Linking successional development of soils in the Maritime Antarctic to belowground processes using a combined stable carbon isotope and metabolomics approach
Research on ecosystem functioning under changing abiotic conditions have been under increasing attention of the scientific commnunity since decades. Maritime Antarctica is among the sensitive areas, which are severely affected by climate change. Global warming in the Antarctic Peninsula with temperatures rise in about 0.06 0C y-1 within the past 45 years has accelerated rapid glacier retreatment forming temporal gradients of soil development region (Convey, 2003; Cook et al., 2005; Sancho et al., 2007). The changes in abiotic parameters reflected in ecosystem dynamics and functioning, and particularly, in vegetation succession are closely linked to soil formation.
Over the last three decades, significant and relatively rapid colonization of the ice-free soils by two vascular plant species (Deschampsia Antarctica and Colobanthus quitensis) has been recorded, indicating biological responses to rapid environmental change in this region (Gerighausen et al., 2003; Parnikoza et al., 2009). Coincidently, due to the fostered interaction to soils, plants are also able to modulate soil development and have a significant impact to ecosystem carbon balance at relatively short time scale.
In the past decade the paradigm emerged that above- and belowground processes are interconnected, e.g. plant photosynthesis is strongly linked with soil respiration. Recently gained carbon can be rapidly transferred belowground, fuelling the activity of microorganisms involved in decomposition of soil organic matter and mineral weathering, and influencing soil CO2 efflux rates on short-time scales (from hours to days) (Högberg and Read, 2006; Shibistova et al., 2012).
The features and different patterns of carbon allocation for numerous plants and ecosystems have been well documented, but such studies for Antarctic ecosystems, occurring in harsh conditions are lacking. Little is also known about the contribution of bacteria and fungi to decomposition of different soil carbon pools with different turnover rates in these soils, which is of utmost importance for the prediction of the future feedback of the Antarctic carbon balance to climate change. With this respect, it appears to be important to make a step in closing a gap in our knowledge on the impact of microbial and plant sources on soil organic matter composition of these soils.
Soil metabolomics is a powerful tool for comprehensive identification and quantification of all metabolites present in a biological sample (Coucheney et al., 2008), and is increasingly used to examine present interactions between organisms and the environmental conditions (Mashego et al., 2007; Coucheney et al., 2008), and to estimate the response of biological system to environmental modifications (Fiehn, 2002; Ossipov et al., 2014).
We were studying this on chronosequences, as they provide an ideal opportunity to study the impact of vegetation on the processes of soil formation. At Maritime Antarctica, glacier retreat chronosequences define sites that represent an increasing level of trophic complexity as a result of vegetation development. The goal of our study was to identify the in vivo biological activity and function in these soils along soil development. We approached this by following soil horizon formation, quantifying soil organic carbon stocks and carbon exchange with the atmosphere along a vegetation gradient at King George Island combining field CO2 flux measurements, soil chemical analyses, 13C in situ labeling and molecular methods (PLFA and metabolomics). Particularly, we aimed to compare the metabolic pools in the soils to reveal the impact of differences in the vegetation community composition and its possible link to the microbial population structure and activity.
Materials and Methods
We have chosen a rock outcrop (11-71 m asl) of the Collins glacier, representing a deglaciation chronosequence ranging from <200 yr B.P. to ~7200 yr B.P., with pronounced succession from algaea and cyanobacteria (i.e., bare soil) over lichens and mosses to the evolutionary younger vascular plant Deschampsia antarctica.
We applied a non-steady state chamber technique to measure carbon exchange between atmosphere and soil interphase. CO2 fluxes were measured in situ using a portable infrared gas analyser (LI-COR 6400, Lincoln, NE, USA), coupled with a custom-made dynamic closed chamber within the vegetational gradient spanning bare soils, mosses, a mixture of mosses and D. antarctica, and pure D. antarctica. The GPP (Gross Primary Production) rates were evaluated from consequent measurements of net CO2 exchange (NEE) with transparent and soil CO2 efflux (SR) by opaque chambers, as following: GPP = NEE – SR and expressed in μmol m-2 s-1.
A short-term in situ 13CO2 pulse labeling of was carried out on February, 3, 2014 in Antarctica as described by Shibistova et al, (2012). The plant, soil and gas samples were collected daily within the chasing period. The soil 13CO2 was collected by NaOH absorption method followed by SrCl2 precipitation. The stable carbon isotope composition was analyzed for leaves, roots, NLFA (neutral lipid fatty acids) and PLFA (phospholipid fatty acids), and soil- and plant derived CO2 was determined by a an Elementar Isoprime 100 IRMS (Isoprime Ltd., Cheadle Hulme, UK) coupled to an Elementar vario MICRO cube EA C/N analyzer (Elementar Analysesysteme GmbH, Hanau, Germany).
We used the modified method of Gunina et al. (2014) to analyze PLFA in the soils collected in the field and stabilized in RNAlater® to prevent sample degradation (Schnecker et al., 2012). Lipids were extracted twice using a chloroform-methanol-citrate buffer (1:2:0.8 v/v/v), separated by solid phase extraction into glycolipids, neutral lipids, and phospholipids, hereafter analyzed by gas chromatography using an Agilent Technologies 7890A GC system equipped with a 60m Zebron capillary GC column (0.25mm diameter and 0.25µm film thickness; Phenomenex, Germany) and a flame ionization detector, using He as a carrier gas. Nonadecanoic acid (FA 19:0) was used as an internal standard. Seventeen PLFA were analyzed in total and the sum of all PLFA was used as a proxy of the microbial biomass and expressed as PLFA biomass. After conducting a principal components analysis (PCA) on data and relating the results to literature data (Zelles, 1999; Ruess and Chamberlain, 2010; Frostegård et al., 2011), we used the following markers to distinguish microbial groups: i15:0, a15:0, i16:0, i17:0, a17:0 and 18:1ω9c were used as markers for gram-positive bacteria (Gram+), 16:1ω5c, 18:1ω7c and Cy19:0 as markers for gram-negative bacteria (Gram–), 10Me16:0 to identify actinomycetes, 18:2ω6,9 as a fungal marker, 20:4ω6c to detect protozoa, and 14:0, 15:0, 16:1ω7c, 17:0, and18:0 as markers for unspecific bacteria.
The metabolites analysis was performed according to Ossipov et al. (2014). In brief, soils were collected in the field and stored frozen prior to analyses. In the laboratory, the samples were evaporated in the vacuum concentrator (Concentrator 5301, Eppendorf AG, Germany). After extraction and purification, followed by derivatisation, TMS derivatives of soil metabolites were transferred into an Perkin-Elmer autosampler vials with 0.15-mL glass inserts, closed by caps with septa, and analyzed with a Perkin-Elmer GC-MS system (GC Autosystem XL with TurboMass Gold quadrupole mass spectrometer, Norwalk, CT, USA). Mass spectrometer was used in the electron ionisation mode (EI+) and ions were generated by a 70 eV electron beam. The data acquisition rate was set at 0.2 s, with a 0.1 s inter-scan delay and the recorded mass range 50 – 620 m/z. The column was a Perkin-Elmer capillary column (PE-5MS, 30 m, 0.25 mm i.d., film 0.25 µm) and helium was used as a carrier gas with a flow rate 1.0 mL/min. The injection volume of metabolite derivatives was 2.0 µL and the split ratio 20:1. The injector temperature was 290°C and the inlet line and the MS source were held at 300°C and 230°C, correspondingly. A series of n-alkanes (C8-C20 and C10-C40, Fluka) were also analyzed to allow calculation of retention index (RI) (Kopka et al., 2005). Full scan output GC-MS files of all samples were converted into NetCDF format and an untargeted metabolomics approach was applied to process the data. MetAlign software (was used to extract and align all recorded masses.
Results and Discussions
Our study revealed that even under extreme environmental conditions, the appearance of higher plants was leading to the formation of well-developed soil, with high contents of organic carbon, with a relatively high rate of CO2 soil efflux, and providing clear evidence of photosynthetic activity.
Along this chronosequence, there was a clear gradient of increasing formation of pedogenic minerals with increasing soil age. The development of a cryptic A horizon to well developed and increasingly thick O and A horizons at the older sites reflected organic matter accumulation from 0.2 kg m-2 at the bare soil to 3.6 kg m-2 under D. antarctica. An increasing photosynthetic activity from algae and cyanobacteria to D. antarctica was also mirrored by increasing soil CO2 efflux rates along the chronosequence from 0.2 ± 0.1 to 2.8 ± 0.9 µmol m-2 s-1. There was a strong temperature dependence of the soil respiration.
Isotope tracer techniques gave us the opportunity to follow carbon fluxes in the plant-soil system in situ. It has been found, that more than 15% of recently assimilated carbon was transferred belowground, of which approximately 2% of assimilated 13C was stored in roots within the chasing period. Carbon flow into soil fungi PLFA at adhering soil under D. antarctica was already recorded at the day 3 after labeling by a prominent 13C peak, whereas 13C excess in NLFA was steadily increasing during the chasing period. In contrast, bacterial PLFAs did not demonstrate surficial tracer incorporation, despite of higher abundance of bacteria in rhizosphere. This suggests that rather not bacteria, but fungi preferentially and faster utilize the recently assimilated low molecular compounds allocated to the soil. This may bring a new insight to the dominating paradigm on distinct niching and specialization within decomposers society.
The metabolomics approach was applied to study the link between the successional stage of soils and its biological activity in vivo. Our soil metabolome database included 89 samples (observations) and 386 metabolites (variables). Application of multivariate statistics (SIMCA+) allowed selecting 57 metabolites as potential markers discriminating the soil horizons. Comparison of retention indexes (RIs) and mass spectra of the individual peaks with data from libraries allowed identifying of 86 metabolites (including some isomers). Among the identified low-molecular compounds carbohydrates, organic acids, alcohols and glycerides, lipophilic compounds (mainly alconoic acids) and sterols were detected. The identified carbohydrates were represented mainly by mono- (i.e., glucose, galactose, ribose and fructose) di- (i.e., maltose, melibiose, and trehalose) and trisacharides (raffinose and maltotrilose). Carboxylic acids (succinic, ethanedioic and azelaic) were found in all groups of samples.
The soil samples represent a complex mixture of metabolites with different chemical properties, concentrations and origin: plant and microbial derived compounds. The organic top-soils from both sites were characterized by high contents of metabolites, with prominent decrease of their relative abundances with soil depth. In most cases, the source of the metabolite could not be determined precisely as far as the most of the low molecular compounds are ubiquitous and inherently involved to metabolic cycles of plants and microorganisms. However, we identified some specific compounds, which could serve as specific biomarkers for different microbial groups. The soils sampled under vascular plant Deschampsia antarctica revealed the impact of the high plants on the soil organic matter, containing significantly higher amounts of carbohydrates and amines, as well as oleanolic acid - the basic oleanane-type triterpene, presumably as a result of root exudation.
We suggest, that metabolomics is a promising approach to assess the biological activity of soil in vivo and to distinguish of the contribution of plants and microorganisms to soil formation processes. Combined with other molecular studies (e.g. microbial biomarkers) and stable isotopes technique, it might been used as a powerful tool that yields additional information on the soil organic metter decomposition and thus the fate of assimilated carbon belowground.
Convey, P., 2003. Maritime Antarctic climate change: signals from terrestrial biology. In: Domack, E., Burnett, A., Leventer, A., Convey, P., Kirby, M., Bindschadler, R. (Eds.), Antarctic Peninsula.
Cook, A.J., Fox, A.J., Vaughan, D.G., Ferrigno, J.G., 2005. Retreating glacier fronts on the Antarctic Peninsula over the past half-century. Science 308, 541-544.
Coucheney E, Daniell TJ, Chenu C, Nunan N. 2008. Gas chromatographic metabolic profiling: A sensitive tool for functional microbial ecology. J.Microbiol.Methods 75(3):491-500.
Fiehn, O., Wohlgemuth , G., Lee, D.Y., V, T., Moon, S., Nikolau, B. 2008. Quality control for plant metabolomics:reporting MSI-compliant studies. The Plant Journal 53, 691–704.
Frostegård, Å., Tunlid, A., Bååth, E., 2011. Use and misuse of PLFA measurements in soils.
Soil Biol. Biochem. 43, 1621–1625. doi:10.1016/j.soilbio.2010.11.021
Gerighausen, U., Bräutigam, K., Mustafa, O., Ulrich-Peter, H., et al., 2003. Expansion of vascular plants on an Antarctic Island a consequence of climate change? In: Huiskes, A.H.L. (Ed.), Antarctic Biology in a Global Context. Backhuys Publishers, Leiden.
Gunina, A., Dippold, M.A., Glaser, B., Kuzyakov, Y., 2014. Fate of low molecular weight organic substances in an arable soil: From microbial uptake to utilisation andstabilisation. Soil Biol. Biochem. 77, 304–313. doi:10.1016/j.soilbio.2014.06.029
Högberg P, Read D (2006) Towards a more plant physiological perspective on soil ecology. Trends Ecol Evol 21: 548–554.
Kopka J, Schauer N, Kruger S, Birkemeyer C, Usadel B, Bergmu¨llerE, Do¨rmann P,Weckwerth W, Gibon Y, Stitt M, Willmitzer L,Fernie A, Steinhauser. D 2005. e78cc2be0fGMD@CSB.DB: theGolmMetabolome Database. Bioinformatics 21:1635–1638.
Ossipov, V., Klemola, T., Ruohomaki, K., Salminen, J-P. 2014. Effects of three years’ increase in density of the geometrid Epirrita autumnata on the change in metabolome of mountain birch trees(Betula pubescens ssp. czerepanovii). Chemoecology 24, 201–214
Parnikoza, I., Convey, P., Dykyy, I., Trakhimets, V., Milinevsky, G., Tyschenko, O., Inozemtseva, D., Kozeretska, I., 2009. Current status of the Antarctic herb tundra formation in the central Argentine Islands. Glob. Change Biol. 15, 1685-1693.
Rinnan, R., Bååth, E. 2009. Differential Utilization of Carbon Substrates by Bacteria and Fungi in Tundra Soil. Applied and Environment. Ecology 11, 3611-3620.
Ruess, L., Chamberlain, P.M., 2010. The fat that matters: Soil food web analysis using fatty
acids and their carbon stable isotope signature. Soil Biol. Biochem. 42, 1898–1910. doi:10.1016/j.soilbio.2010.07.020
Sancho, L.G., Green, T.G.A., Pintado, A., 2007. Slowest to faster: Extreme range in lichen growth rates supports their use as an indicator of climate change in Antarctic. Flora-Morphology, Distribution, Functional Ecology of Plants, 202, 667-673.
Schnecker, J., Wild, B., Fuchslueger, L., Richter, A., 2012. A field method to store samples from temperate mountain grassland soils for analysis of phospholipid fatty acids, Soil Biology and Biochemistry, doi:10.1016/j.soilbio.2012.03.029.
Shibistova O, Yohannes Y, Boy J, Richter A, Wild B, et al. (2012) Rate of Belowground Carbon Allocation Differs with Successional Habit of Two Afromontane Trees. PLoS ONE 7(9): e45540. doi:10.1371/journal.pone.0045540.
Zelles, L., 1999. Fatty acid patterns of phospholipids and lipopolysaccharides in thecharacterisation of microbial communities in soil: a review. Biol. Fertil. Soils 29, 111–790 129. doi:10.1007/s003740050533.