Intact polar diacylglycerol biomarker lipids isolated from suspended particulate organic matter accumulating in an ultraoligotrophic water column
Introduction
Fatty acids (FAs) have a long history as tracers of biological activity in aquatic environments. Their sources in the environment are, however, often ambiguous due to the production of common structures by multiple organisms, including different groups of algae (Lang et al., 2011). For this reason, the use of intact polar diacylglycerol lipids (IP-DAGs), the parent compounds of FAs, has been proposed as a means of achieving an additional layer of metabolic, and in some cases even taxonomic, specificity as compared with examination of total FAs alone (Sturt et al., 2004). The IP-DAG structure, defined by both the head group and associated FAs, can reveal not only the potential phylogenetic associations of source organisms (Schubotz et al., 2009) but also the conditions under which they were produced, such as nutrient limitation (Van Mooy et al., 2009). In addition, because the polar head group is thought to be hydrolyzed relatively quickly after cell death, particularly under oxygenated conditions (White et al., 1979, Harvey et al., 1986), IP-DAGs can be assumed to represent living or recently living biomass. This makes them potentially useful biological tracers of ecosystem processes, including rapid exchange between living and detrital pools of organic matter (OM).
Planktonic IP-DAGs have only recently gained prominence as biomarkers for studying marine biogeochemical processes. Three major groups are thought to be commonly produced by marine plankton in open ocean environments (Van Mooy et al., 2009, Van Mooy and Fredricks, 2010, Popendorf et al., 2011a, Popendorf et al., 2011b): (i) three types of phospholipids, phosphatidylglycerol (PG), phosphatidylethanolamine (PE) and phosphatidylcholine (PC), (ii) three types of glycolipids, monoglycosyl-diacylglycerol (MGDG), diglycosyldiacylglycerol (DGDG) and sulfoquinovosyl-diacylglycerol (SQDG) and (iii) three types of betaine lipids, diacylglyceryl trimethylhomoserine (DGTS), diacylglyceryl hydroxymethyltrimethylalanine (DGTA) and diacylglyceryl carboxyhydroxymethylcholine (DGCC). A fourth glycolipid variation is glucuronosyldiacylglycerol (GADG), recently observed in strains of the heterotrophic SAR11 clade (Carini et al., 2015) and in the Alphaproteobacterium Erythrobacter sp. NAP1 (Sebastián et al., 2015) when each was grown under P starved conditions. Structures are shown in Fig. 1.
Studies have also attempted to establish associations among particular head group structures and marine microbial groups, and have suggested that the IP-DAG composition varies among phytoplankton and heterotrophic bacteria in surface waters (Schubotz et al., 2009, Van Mooy and Fredricks, 2010, Brandsma et al., 2012). As a group, the glycolipids are commonly referred to as “chloroplast lipids” because they are frequently associated with the thylakoid membranes of photosynthetic organisms, including both cyanobacteria and eukaryotic phytoplankton (Wada and Murata, 1998, Sato, 2004;). Furthermore, a recent study using 13C-labeled substrates proposed that SQDG in particular appears to be exclusively produced by photosynthetic organisms in the surface ocean (Popendorf et al., 2011a, Popendorf et al., 2011b), but the sources of others, such as MGDG, are more difficult to define and may be produced by photosynthetic organisms and heterotrophic bacteria (Sebastián et al., 2015). Experiments with these 13C-labeled substrates also supported previous indications that the betaine lipids are likely produced mainly by eukaryotic phytoplankton (Kato et al., 1996, Popendorf et al., 2011a, Popendorf et al., 2011b), at least in marine surface waters, although some bacterial production has been observed in cultures of heterotrophic bacteria under P-limited conditions (Benning et al., 1995, Sebastián et al., 2015) and in anoxic regions of the water column (Schubotz et al., 2009). As for the phospholipids, PG and PE are more commonly attributed to heterotrophic bacteria, but PG in particular is also found in cyanobacteria, as it has been shown to be an essential component of the thylakoid membrane (Sato et al., 2000). Similarly, PC likely can have both a bacterial source and a eukaryotic source (Kato et al., 1996, Popendorf et al., 2011a, Popendorf et al., 2011b), although it has not been found in cyanobacteria (Van Mooy et al., 2006).
Typically, IP-DAGs are separated using high performance liquid chromatography (HPLC) and detected and identified using electrospray ionization mass spectrometry (ESI-MS) techniques (e.g. Sturt et al., 2004). The polar lipid extracts of environmental samples can be extremely complex and IP-DAGs are often present at relatively low concentration. Thus, manually extracting and analyzing individual mass spectra to definitively assign IP-DAG structures from complex samples can be time consuming.
Molecular networking is an analytical strategy that can greatly facilitate this task. Molecular networks are visual representations of structurally similar compounds, constructed on the basis of the similarity in their tandem MS fragmentation patterns (Watrous et al., 2012, Yang et al., 2013). Similar structures therefore cluster together and can be assigned on the basis of their proximity to the spectra of standard compounds. Each of the nine major IP-DAG classes commonly observed in marine samples (Fig. 1) has a characteristic fragmentation pattern (Sturt et al., 2004, Schubotz et al., 2009, Van Mooy and Fredricks, 2010) making them ideal candidates for analysis using this approach. In addition to aiding in identification, the resulting structural diversity, as well as the relative abundance of individual structures, can be visually compared between samples.
In the first application of molecular networking to marine particulate samples, we sought to (i) investigate the evolution of IP-DAG structural diversity in suspended particulate OM (POM) with depth in an oligotrophic marine water column, and (ii) demonstrate the utility of molecular networking to rapidly identify, classify and visualize differences in IP-DAG diversity in a complex dataset where individual compounds of interest are in very low abundance. An additional motivation was to test the feasibility of utilizing IP-DAGs in suspended POM as tracers for the biomass of small photosynthetic organisms from the surface through the water column into the deep ocean. As noted above we chose to focus on IP-DAGs over other commonly employed biomarkers like FAs because of the greater taxonomic specificity afforded by examining head group structures (Sturt et al., 2004), their relative lability and because there was precedent for finding IP-DAGs in deeper water (Close et al., 2014). In addition, the head groups of IP-DAGs can provide information about environmental conditions experienced by producing organisms, such as P limitation (Van Mooy et al., 2006, Sebastián et al., 2015). To initially seed the molecular network with relevant classes of IP-DAGs we used available laboratory cultures of phytoplankton expected to be present in the environment of interest. The cultures further served as a tool to connect the IP-DAG dataset to the major phytoplankton groups identified in the same field samples from 16S, 18S and plastid 16S phylogenetic affiliations, in order to assign tentative sources to some IP-DAGs found in suspended POM.
Our data show that SQDG, previously implicated as a biomarker for photosynthetic organisms, does not persist to depth in the suspended POM reservoir. Other glycolipids, which could have mixed heterotrophic and autotrophic sources, show a similar pattern. However, some MGDG and betaine lipids were detected in deeper samples, which probably identifies the overall shift to a bacterial dominated IP-DAG contribution to the suspended POM reservoir in the dark ocean at this site. In contrast, the phospholipids PE and PG were present throughout the water column, as would be expected if heterotrophic bacteria were the major contributors of these lipids to the suspended particulate reservoir. Paired analysis of 16S and 18S based microbial diversity on the same particles confirmed the important photosynthetic role of Prochlorococcus spp. and the picoeukaryote Pelagomonas spp., potentially identifying the major contributors to SQDG and betaine lipids found in shallow POM samples.
Section snippets
Sample collection
All environmental samples were collected on the Microbial Oceanography of the Tonga Trench (MOTT) cruise on the R/V Revelle in September 2012, from a water column station in the northern part of the Tonga Trench (16°38.5′ S, 172°12.0′ W, water depth 9100 m). Depth profiles of the water column were obtained via conductivity, temperature and depth (CTD) measurements and dissolved O2 concentration was measured at both stations with a Sea-Bird Electronics oxygen probe validated by shipboard Winkler
IP-DAG analysis of cultured picophytoplankton
A summary of IP-DAG classes and the number of associated structures in each culture is provided in Fig. 2 and a full list of all IP-DAGs in each culture can be found in Table A.3. Analysis of the cyanobacteria Prochlorococcus and Synechococcus demonstrated that both produce the same major IP-DAG classes (PG, MGDG, DGDG and SQDG). Prochlorococcus, however, produced FAs such as 19:1, whereas Synechococcus appears to use only combinations of C14, C16 and C18 FAs, either saturated or
Discussion
The structural diversity of intact polar lipids, such as the IP-DAGs, and their potential in identifying taxonomic diversity, activity and nutrient status, is becoming more commonly examined in a variety of marine environments ranging from the surface ocean (e.g. Van Mooy et al., 2006, Brandsma et al., 2012) to deep subsurface sediments (Lipp and Hinrichs, 2009). However, few studies of planktonic IP-DAGs have examined depth profiles of lipid diversity extending into the dark ocean (Close et
Conclusions and future directions
This study examined a single depth profile of suspended POM collected from the Tonga Trench region of the western South Pacific Ocean, and therefore the observations must be interpreted in this limited context. This is the first time, however, that this environment has been sampled in this manner. The analysis describes the deepest water column IP-DAG dataset to date, and the application of the molecular networking tool to identify IP-DAGs in this complex environmental dataset highlights the
Acknowledgements
We thank B. Palenik (SIO), M. Saito (MIT-WHOI) and T. Coale (UCSD/JCVI) for contribution of cultures, and A. Rabines (JCVI) for assistance with DNA and sample processing. We thank A. Sessions, F. Schubotz and an anonymous reviewer for comments that greatly helped improve the manuscript. The MOTT 2012 cruise to the Tonga Trench was funded by the University of California Ship-Funds Program. The work was also funded in part by grants to A,E,A. from the Gordon and Betty Moore Foundation (GBMF3828)
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