Tracing carbon fixation in phytoplankton—compound specific and total C incorporation rates

Measurement of total primary production using C incorporation is a widely established tool. However, these bulk measurements lack information about the fate of fixed carbon: the production of major cellular compounds (carbohydrates, amino acids, fatty acids, and DNA/RNA) is affected by for instance nutrient availability as their C:N:P requirements differ. Here, we describe an approach to combine established methods in gas chromatography/isotope ratio mass spectrometry (GC/C-IRMS) and recently developed methods in liquid chromatography/IRMS (LC/IRMS) to trace stable isotope incorporation into neutral carbohydrates, amino acids, and fatty acids, and compare their production to total carbon fixation rates. We conducted a trial study at stations in the North Sea where different nutrients were limiting. There was variation in the fate of fixed carbon at these sites. The majority of fixed carbon (64–71%) was incorporated into neutral carbohydrates, followed by amino acids (19–32%) and fatty acids (4–9%). The sum of carbon fixation into these three fractions accounted for 81–116% of total carbon fixation. Pand N-limitation increased the biosynthesis of storage lipids and storage carbohydrates while N-limitation decreased synthesis of amino acid proline with a concurrent increase in glutamic acid1 glutamine. This new approach provides the capability to determine direct effects of resource limitation and the consequences for the physiological state of a phytoplankton community. It may thereby enable us to evaluate the overall quality of phytoplankton as a food source for higher trophic levels or trace consumption of phytoplankton through the food web. Approximately half of the global net primary production is performed in the ocean (Field et al. 1998) and phytoplankton forms the basis of most food webs in the sea. Methods to estimate primary production have been around for decades and remote sensing as well as several experimental approaches are currently in use (Cullen 2001). Widely used methods for determining rates of primary production in the field are based on the incorporation of carbon isotopes, both radioactive (C) and stable (C), into phytoplankton biomass (Steeman-Nielsen 1952; Montoya et al. 1996). A wealth of data is available on primary production rates in different areas (Gosselin et al. 1997; Carpenter et al. 2004; Shiozaki et al. 2010), over different time scales (Karl et al. 1996; Gallon et al. 2002) and from culture studies (Degerholm et al. 2006; Wannicke et al. 2009), providing a valuable tool to estimate total productivity of a system. However, total primary production rates do not give any information on the intracellular fate of the fixed carbon and, therefore, the nutritional value of it to higher trophic levels. It is well known that carbon uptake and consequently phytoplankton growth are regulated by many factors such as light or nutrient availability. Phytoplankton stressed by too much light or too little nutrient availability react by storing carbon in the form of storage carbohydrates and/or triglycerides (Granum et al. 2002; Borsheim et al. 2005). Both of those compounds are carbon rich but do not contain nitrogen (N) or phosphorus (P), causing a shift in phytoplankton C:N:P ratios and a decline in the nutritional value of phytoplankton to consumers (Sterner et al. 1993; Plath and Boersma 2001). The diversity in nutrient N:P ratios faced by marine phytoplankton led to the development of models to predict changes in the growth strategy of phytoplankton (Klausmeier et al. 2004). Low cellular N:P ratios would be present in phytoplankton adapted to high growth rates, which have the resources to invest in growth machinery high in both N and P (e.g., ribosomal RNA [rRNA]) (Falkowski 2000). In contrast, to sustain growth under low resource availability, phytoplankton invests in resource acquisition machinery (pigments and proteins), which is rich in N but mostly lacks P, resulting in high N:P ratios (Geider and LaRoche 2002). Confirming those strategies in natural phytoplankton communities and changes between them caused by changes in *Correspondence: julia.grosse@nioz.nl 288 LIMNOLOGY and OCEANOGRAPHY: METHODS Limnol. Oceanogr.: Methods 13, 2015, 288–302 VC 2015 Association for the Sciences of Limnology and Oceanography doi: 10.1002/lom3.10025 resource availability is challenging and investigations on the level of individual compounds have been rare until a few years ago and are mainly based on changes in compound concentrations following the addition or reduction of nutrients (Granum et al. 2002; Mock and Kroon 2002). Detection of significant changes in the compound concentrations requires long-term incubations (several days to weeks), which can simultaneously cause undesired changes in the phytoplankton community and may not lead to field relevant results (Beardall et al. 2001). Charpin et al. (1998) and Su arez and Mara~ n on (2003) used the incorporation of C to quantify carbon allocation into different macromolecule groups (total lipids, proteins, and polysaccharides), but due to for instance special regulations of handling radioactive material, this method is not widely applied. In recent years, the advances in compound specific stable isotope analysis (CSIA) by either gas chromatography (GC) or liquid chromatography (LC) in combination with isotope ratio mass spectrometry (IRMS) have made it possible to obtain specific isotope information of a wide range of compounds directly from complex mixtures. This opens possibilities to use C stable isotopes in the same way as they are already used for total primary production measurements (bulk) but to study phytoplankton communities on a more detailed compound specific level by following the photosynthetically fixed carbon into macromolecules such as individual fatty acids, amino acids, and carbohydrates. Many studies are already available on the incorporation of carbon into a particular fraction of fatty acids, the phospholipid derived fatty acids (PLFA), to determine the activity or composition of specific groups of phytoplankton or bacteria (Middelburg et al. 2000; Van Den Meersche et al. 2004; Dijkman et al. 2010). Separation of individual fatty acids is performed on a GC and, therefore, fatty acids have to be derivatized. As only one extra carbon has to be added per fatty acid, it makes corrections for natural abundance dC values straightforward. However, requirements of heavy derivatization of carbohydrates and amino acids for separation on a GC make determination of dC natural abundance studies prone to errors (Rieley 1994) and require extensive corrections. Therefore, the GC/C-IRMS method is commonly used for tracer studies with C and N incorporation into amino acids (Veuger et al. 2007; Oakes et al. 2010) as well as food web studies using natural abundance of N in amino acids (McCarthy et al. 2013). The recently developed LC/ IRMS methods make the derivatization of carbohydrates and amino acids unnecessary and are being introduced to a wide range of fields including geochemistry, nutrition, paleodiet, ecology, forensics, and medicine (Godin et al. 2007). Currently, the majority of studies focus on the natural abundance of C in those compounds, usually used to identify sources and only a limited number of publications included C amended tracers to investigate carbon incorporation into different compounds (McCullagh et al. 2008; Oakes et al. 2010; Miyatake et al. 2014). In all cases, carbon incorporation was mainly determined for one macromolecule group, for example, amino acids or PLFAs, and information is lacking on how carbon is simultaneously distributed between different pools of macromolecules. Combining these methods to determine fatty acid, amino acid, and neutral carbohydrate synthesis by C labeling would give insight into the biochemical fate of fixed carbon and the physiological state of the phytoplankton community in terms of resource limitation. In this study, we show how a combination of established GC/C-IRMS and recently developed LC/IRMS methods (Fig. 1) can be used to identify the composition and biosynthesis of individual fatty acids, amino acids, and carbohydrate pools of natural phytoplankton communities. We modified existing protocols to make them applicable to marine phytoplankton and added clean up steps to reduce interference from impurities in the LC-methods. By combining the GC and LC approaches with C measurements on an IRMS, the biosynthesis rates of these individual compounds can be calculated. Overall, these three major macromolecule groups can be examined in detail and be compared with bulk measurements of primary production. This makes it possible to provide an overview of the ability of phytoplankton to allocate carbon fixed through photosynthesis into different functional groups of macromolecules and to study how phytoplankton copes with differences in resource availability. Materials and procedures Field experiment For the trial experiment, we chose three sites in the North Sea (Fig. 2) with different physical and chemical features. The Coastal Station is only four kilometers offshore with a water depth of eight meters and, therefore, heavily influenced by runoff from land, mainly through nutrient-rich discharge from the river Rhine. The Oyster Ground is a relatively deep station (46 m) and stratified during summer. The Dogger Bank station is shallower (28 m) and complete mixing of the water column is possible year around. Labeling of phytoplankton with C-bicarbonate A labeling experiment with stable isotope tracer Clabeled bicarbonate was performed during a North Sea cruise on board the R/V Pelagia in May 2012. For the experiments, subsurface water (seven meters) was obtained with Niskin bottles, transferred to 10 L carboys and enriched with Csodium bicarbonate (99% C). The final labeling concentration reached 1.5–2% C of the ambient dissolved inorganic carbon (DIC) concentration. To determine the absolute C enrichment in DIC, 10 mL of sample were sealed in a crimp vial without gas bubbles, a 2 mL helium headspace was created, and after acidification the headspace was analyzed for CO2 concentration and C-content by a Flash EA 1112 Series elemental analyzer (EA) coupled via a Conflo III Grosse et al. C uptake into macromolecules