1Biosphere Oriented Biology Research Unit, RIKEN Advanced Science Institute, 2Graduate School of Nanobioscience, Yokohama City University, 3Advanced NMR Metabomics Research Team, RIKEN Plant Science Center, 4Graduate School of Bioagricultural Science, Nagoya University
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Everroad, R. C., Yoshida, S., Tsuboi, Y., Date, Y., Kikuchi, J., Moriya, S. Concentration of Metabolites from Low-density Planktonic Communities for Environmental Metabolomics using Nuclear Magnetic Resonance Spectroscopy. J. Vis. Exp. (62), e3163, doi:10.3791/3163 (2012).
Environmental metabolomics is an emerging field that is promoting new understanding in how organisms respond to and interact with the environment and each other at the biochemical level1. Nuclear magnetic resonance (NMR) spectroscopy is one of several technologies, including gas chromatography–mass spectrometry (GC-MS), with considerable promise for such studies. Advantages of NMR are that it is suitable for untargeted analyses, provides structural information and spectra can be queried in quantitative and statistical manners against recently available databases of individual metabolite spectra2,3. In addition, NMR spectral data can be combined with data from other omics levels (e.g. transcriptomics, genomics) to provide a more comprehensive understanding of the physiological responses of taxa to each other and the environment4,5,6. However, NMR is less sensitive than other metabolomic techniques, making it difficult to apply to natural microbial systems where sample populations can be low-density and metabolite concentrations low compared to metabolites from well-defined and readily extractable sources such as whole tissues, biofluids or cell-cultures. Consequently, the few direct environmental metabolomic studies of microbes performed to date have been limited to culture-based or easily defined high-density ecosystems such as host-symbiont systems, constructed co-cultures or manipulations of the gut environment where stable isotope labeling can be additionally used to enhance NMR signals7,8,9,10,11,12. Methods that facilitate the concentration and collection of environmental metabolites at concentrations suitable for NMR are lacking. Since recent attention has been given to the environmental metabolomics of organisms within the aquatic environment, where much of the energy and material flow is mediated by the planktonic community13,14, we have developed a method for the concentration and extraction of whole-community metabolites from planktonic microbial systems by filtration. Commercially available hydrophilic poly-1,1-difluoroethene (PVDF) filters are specially treated to completely remove extractables, which can otherwise appear as contaminants in subsequent analyses. These treated filters are then used to filter environmental or experimental samples of interest. Filters containing the wet sample material are lyophilized and aqueous-soluble metabolites are extracted directly for conventional NMR spectroscopy using a standardized potassium phosphate extraction buffer2. Data derived from these methods can be analyzed statistically to identify meaningful patterns, or integrated with other omics levels for comprehensive understanding of community and ecosystem function.
1. Filter Preparation to Remove Extractables
2. Filtration of Sample Material
3. Extraction of Aqueous-soluble Metabolites
4. NMR Spectroscopy and Data Analysis
5. Representative Results
An example of 1H NMR spectra obtained using the above methods are shown in Figure 1. These samples, from two time points of a microcosm experiment show clear differences due to algal metabolic activities. The day 4 spectrum shows considerable abundance of peaks, particularly in the 3-4 ppm range compared to the day 1 sample. These peaks can be attributed to sugars produced by blooming diatoms within the microcosm. In a similar experiment comparing the growth of natural plankton communities in artificial or natural seawater, statistical approaches such as principal component analysis (PCA) score plot derived from binned NMR spectra can be used to show clear metabolic differences between the two treatments (Fig. 2), while the loading plots can identify peaks within the spectra that shape the distribution of the data. Such results can be compared with data from other omics levels, such as from genomic fingerprinting methods (Fig. 3). These NMR peaks can be queried individually (e.g. at the BMRB; http://www.bmrb.wisc.edu/)19, or entire spectra can be analyzed statistically (e.g. with SpinAssign at http://prime.psc.riken.jp/?action=nmr_search)2. In this example, differences between treatments were due to an abundance of peaks in the sugars region (3.39 ppm to 4.04 ppm) of spectra from natural plankton community metabolites, and several peaks characteristic to the artificial seawater communities were tentatively identified as lactate and formate using SpinAssign.
Figure 1. Representative 1H NMR spectra obtained from samples processed using this procedure. Microcosm samples were taken before (day 1) and during (day 4) an intense diatom bloom. NMR experiments were performed on a Bruker DRX-500 with signals normalized to the internal standard peak height (DSS; 0 ppm).
Figure 2. Principal component analysis (PCA) score plot for binned NMR spectra from metabolomes of naturally-derived microbial planktonic communities grown in microcosms with natural (open diamonds) or artificial (black circles) seawater. Clear metabolic differences can be observed in the scatterplot. A loading plot from such an analysis can then be used to identify distinct peaks of importance in the system; these peaks can be further analyzed as needed.
Figure 3. An example of multi-omics analysis combining NMR with genomic data. Community composition based on denaturing gradient gel electrophoresis of 18S (left) and 16S (right) rRNA genes from the same samples as analyzed in Figure 2 also shows distinct microbial community patterns between natural (open diamonds) and artificial (black circles) seawater microcosms. Such correspondence between metabolome and genome from natural systems demonstrates the usefulness of this approach.
The filtration and metabolite extraction method demonstrated here allows for microbial planktonic biomass to be collected in sufficient amount for NMR metabolomics. While only extraction of aqueous-soluble metabolites using KPi and 1D 1H NMR is demonstrated, other extraction solvents and spectroscopic approaches can be used. One useful example is the use of deuterated methanol as a semi-polar solvent, which has been shown to produce superior NMR spectra from heterogeneous samples and is less sensitive to contamination by paramagnetic ions as are found in marine samples15. In such cases, the pellet from the extraction above should be retained for successive extractions. Our previous work has shown the stability of spectra under such incubation times and temperatures and the suitability of direct aqueous extraction for NMR spectroscopy15,20. However researchers may also prefer to modify extraction steps, for example by using a denaturing step to inactivate enzymes prior to extraction, or by using rapid-quenching methods that differ from simply freezing the cells as shown here. Additionally, while the methods presented here are best suited for observing proportional changes in metabolites across treatments, if desired, filters can be pre-weighed and then weighed again after sample filtration and lyophilization to obtain dry weight, or the volume of sample filtered can be used to obtain more quantitative metabolite source data.
Ultimately, the utility of NMR for planktonic samples is constrained by the amount of mass that can be successfully collected; even high-density cultures may require large volumes (>100 ml) to obtain sufficient dry biomass. However, within an experimental framework, stable isotope labeling in micro- or mesocosm experiments, 2D 1H-13C heteronuclear single quantum coherence (HSQC) approaches are possible. Further, we have additionally used 47-mm filters and 5-ml polypropylene tubes to increase the amount of biomass that can be collected for extraction, as even larger volumes may be necessary (i.e. > 2 L) for natural communities from, e.g. oligotrophic waters where cell densities are low.
Filtration is advantageous over centrifugation as it is our observation that some smaller microbial taxa (particularly small heterotrophic bacteria) often do not pellet well. Filtration can be performed manually in the field, and the volumes filtered are limited only by the number of filters available. Additionally, excess media or water can be removed in this manner, and the samples can be rinsed if needed. Of course, even with filtration, the community collected will be limited to a size fraction down to the filter cutoff, which in this example is 0.22 μm.
No conflicts of interest declared.
This research was supported in part by Grants-in-Aid for Scientific Research for challenging exploratory research (J.K.), and Scientific Research (A) (J.K. and S.M.) from the Ministry of Education, Culture, Sports, Science, and Technology, Japan. A RIKEN FPR fellowship (R.C.E.) provided additional support. The authors express their gratitude to Drs. Eisuke Chikayama, Yasuyo Sekiyama and Mami Okamoto for technical assistance with NMR and statistical analyses.
|0.22 Ám hydrophilic Durapore PVDF filters, 25 mm||EMD Millipore||GVWP02500|
|Microanalysis Filter Holder, 25 mm, fritted glass support||EMD Millipore||XX1002500|
|3-place manifold, 47 mm, stainless steel||EMD Millipore||XX2504735|
|KH2PO4||Wako Pure Chemical Industries, Ltd.||169-04245|
|K2HPO4||Wako Pure Chemical Industries, Ltd.||164-04295|
|Deuterium oxide, 2H > 90%||Campridge Isotope Laboratoties||DLM-4|
|Automill||Tokken||TK-AM4||Stainless steel crushers included|
|Thermomixer comfort||Eppendorf||5355 000.011|
|NMR||Bruker Corporation||DRX-500 with 5 mm-TXI probe|
|Spectral binning tool||Originally developed||FT2DB||https://database.riken.jp/ecomics/|
|Metabolite annotation tool and database||Originally developed||SpinAssign||http://prime.psc.riken.jp/?action=nmr_search|