At JGI we analyze metabolite profiles from a wide range of samples including microbes, plants and fungi, as well as the media in which they grow and environment in which they are found, including soil, bodies of water (e.g. ocean, lake), etc. Metabolites are extracted from each type of sample using a variety of methods and solvent systems optimized for specific metabolites of interest. Metabolites from extracts are then detected using our liquid-chromatography tandem mass spectrometry (LC-MS/MS) system, and analyzed using a “targeted” approach, in which standards are used for identification, or an “untargeted” approach, in which software and algorithms are used to help identify compounds, or both depending on the experiment hypotheses.
Currently, the following types of metabolite analyses can be requested in a CSP proposal:
- Polar Metabolite Analysis – small, hydrophilic polar metabolites such as amino acids, nucleic acids, sugars and small organic acids, often involved in primary metabolism. Limit 200 samples.
- Non-polar Metabolite Analysis – generally non-polar metabolites not directly involved in primary metabolism, such as antibiotics, polyketides, phenolics. Limit 500 samples.
- “Targeted” stable isotope labeling of either polar or non-polar metabolites. Limit 200 (if polar) or 500 (if non-polar) samples.
Additional Capabilities – JGI also has limited capacity for samples that include (a) stable isotopic labeling or (b) lipidomics. Please contact Metabolomics group lead Trent Northen or Katherine Louie to discuss available metabolomics analyses complementary to your research.
Polar Metabolite Analysis
Polar metabolite analysis consists of small, polar metabolites such as amino acids, nucleic acids, sugars and small organic acids that are typically part of primary metabolism, often playing a role in normal growth and development and part of fundamental metabolic pathways essential for survival. Characterizing primary metabolites is important for examining interspecies interactions and cross-feeding, and can be used to determine what substrates are synthesized, taken up or released by different organisms under various environmental conditions.
Extraction is performed on a sample (e.g. media, microbial pellet) that has been lyophilized dry, then 100% methanol added to extract the primary metabolites while precipitating most proteins and salts. Each sample extract is run on the JGI LC-MS/MS system with HILIC chromatography, with acquisition of UV as well as MS and MS/MS fragmentation spectra. (~1 hr/sample)
Non-polar Metabolite Analysis
Non-polar metabolite analysis consists of metabolites that have non-polar or hydrophobic chemical properties, and often encompasses secondary metabolites such as polyketides and phenolics. Although not usually essential, secondary metabolites can provide evolutionary advantages important for survival. As more and more organisms are sequenced, more and more new, unique biosynthetic clusters are revealed each day, with the associated secondary metabolites yet to be discovered and functionally characterized.
Analyzing the non-polar or secondary metabolite profile of organisms under various conditions provides the opportunity to identify new compounds, and to gain insight and create linkages between sequence and function, especially in combination with transcriptomics performed on replicate samples. In synthetic biology, this information can be used to determine relative synthesis levels between constructs, discover new compounds as they relate to organism genomics, as well as identify pathway intermediate, shunt products and precursors to better understand pathway dynamics.
Since secondary metabolites are typically non-polar or hydrophobic in nature, either chloroform, methanol or ethyl acetate is used for extraction of a sample. Each sample extract is run on the JGI LC-MS/MS system with C18 chromatography, with acquisition of UV as well as MS and MS/MS fragmentation spectra. (~35 min/sample)
Stable isotope labeling
Stable isotope labeling analysis consists of profiling the relative amount of incorporation of a heavy isotope (e.g. 13C, 2H, 15N) into synthesized metabolites. Mass spectrometry is an ideal analysis tool for stable isotope labeling, since the isotope of each compound is detected in a typical mass spectrum. Here, by comparing ion intensities of isotopes for a metabolite in unlabeled vs. labeled (treated with 13C or deuterium source, for instance) samples, active metabolic pathways can be traced through an organism, fate of a carbon source can be identified, and newly synthesized compounds can be identified.
The heavy isotope can be introduced, for example, as a labeled metabolite serving as a carbon source (e.g. 13C-acetate) to a microbial culture, and then using mass spectrometry to track to what degree (and potentially where) 13C is incorporated into metabolites in various metabolic pathways. For these types of experiments, unlabeled control samples must also be prepared for analysis.
This type of analysis can be performed on any ion feature (unique m/z, RT pair) detected by mass spectrometry; however, currently JGI Metabolomics is restricting analysis to “targeted” metabolites only. Here, the metabolites of interest need to be specified and have a standard available.
“Targeted” Approach
To identify metabolites using a “targeted” approach, we have already run a large library of metabolite standards (currently >500 and growing) to which we are able to compare retention time, m/z (detected mass/charge ratio) and fragmentation spectra to definitively identify metabolites in a sample. Here is a representative sampling of metabolite standards in our library. This approach can be used for any metabolite in which a standard is available, including secondary metabolites (e.g. violacein, prodigiosin).
“Untargeted” Approach
Often, a metabolite standard is not available and no database contains MS/MS fragmentation spectra, especially in the case of many secondary metabolites, or when little is known about the sample submitted for analysis and many unknown or novel compounds are expected. Here, metabolites are putatively identified using an “untargeted approach” with a variety of developed software and algorithms.
Pactolus, a new version of MIDAS (Metabolite Identification via Database Searching), is one solution for “untargeted” analysis developed by LBL researchers. This is essentially an open-source software tool that is able to predict MS/MS fragments from any chemical structure, real or theoretical, available in a database. A metabolite in a sample can then be putatively identified, with a percent probability, by comparing predicted fragments to actual measured fragments from a sample. In the absence of MS/MS fragmentation data from a standard, this is a powerful tool for metabolite identification and dereplication for discovery. Our current database has over 180,000 compounds for untargeted analysis. Additional software tools are in development for identification of unknowns and linkage to genomics.
Lipidomics
A diversity of lipids are found across organisms and environments, each playing critical roles in membrane organization, structure, and signaling, responding to environmental conditions such as desiccation or light, sporulation, as well as being important precursors for production of biofuels or involved in secondary metabolite biosynthesis. Often, species of lipids (e.g. phosphatidylcholine, or PC lipid) are distinguished by a common headgroup attached to fatty acid chains of various carbon length and degree of saturation. Although several hundred forms of each species may exist, fragmentation during mass spectrometry analysis often leads to a characteristic fragmentation ion (e.g. 184 for PC) or neutral loss (e.g. -179 for MGDG) allowing for identification.
Here, we are able to identify common lipid species that have characteristic fragmentation spectra, and are often able to purchase a standard of each species. Some lipid species we have recently annotated include TG, DG, PC, PE, SQDG, SM, MGDG, DGDG, PG and respective lyso-lipids. Please contact Trent Northen or Katherine Louie to discuss available lipidomics analyses.