analysis of the non-transitory starch tradeoff for lipid production in mature tobacco leaves

The metabolic plasticity of tobacco leaves has been demonstrated via the generation of transgenic plants that can accumulate over 30% dry weight as triacylglycerols. In investigating the changes in carbon partitioning in these high lipid-producing (HLP) leaves, foliar lipids accumulated stepwise over development. Interestingly, non-transient starch was observed to accumulate with plant age in WT but not HLP leaves, with a drop in foliar starch concurrent with an increase in lipid content. The metabolic carbon tradeoff between starch and lipid was studied using 13CO2-labeling experiments and isotopically nonstationary metabolic flux analysis, not previously applied to the mature leaves of a crop. Fatty acid synthesis was investigated through assessment of acyl-acyl carrier proteins using a recently derived quantification method that was extended to accommodate isotopic labeling. Analysis of labeling patterns and flux modeling indicated the continued production of unlabeled starch, sucrose cycling, and a significant contribution of NADP-malic enzyme to plastidic pyruvate production for the production of lipids in HLP leaves, with the latter verified by enzyme activity assays. The results suggest an inherent capacity for a developmentally regulated carbon sink in tobacco leaves and may in part explain the uniquely successful leaf lipid engineering efforts in this crop.

Quantification of Acyl-Acyl Carrier Proteins for Fatty Acid Synthesis Using LC-MS/MS

The fatty acid biosynthetic cycle is predicated on an acyl carrier protein (ACP) scaffold where two carbon acetyl groups are added in a chain elongation process through a series of repeated enzymatic steps. The chain extension is terminated by hydrolysis with a thioesterase or direct transfer of the acyl group to a glycerophospholipid by an acyltransferase. Methods for analysis of the concentrations of acyl chains attached to ACPs are lacking but would be informative for studies in lipid metabolism. We describe a method to profile and quantify the levels of acyl-ACPs in plants, bacteria and mitochondria of animals and fungi that represent Type II fatty acid biosynthetic systems. ACPs of Type II systems have a highly conserved Asp-Ser-Leu-Asp (DSLD) amino acid sequence at the attachment site for 4'-phosphopantetheinyl arm carrying the acyl chain. Three amino acids of the conserved sequence can be cleaved away from the remainder of the protein using an aspartyl protease. Thus, partially purified protein can be enzymatically hydrolyzed to produce an acyl chain linked to a tripeptide via the 4'-phosphopantetheinyl group. After ionization and fragmentation, the corresponding fragment ion is detected by a triple quadrupole mass spectrometer using a multiple reaction monitoring method. ¹⁵N isotopically labeled acyl-ACPs generated in high amounts are used with an isotope dilution strategy to quantify the absolute levels of each acyl group attached to the acyl carrier protein scaffold.

Analyzing Mass Spectrometry Imaging Data of 13C-Labeled Phospholipids in Camelina sativa and Thlaspi arvense (Pennycress) Embryos

The combination of ¹³C-isotopic labeling and mass spectrometry imaging (MSI) offers an approach to analyze metabolic flux in situ. However, combining isotopic labeling and MSI presents technical challenges ranging from sample preparation, label incorporation, data collection, and analysis. Isotopic labeling and MSI individually create large, complex data sets, and this is compounded when both methods are combined. Therefore, analyzing isotopically labeled MSI data requires streamlined procedures to support biologically meaningful interpretations. Using currently available software and techniques, here we describe a workflow to analyze ¹³C-labeled isotopologues of the membrane lipid and storage oil lipid intermediate―phosphatidylcholine (PC). Our results with embryos of the oilseed crops, Camelina sativa and Thlaspi arvense (pennycress), demonstrated greater ¹³C-isotopic labeling in the cotyledons of developing embryos compared with the embryonic axis. Greater isotopic enrichment in PC molecular species with more saturated and longer chain fatty acids suggest different flux patterns related to fatty acid desaturation and elongation pathways. The ability to evaluate MSI data of isotopically labeled plant embryos will facilitate the potential to investigate spatial aspects of metabolic flux in situ.

Model-assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom-up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint-based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

¹³C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. ¹³C MFA, however, stands out from other "-omics sciences," in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying ¹³C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of ¹³C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an "all-around carefree package" for ¹³C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of ¹³C MFA.

Accurate and efficient amino acid analysis for protein quantification using hydrophilic interaction chromatography coupled tandem mass spectrometry

BACKGROUND

Methods used to quantify protein from biological samples are often inaccurate with significant variability that requires care to minimize. The errors result from losses during protein preparation and purification and false detection of interfering compounds or elements. Amino acid analysis (AAA) involves a series of chromatographic techniques that can be used to measure protein levels, avoiding some difficulties and providing specific compositional information. However, unstable derivatives, that are toxic and can be costly, incomplete reactions, inadequate chromatographic separations, and the lack of a single hydrolysis method with sufficient recovery of all amino acids hinder precise protein quantitation using AAA.

RESULTS

In this study, a hydrophilic interaction chromatography based method was used to separate all proteinogenic amino acids, including isobaric compounds leucine and isoleucine, prior to detection by multiple reaction monitoring with LC-MS/MS. Through inclusion of commercially available isotopically labeled (13C, 15N) amino acids as internal standards we adapted an isotopic dilution strategy for amino acid-based quantification of proteins. Three hydrolysis methods were tested with ubiquitin, bovine serum albumin, (BSA), and a soy protein biological reference material (SRM 3234; NIST) resulting in protein estimates that were 86-103%, 82-94%, and 90-99% accurate for the three protein samples respectively. The methane sulfonic acid hydrolysis approach provided the best recovery of labile amino acids including: cysteine, methionine and tryptophan that are challenging to accurately quantify.

CONCLUSIONS

Accurate determination of protein quantity and amino acid composition in heterogeneous biological samples is non-trivial. Recent advances in chromatographic phases and LC-MS/MS based methods, along with the availability of isotopic standards can minimize difficulties in analysis and improve protein quantitation. A robust method is described for high-throughput protein quantification and amino acid compositional analysis. Since accurate measurement of protein quality and quantity are a requirement for many biological studies that relate to crop improvement or more generally, our understanding of metabolism in living systems, we envision this method will have broad applicability.

Recent developments in synthetic biology and metabolic engineering in microalgae towards biofuel production

In the wake of the uprising global energy crisis, microalgae have emerged as an alternate feedstock for biofuel production. In addition, microalgae bear immense potential as bio-cell factories in terms of producing key chemicals, recombinant proteins, enzymes, lipid, hydrogen and alcohol. Abstraction of such high-value products (algal biorefinery approach) facilitates to make microalgae-based renewable energy an economically viable option. Synthetic biology is an emerging field that harmoniously blends science and engineering to help design and construct novel biological systems, with an aim to achieve rationally formulated objectives. However, resources and tools used for such nuclear manipulation, construction of synthetic gene network and genome-scale reconstruction of microalgae are limited. Herein, we present recent developments in the upcoming field of microalgae employed as a model system for synthetic biology applications and highlight the importance of genome-scale reconstruction models and kinetic models, to maximize the metabolic output by understanding the intricacies of algal growth. This review also examines the role played by microalgae as biorefineries, microalgal culture conditions and various operating parameters that need to be optimized to yield biofuel that can be economically competitive with fossil fuels.

Recent advances in stable isotope-enabled mass spectrometry-based plant metabolomics

Methods employing isotope labeled compounds have been an important part of the bioanalytical canon for many decades. The past fifteen years have seen the development of many new approaches using stable (non-radioactive) isotopes as labels for high-throughput bioanalytical, 'omics-scale' measurements of metabolites (metabolomics) and proteins (proteomics). This review examines stable isotopic labeling approaches that have been developed for labeling whole intact plants, plant tissues, or crude extracts of plant materials with stable isotopes (mainly using ²H, ¹³C, ¹⁵N, ¹⁸O or ³⁴S). The application of metabolome-scale labeling for improving metabolite annotation, metabolic pathway elucidation, and relative quantification in mass spectrometry-based metabolomics of plants is also reviewed.