This protocol describes how to prepare Drosophila larvae for GC-MS-based metabolomic analysis.
Recent advances in the field of metabolomics have established the fruit fly Drosophila melanogaster as a powerful genetic model for studying animal metabolism. By combining the vast array of Drosophila genetic tools with the ability to survey large swaths of intermediary metabolism, a metabolomics approach can reveal complex interactions between diet, genotype, life-history events, and environmental cues. In addition, metabolomics studies can discover novel enzymatic mechanisms and uncover previously unknown connections between seemingly disparate metabolic pathways. In order to facilitate more widespread use of this technology among the Drosophila community, here we provide a detailed protocol that describes how to prepare Drosophila larval samples for gas chromatography-mass spectrometry (GC-MS)-based metabolomic analysis. Our protocol includes descriptions of larval sample collection, metabolite extraction, chemical derivatization, and GC-MS analysis. Successful completion of this protocol will allow users to measure the relative abundance of small polar metabolites, including amino acids, sugars, and organic acids involved in glycolysis and the TCA cycles.
The fruit fly Drosophila melanogaster has emerged as an ideal system for studying the molecular mechanism that regulate intermediary metabolism. Not only are most metabolic pathways conserved between Drosophila and humans, but key nutrient sensors and growth regulators, such as insulin, Tor, and myc, are also active in the fly1,2. As a result, Drosophila can be used to explore the metabolic basis of human diseases ranging from diabetes and obesity to neurodegeneration and cancer. In this regard, Drosophila larval development provides the ideal framework in which to study a metabolic program known as aerobic glycolysis, or the Warburg effect. Just as many tumors use aerobic glycolysis to generate biomass from carbohydrates, so to do Drosophila larvae activate aerobic glycolysis to promote developmental growth3,4,5. These similarities between larval and tumor metabolism establish Drosophila as a key model for understanding how aerobic glycolysis is regulated in vivo.
Despite the fact that the fly has emerged as a popular model for studying metabolism, most Drosophila studies rely on methods that are designed to measure individual metabolites3, such as trehalose, triglycerides, or ATP. Since a specific protocol is required to measure each metabolite, assay-based studies are labor-intensive, expensive, and biased towards those compounds that can be measured using commercial kits. A solution to these limitations has emerged from the field of metabolomics, which provides a more efficient and unbiased means of studying Drosophila metabolism. Unlike an assay-based study, a single metabolomic analysis can simultaneously measure hundreds of small molecule metabolites and provide a comprehensive understanding of an organism's metabolic status6,7. This technique has significantly expanded the scope of Drosophila metabolic studies and represents the future of this emerging field8.
Metabolomic studies are primarily conducted using three technologies: (i) nuclear magnetic resonance (NMR), (ii) liquid chromatography-mass spectrometry (LC-MS), and (iii) gas chromatography-mass spectrometry (GC-MS)9. Each approach offers distinct advantages and disadvantages, and all of these technologies have been used to successfully study Drosophila metabolism. Since the research conducted in our lab is focused on small, polar metabolites, we primarily employ a GC-MS-based method. GC-MS provides the user with a number of advantages, including high reproducibility, peak resolution, sensitivity, and the availability of a standard electron impact (EI) spectral library, which allows for the rapid identification of discovered metabolic features10,11. The preparation of samples for GC-MS, however, is somewhat complex and requires a careful attention to detail. Samples must be collected, washed, weighed, and frozen in a manner that quickly quenches metabolic reactions. Furthermore, the fly carcass is resistant to standard homogenization protocols and requires a bead mill to ensure optimal metabolite extraction. Finally, samples analyzed by GC-MS must undergo chemical derivatization prior to detection12. While previously published methods describe all of these steps3,13,14, a visual protocol that would allow the novice user to reproducibly generate high quality data is still needed. Here we demonstrate how to prepare Drosophila larval samples for GC-MS-based metabolomics analysis. This protocol allows the user to reproducibly measure many of the small polar metabolites that compose central carbon metabolism.
1. Egg Collection
2. Larval Sample Collection
3. Transfer of Samples to Bead Tubes
4. Sample Extraction
5. Chemical Derivatization
6. GC-MS Detection
NOTE: In most cases, the user will conduct this step with the assistance of a mass spectroscopy core facility. This protocol is designed to be used with a 30 m, GC column with a 5 m guard column.
7. Data Analysis
Lactate dehydrogenase (dLDH) mutants, which lack dLDH activity4, and genetically-matched controls were collected as mid-L2 larvae and processed according to protocol described above. When compared with controls, mutant larvae exhibit significant changes in lactate, pyruvate, and L-2-hydroxyglutarate4. Spectra were acquired with an Agilent GC6890-5973i MS system. An example of the GC-MS spectra generate with our protocol is shown in Figure 1. There are many visible features and a notable peak for trehalose, which normally represents the largest peak in a larval sample and is usually oversaturated (Figure 1A,B). The individual spectrum of negative control sample is shown in Figure 1C. Although there are still several visible peaks in the negative control sample, the intensity and the number of peaks are reduced when compared with the experimental samples shown in Figure 1A,B. These peaks primarily result from column bleed, the internal standard (succinic-d4 acid), FAMEs, and contaminating fatty acids. Failed sample preparation will generate a spectrum similar to the one shown in Figure 1C.
All the spectra were preprocessed using MetAlign17 and data were normalized with the internal standard and pellet mass. Subsequently, the data were submitted to MetaboAnalyst18,19 for statistical analysis. Principle component analysis (PCA) clearly shows that the two groups separate from each other and that there is no outlier in either group (Figure 2A). Further analysis shows significant changes in the metabolites known to be affected by loss of dLDH (Figure 2B)4.
Figure 1: Representative GC-MS spectra of Drosophila larval extract. (A-B) Typical spectra of mid-L2 larval extracts from wild type (WT) and dLDH mutants (KO). (C) A representative GC-MS spectrum generated from a negative control (NC) sample. Most of the peaks in this spectrum are from internal standard, FAMEs and fatty acids. (D-F) When compared with WT samples, the KO samples exhibit elevated levels of (D) pyruvate and decreased levels of (E) lactate and (F) 2-hydroxyglutarate (2-HG). Please click here to view a larger version of this figure.
Figure 2: Statistical analysis shows the different metabolic profiles between wild type (WT) and dLDH knockout (KO) larvae. (A) PCA scores plot. (B) Metabolites that exhibit significant changes in dLDH mutants. All data points are plotted relative to the mean of the WT control, which was adjusted to an arbitrary value of 100. Prior to analysis, data was normalized to the succinic-d4 acid internal standard and larval pellet mass. Data shown as mean ± one standard deviation. p <0.01 for all metabolites using a two-tailed t-test. Please click here to view a larger version of this figure.
Metabolomics provides an unparalleled opportunity to survey the metabolic reactions that compose intermediary metabolism. The sensitivity of this technology, however, renders data susceptible to genetic background, developmental cues, and a variety of environmental stresses, including temperature, humidity, population density, and nutrient availability. Therefore, a high quality and reproducible metabolomics analysis requires that samples be collected under highly controlled conditions. While several reviews emphasize this point3,8,23, here we provide a step-by-step method for collecting larvae that is designed to ensure reproducibility.
The most common source of variability in a metabolomics analysis stems from a failure to quench, or stop, metabolic reactions after the sample is collected. In this regard, metabolism will stop upon freezing in liquid nitrogen and metabolic enzymes will be destroyed when the sample is homogenized in -20 °C methanol. Assuming that the user pays special attention to keeping a sample frozen prior to methanol extraction, our protocol is designed to ensure that the metabolomics data generated by this procedure represent an accurate snapshot of larval metabolism. Should the user experience unacceptable levels of data variability, the user should reexamine the collection and metabolite extraction protocol with special attention paid to ensuring (1) that metabolism is rapidly quenched (Steps 2.9–4.2) and (2) that the sample is efficiently homogenized in 90% methanol (Step 4.4). In this regard, many bead mills provide insufficient force to homogenize samples within the specified time and we encourage the user to use an instrument that has been used in previous studies8.
Our protocol also highlights key steps that the novice user must note in order to reproducibly derivatize samples. This is essential for GC-MS because many metabolites have limited volatility or poor thermal stability. Derivatization increases both the volatility and thermal stability of many metabolites, thereby increasing the number of compounds that can be reproducibly measured. As a result, samples that have undergone incomplete derivatization will exhibit non-reproducible peak areas, heights, and shapes. As we emphasize here, a common source of failed derivatization is exposure of the sample to water, which decreases the chemical derivatization efficiency. Therefore, all reagents, including MSTFA, MOX, and pyridine, must be kept under moisture-free conditions. The need to maintain dry conditions also extends to preparing samples that are stored at -80 °C, which should be placed in a vacuum centrifuge for 30 min before opening to ensure that condensation does not enter the sample. We would also like to emphasize that GC-MS is a sensitive technology, and as a result, larger samples will not necessarily generate better data. Our protocol provides experimentally tested sample sizes and will reproducibly measure most metabolites in central carbon metabolism. Some of these metabolites are very abundant and increased sample size will lead to signal saturation in the spectrum. In fact, the signal for trehalose is already saturated in our analysis and a split ratio of 100:1 for GC-MS injection must be used to accurately measure this compound. Finally, the user should note that because we use a polar extraction solution, our protocol is not appropriate for lipid extraction. Our protocol also does not account for fatty acids contaminants that could be present on the plastic tubes and tips, which is why some fatty acid signals appear in the negative control sample (Figure 1B).
Finally, the methods detailed here provides a powerful tool for studying Drosophila metabolism. This protocol, however, is not specific to Drosophila and can be used with few modifications for conducting metabolic studies in any small invertebrate. Regardless of the species, this simple method allows for relative quantification of nearly all amino acids, intermediates in glycolysis and the TCA cycle, as well as a number of other small polar molecules. When combined with the unparalleled genetic tools available to the Drosophila community, this type of metabolomic analysis places the fly at the forefront of metabolic research for the foreseeable future.
The authors have nothing to disclose.
Thanks to members of the Indiana University Mass Spectroscopy Facility and the University of Utah Metabolomics Core Facility for assistance in optimizing this protocol. J.M.T. is supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM119557.
Unsulfured blackstrap molasses | Good Food, INC | ||
Drosophila Agar Type II | Genesee Scientific | 66-103 | |
Pyridine | EMD Millipore | PX2012-7 | |
Methoxyamine hydrocholoride (MOX) | MP Biomedicals, LLC | 155405 | |
MSTFA with 1% trimethylchlorosilane | Sigma | 69478 | |
Fleischmann’s Active dry yeast | AB Mauri Food Inc | 2192 | |
6oz Drosophila stock bottle | Genesee Scientific | 32-130 | |
Soft tissue homogenizing mix (2 mL tubes) | Omni International | SKU:19-627 | |
Vial insert, 250 µL deactivated glass with polymer feet | Agilent | 5181-8872 | |
Succinic acid-2,2,3,3-d4 | Sigma | 293075 | |
SpeedVac | Thermo | SC210A | |
o-Phosphoric acid | Fisher Scientific | A242-1 | |
Propionic acid | Sigma | P5561 | |
p-Hydroxy benzoic acid methyl ester | Genesee Scientific | 20-258 | |
Bead Ruptor | Omni International | SKU:19-040E | |
ThermoMixer F1.5 | Eppendorf | 5384000012 | |
MultiTherm Shaker with a 24 X 12 mm block | Benchmark Scientific | H5000 | |
Methanol | Sigma | 34860 | |
1.5 mL centrifuge tube | Eppendorf | 22364111 | |
Falcon 35 X 10 mm tissue culture dish | Corning Incorporated | 353001 | |
GC column | Phenomex | ZB-5MSi |