Lipid stoichiometry and biomarkers reflect microbial acclimation and nutrient stress across the Atlantic Ocean

Lipid stoichiometry and biomarkers reflect microbial acclimation and nutrient stress across the Atlantic Ocean | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Lipid stoichiometry and biomarkers reflect microbial acclimation and nutrient stress across the Atlantic Ocean Daniel Lowenstein, Henry Holm, Helen Fredricks, Benjamin Van Mooy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8022751/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The stoichiometry of particulate organic matter (POM) in the ocean influences the global carbon, nitrogen, and phosphorus cycles, but elemental distributions within macromolecule classes are not well constrained. Using publicly available datasets of lipid abundances, nutrient concentrations, and POM stoichiometry, we conduct the first basin-scale survey of lipid stoichiometry along a north-south transect spanning the western Atlantic Ocean from ~ 40°S to ~ 55°N, and demonstrate that surface ocean lipid stoichiometry is highly variable, is primarily linked to phosphate (P) availability, and is strongly correlated with POM stoichiometry. We evaluate lipid biomarkers of microbial nutrient stress and find they are not uniformly in agreement (i.e. some indicate P-stress in regions where others do not). To that end, we describe a novel polar lipid class, diacylglycerylcarboxyhydroxysulfocholine, thus far detected only in the coccolithophore genus Gephyrocapsa , potentially indicative of nitrogen (N) and phosphorus stress. We also advance three new biomarkers of nutrient stress, specific to oligotrophic heterotrophic bacteria and to the globally significant coccolithophore, G. (ex Emiliania) huxleyi . We find they effectively elucidate a transition from proximal N- to P-stress in the Atlantic Ocean. Earth and environmental sciences/Ocean sciences/Marine chemistry Earth and environmental sciences/Ecology/Biogeochemistry/Element cycles Earth and environmental sciences/Ecology/Biooceanography/Microbial biooceanography Figures Figure 1 Figure 2 Figure 3 Introduction Since the relationship was first discovered in marine particulate organic matter (POM) almost seventy years ago, the canonical “Redfield” ratio of 106 carbon (C) to 16 nitrogen (N) to 1 phosphorus (P) atoms has undergone significant revision. Though an ocean-scale view yields an average ratio of ~ 106:16:1, the figure belies significant heterogeneity. Inter- and intra-specific variations in elemental quota, community spatial heterogeneity, and circulation processes all influence the global averages that Redfield, Ketchum, and Richards illuminated 1 – 5 . A portion of this variation is due to changing cellular proportions of macromolecules like lipids, proteins, and carbohydrates; up- or downregulation of these macromolecule groups results in variations in bulk stoichiometry across small and large spatial scales 6 , 7 . However, though ocean models and studies of particulate stoichiometry frequently assume carbohydrates, lipids, and proteins have fixed elemental ratios based on culture studies 4 , 6 – 9 , macromolecular stoichiometry in the open ocean is largely unknown. Polar membrane lipids comprise ~ 10–20% of suspended organic matter in the ocean 10 , 11 . The amphiphilic nature of these molecules induces them to form bilayers, and they are the primary interface separating living microbes from their immediate environment. Due to lipid C abundance and the headgroup requirement of a monosaccharide or heteroatom moiety to provide polarity (e.g. P, N, and sulfur, S), the lipidome also functions as a labile reservoir of cell C and both major limiting macronutrients (i.e. N and P). For instance, under N- or P- limitation, microbes can substitute lipid headgroups with a non-limiting heteroatom to mobilize a limiting element for other cellular processes 12 . Additionally, genes for lipid degradation and fatty-acid β-oxidation are widespread among phytoplankton, protists, and heterotrophic bacteria, and are globally distributed 13 – 15 . Therefore, lipid abundance and differential expression directly affects the availability of labile organic carbon and influences the global cycles of P and N 16 . Lipids can also function as biomarker molecules, indicating physiological states of microbial homeostasis, community structure, and P- and N- stress 12 , 17 , 18 . However, many of the lipid biomarkers in modern use can be ambiguous with respect to source, as most membrane lipids and fatty acids have been detected in taxa in multiple kingdoms 18 – 20 . Additionally, indicators of nutrient stress in some species, such as the ratio of the sulfur-based lipid sulfoquinovosyldiacylglycerol (SQDG) to the phospholipid phosphatidylglycerol (PG), have been found not to apply in others 12 , 21 . However, recent studies using high resolution mass spectrometry have uncovered promising, taxonomically-diagnostic molecules that may address these ambiguities 22 – 25 , ushering in an exciting era of precise chemo-physiological inference. Finally, global climate change is predicted to cause large-scale alterations to ocean temperature, stratification, and nutrient distribution 26 . These effects are likely to propagate through microbial community structure, population distributions, macromolecule allocation, and cellular stoichiometry, and therefore the stoichiometry of particulate and dissolved organic matter available for heterotrophic uptake and respiration 8 , 27 . Modelling the modern ocean and predicting future changes to elemental cycles requires a detailed understanding of microbial stoichiometry, ecophysiology, and acclimation strategy 4 , 28 . However, there is a dearth of in-situ analytical measurements to inform macromolecule stoichiometry predictions made by these models. To that end, we performed the first study of polar lipid stoichiometry across an ocean basin, identified several clade-specific biomarkers of nutrient stress, and elucidated the structure of a novel biomarker lipid to diagnose N- and P-stress in globally abundant phytoplankton. Results and Discussion Variability of lipid and bulk particulate organic matter stoichiometry To understand the distribution of essential elements (C, N, P, S) in organic matter throughout the global ocean, we must resolve the variability of macromolecule pool stoichiometry. Using a publicly available dataset 29 , 30 of polar membrane lipids, energy storage triacylglycerols (TAG), and chloropigments in particulate organic matter samples from the western Atlantic Ocean (Fig. 1 , Methods and Data Availability ), we calculated the molar contribution of each element in the lipidome and evaluated the influence of inorganic nutrient availability on membrane lipid stoichiometry and bulk stoichiometry. Polar lipid species distributions were relatively constant below the equator and more varied in the Northern Hemisphere (Supplementary Figs. 1, 2), reflecting seasonal stratification patterns, nutrient availability, and emergent microbial communities—to the south of ~ 10 °N, relatively high dissolved phosphate ([PO 4 ]) and dissolved inorganic nitrogen (DIN, i.e. [nitrate + nitrite]) concentrations (Fig. 1 ) resulted in stable, relatively homogenous microbial communities and lipidomes. Above ~ 10 °N, where sampling spanned rapidly changing spring and summer bloom populations 2 , 31 , surface PO 4 concentrations were close to the limit of detection from ~ 10 °N up to the Gulf Stream at ~ 41 °N, where DIN concentrations were also drawn down to the limit of detection in most of the mixed layer up to the north end of the transect in the Labrador Sea. Despite these diverse conditions, coherent signals in lipidome and bulk stoichiometry clearly emerged. Across the entire Atlantic Ocean, lipid C:P, N:P, and S:P ratios in the mixed layer were all negatively correlated with [PO 4 ] (Fig. 1 , Supplementary Fig. 1), indicating increased expression of non-P-based lipids in P-scarce environments. While substitution of phospholipids by N-, S-, and C-based lipid headgroups has been well documented in cultures and the environment 12 , 21 , we find that that this lipid renovation is also clearly detectable as a change in the bulk macromolecule stoichiometry at large scales. Lipid C:P and S:P in the mixed layer showed wide ranges, from ~ 83:1 to ~ 215:1 (mean = 132:1 ± 28) and 0.3 to 1.3 (mean = 0.8 ± 0.2), respectively, while N:P was more tightly constrained, ranging from 0.95:1 to 1.9:1 (mean = 1.3 ± 0.2). All three ratios reached maxima in the Sargasso Sea, reflecting acute P-scarcity and widespread headgroup substitution (Fig. 1 b, c). In contrast, lipid stoichiometry was not significantly correlated with DIN, despite culture studies demonstrating lipid responses to N-limitation 22 , 32 , suggesting whole-community headgroup substitution in the Atlantic Ocean is more strongly influenced by PO 4 availability. To assess the influence of lipid stoichiometry on bulk stoichiometry, we quantified the contributions of polar lipid C, N, and P and pigment N relative to bulk particulate pools, and evaluated their relationships in the context of changing nutrient availability. In the 128 surface (≤ 40m) samples from North Atlantic cruise AE1319 (~ 30°N-55°N) where lipids and particulate organic C, N, and P (POC, PON, and POP) were simultaneously measured, membrane lipid C constituted up to 17% of total C (mean = 8.2 ± 3.4%), and lipid N comprised up to ~ 4%, with a mean of 1.1 ± 0.8%. Lipid P contained up to 23% of total P (10.2 ± 3.9%), highlighting the magnitude of POP that can be contributed by the P-rich lipidome (Supplementary Fig. 1, Supplementary Table 1; particulate CNP data previously published in Lomas et al. 33 ). Bulk particulate stoichiometry showed strong correlations with nutrient availability (as reported by Lomas et al. 3 , Supplementary Fig. 4), with membrane lipid stoichiometry, and with relative lipid contributions to total C, N, and P. The ratios of particulate C:P and C:N were both negatively correlated with PO 4 and DIN, and Lomas et al. 3 found C:P and N:P to be positively correlated with N:P vertical flux ratios. These responses are consistent with previous research showing that an increase in C:P and C:N under P- and N-limitation, respectively, is a common response among diverse species 7 , 9 . However, we found lipid ratios were most strongly correlated with POC:POP (Fig. 2 ), not PON:POP, and only lipid S:P was correlated with POC:PON (Spearman ρ (rho) = 0.54, p = 0.01). Bulk POC:POP was highly correlated with lipid C:P (Spearman ρ = 0.65, p = 7.71 × 10 − 5 ) and lipid S:P (Spearman ρ = 0.82, p = 1.86 × 10 − 8 ), showing clear simultaneous regulation of lipid and bulk stoichiometry across environmental gradients (Fig. 1 , 2 ). This relationship is strongest below a POC:POP ratio of ~ 200:1, and is highly linear below that threshold in the case of S:P (Adjusted R 2 = 0.55, p = 9.9 × 10 − 6 ), reflective of consistently greater headgroup substitution as POC:POP increases. However, in both lipid C:P and lipid S:P, there is a distinct attenuation in the lipid ratio response above POC:POP of ~ 200:1, suggesting there is an upper physiological limit beyond which microbes cannot substitute headgroups, and therefore a minimum P quota in the community polar lipidome. Indeed, below POC:POP of 200:1, bulk stoichiometry does not significantly change if lipid mass is subtracted, reflecting the in-step modulation of lipid and bulk stoichiometry; but above 200:1, bulk POC:POP would be significantly greater if lipids were removed due to the high proportion of lipid P that cannot be substituted (Supplementary Fig. 5). Lipidome contributions to total POC, PON, and POP also varied also as a function of bulk stoichiometric ratios (Supplementary Fig. 6). Lipid C:POC was negatively correlated with POC:POP (Spearman ρ = -0.39, p = 0.029), reflecting a decreasing lipid fraction of total C under P-stress, while lipid P:POP was positively correlated with POC:POP (Spearman ρ = 0.40, p = 0.026), supporting the hypothesis of non-substitutable P quota in the lipidome. The increase in bulk C:P and concomitant decrease in membrane lipid C:POC would require an increase in a C-rich non-membrane lipid pool like carbohydrates or energy-storage lipids, like eukaryotic triacylglycerols (TAG). However, TAG C did not correlate with POC:POP (Spearman rho = -0.19, p = 0.39), possibly because of variable microbial communities or because relative abundance of TAG is highly dependent on sampling time-of-day 34 , so the source of the increase in POC:POP is unclear. Lipid N:PON correlated positively with POC:PON (Spearman ρ = 0.41, p = 2.50 × 10 − 5 ), and lipid N:PON was negatively correlated with PON:POP (Spearman ρ = -0.66, p = 5.2 × 10 − 5 ). This supports previous evidence showing protein N strongly influences cellular N:P levels (citation 9 and references therein); however it also suggests that, despite relatively lower contributions of lipid N to total PON (mean = ~ 1.1 ± 0.8%), there may also be a minimum N quota in the lipidome, which can increase to nearly 4% of total N, as DIN becomes scarce and protein decreases as a fraction of total POM 7 (Supplementary Fig. 6). We also quantified pigment N content, which comprised 0.07–2.2% of total PON (mean = 0.44 ± 0.39%). This is slightly lower than previous estimates based on cultures 9 , likely due to detrital material. Pigment N:PON was not significantly correlated with either [PO 4 ] or [DIN], in contrast with previous hypotheses of pigment N modulation in response to N-stress 7 —however, given the latitudinal range and inconsistent time-of-day of sampling, it is possible that other environmental drivers influenced pigment content more than DIN availability. Overall, these results confirm that lipid stoichiometry is highly variable and its regulation is central to cell elemental allocation, contrary to previous hypotheses of discrete pools of fixed stoichiometry (e.g. polyphosphate or pigments) 4 , 7 , 35 . Evaluating existing lipid indicators of nutrient-stress The expansion of oligotrophic gyres due to climate change raises the need for easily detectable biomarkers to indicate nutrient limitation in major taxa—the traditional method for assessing nutrient limitation, i.e. nutrient addition experiments, are time consuming and complex 36 , and an experiment’s results are only applicable for relatively small regions. In contrast, lipid biomarker ratios are readily detectable via mass spectrometry and can be measured at ocean-wide scales, even where macronutrient concentrations are at or below the limit of detection. The two most well-described lipidomic indicators of nutrient limitation in phytoplankton are the ratios of S-lipid sulfoquinovosyldiacylglycerol to P-lipid phosphatidylglycerol (SQDG:PG) and the ratio of N-based betaine lipids to the P-lipid phosphatidylcholine (BL:PC). They are well-demonstrated markers of P-stress in cyanobacteria and eukaryotic phytoplankton, respectively 17 , 21 , 37 , and reflect marked differences in P-availability between ocean basins 12 and along ocean transects (usually from an area of high-P to low-P) 38,39 . Both ratios increase under P-stress, and decrease when P is more available. However, their interpretation is less clear between mixed communities due to diverse steady-state lipid abundances and stress responses between species. For example, SQDG and PG are produced by all known oxygenic phototrophs 40 , but a P-stressed cyanobacteria Prochlorococcus SQDG:PG ratio can range from ~ 30–130 while a P-stressed diatom Thalassiosira pseudonana may have a ratio of almost 400 12,21,22,41 . Further, though many eukaryotes increase their ratios of betaine- to phospho-lipids under P-limitation, most P-lipids can be found at significant abundances in both bacteria and eukaryotes 17 , 39 , 42 , increasing the potential ambiguity of these markers and highlighting the need to evaluate them at this scale. In the mixed layer, we found the highest SQDG:PG and BL:PC ratios coincided with the lowest PO 4 concentrations between ~ 10–30°N in the Sargasso Sea, predictably indicating the region of highest P-stress (Supplementary Fig. 7). However, the two markers diverge south of the equator and at higher northern latitudes, and only BL:PC showed a significant negative relationship with [PO 4 ] across the combined transects (Supplementary Fig. 8; Spearman ρ = -0.28, p = 0.01). Moreover, the latitude of maximum P-stress differed between the two, with the highest values for SQDG:PG and BL:PC measured at ~ 15°N and ~ 30°N, respectively. These differential responses may indicate taxonomically variable P-stress in different regions—cyanobacteria could be experiencing greater P-stress than eukaryotes nearer to the equator and in the Southern Hemisphere, as suggested by increased lipid C:P and S:P (Fig. 1 ) and by metagenome-inferred P-stress in Prochlorococcus in the South Atlantic 43 ; it may also simply reflect greater relative abundance of cyanobacteria at lower latitudes 44 , as Prochlorococcus produces significantly more SQDG relative to total lipids than other phototrophs 39 , 45 . Therefore, despite these ratios appearing to be strong indicators of P-stress within individual species and within similar microbial communities 12 , 21 , 46 , 47 , this uncertainty emphasizes the need for environmental markers with higher taxonomic specificity. Ornithine lipids (OL) are a compelling candidate for bacteria-specific community analysis—OL biosynthesis genes occur in around half of genome-sequenced bacteria 48 , 49 , but no known archaea or eukaryotes 50 . And despite OL synthesis requiring two costly N atoms per headgroup (compared to one N atom in most known N-containing membrane lipids), OL upregulation in response to P-stress has been documented in several cultured heterotrophic bacteria, including some strains of SAR11 17,37,51 . We measured OL abundance along the combined transects and in relation to the dominant bacterial membrane lipid, PE. In the mixed layer, we detected a range of OL relative abundances from 0.05% of total lipids in the Labrador Sea to 1.25% in the Sargasso Sea, in concert with drastically elevated log 10 OL:PE, which increased from − 2.27 to -0.90 (Fig. 3 , Supplemental Figs. 7, 9). OL:PE is also significantly negatively correlated with [PO 4 ] (Supplemental Fig. 8; Spearman ρ = -0.46, p = 1.6 × 10 − 5 ) indicating there is sufficient P-stress in dominant heterotrophic bacteria to necessitate the use of “luxury” N in N-rich OL. The glycolipid, glucuronosyl diacylglycerol (GADG, often labelled GlcADG), which has been more recently discovered in the ocean, has been shown to increase drastically in P-limited bacteria 37 , 47 , 52 and higher plants 53 , and we find it to be an effective marker of low P-availability in heterotrophic bacteria. Carini et al. 37 found GADG glycosyltransferases are overrepresented in strains of SAR 11 endemic to the Sargasso Sea relative to other ocean regions, and measured significantly increased abundance of GADG under P-limited conditions. In cultures of one North Atlantic strain, relative abundance of GADG to the typical dominant membrane lipid, PE, increased from undetectable under replete conditions to an average log 10 GADG:PE ratio of -0.61, with GADG comprising an average of ~ 25% of total lipids—an order of magnitude higher than in known marine eukaryotes 22 . Along our combined transects, log 10 GADG:PE ranged from − 2.81 to a maximum of -0.41 in the Sargasso Sea (Fig. 3 ., Supplementary Fig. 7) and is highly negatively correlated with [PO 4 ] (Supplemental Fig. 8; Spearman ρ = -0.56, p = 5.8 × 10 − 8 ). Therefore, despite minor GADG production in some eukaryotes 22 , GADG:PE appears to be a strong environmental indicator of microbial lipid renovation in response to P-scarcity, likely driven by heterotrophic bacteria. In comparison with GADG:PE, both measures are highly correlated (R 2 = 0.89, p < 1 × 10 − 15 ) and have maxima at the same latitude, confirming P-scarcity responses in the most prevalent marine bacteria. Novel marker of N- and P- stress in ubiquitous coccolithophores Lastly, we present a novel metric, the ratio of two haptophyte-specific lipid classes which are easily detectable via mass spectrometry as a handful of molecular ions (Supplementary Table 2), that can indicate differential N- and P-stress responses in the ubiquitous and globally significant coccolithophore, Gephyrocapsa huxleyi , enabling ecological nutrient-stress inferences where DIN and PO 4 measurements are near and below the limit of measurement (Fig. 1 b). In developing this measure, we have elucidated the structure of a novel lipid headgroup, thus far only detected in the morphospecies G. huxleyi / G. oceanica 54 (Supplementary Figs. 10, 11). Combined with another recently discovered lipid, phosphatidyl-S,S-dimethylpropanethiol 23 (PDPT), which has only been detected in marine haptophytes including G. huxleyi and is highly upregulated under N-limitation 22 , the molecules function as an easily detectable and taxonomically distinct indicator of N- and P- stress in the open ocean. The novel lipid class, first detected but uncharacterized by Schleyer et al. 55 , contains only sulfur, carbon, hydrogen, and oxygen, and therefore avoids the typical membrane lipid requirement for P or N. It has an S-based analogous structure to the prominent eukaryotic membrane lipid, diacylglycerylcarboxyhydroxymethylcholine (DGCC), substituting di-methylated sulfur instead of tri-methylated nitrogen 56 (Supplementary Fig. 10). Therefore, we propose the nomenclature diacylglycerylcarboxyhydroxysulfocholine (DGCS). Reanalysis of previously published culture data 22 shows significant upregulation in N-limited G. huxleyi , and non-significant increases under P-limitation (Supplementary Fig. 11). However, though DGCS comprises only ~ 0.2–1.3% of polar lipids in G. huxleyi and G. oceanica cultured in nutrient-replete conditions (Supplementary Fig. 11), DGCS is present throughout the Atlantic Ocean mixed layer and accounts for almost 3% of the total polar lipid pool in the most nutrient-poor Atlantic samples, irrespective of haptophyte relative abundance (Supplementary Fig. 12). Its relative abundance in the photic zone is negatively correlated with [PO 4 ] (Spearman rho = -0.63, p < 2.2 × 10 − 16 ) and [DIN] (Spearman rho = -0.80, p < 2.2 × 10 − 16 ), and though Schleyer et al. 55 found it to be downregulated in response to viral infection, we did not detect a well-documented biosignature of viral infection of G. huxleyi 57 , 58 , suggesting viruses were not a major stressor during this study. This evidence indicates DGCS is responsive not only to N-limitation, but to N- and P-stress, and appears to be a major adaptation and acclimation strategy for these coccolithophores in nutrient-scarce environments. The other biomarker lipid class, PDPT, has only been detected in marine haptophytes, and has been previously identified as a strong indicator of N-limitation in cultured G. huxleyi 22 , 23 . Across the transect, PDPT comprised an average of ~ 1% of total polar lipids, increasing to ~ 5% above the Gulf Stream where DIN concentrations dropped below the limit of detection (Fig. 1 , Supplementary Figs. 1, 13), and PDPT relative abundance in the photic zone negatively correlated with [DIN] (Spearman rho = -0.33, p = 2.1 × 10 − 5 ). When the two headgroups are combined into a ratio of DGCS:PDPT, the metric shows a clear maximum in the P-scarce Sargasso Sea and decreases to a minimum north of the Gulf Stream where a eukaryote bloom had reduced [DIN] to below the limit of detection (Figs. 1 , 3 ), cleanly elucidating a transition from P- to N-stress in the North Atlantic. The consistent abundance of N-stress marker PDPT throughout the transects, superseded by abundance of DGCS in the Sargasso Sea, supports hypotheses of widespread N-limitation in the Atlantic overridden by proximal P-limitation in the Sargasso Sea, inferred from metagenome 43 and nutrient-addition meta analyses 36 , 59 (Fig. 3 ), demonstrating the power of a single lipidomic dataset to diagnose nutrient stress across ocean-wide geochemical gradients in multiple microbial clades. Thus, all three indices, GADG:PE, OL:PE, and DGCS:PDPT appear to have the capacity to indicate nutrient stress with more taxonomic and functional group resolution than previously developed lipid indicators, which will aid predictions and diagnoses of nutrient stress due to enhanced stratification and the expansion of oligotrophic gyres driven by global climate change. Discussion Lipids are a large, labile component of both living and non-living marine organic matter, and the elemental composition of the lipid pool has a significant influence on the biogeochemical cycling of C, N, P, and S. Traditionally, the stoichiometry of polar membrane lipids in marine microbes is assumed to have a fixed proportion of C and P, with a negligible or non-existent contribution of N. We found significantly more N in polar lipids than is frequently cited in the literature 4 , 9 , 35 , comprising an average ~ 1% and up to 4% of total N in the mixed layer, comparable to total N in all measured metabolites in the North Pacific 60 . Proteomic adaptive responses to nutrient scarcity in phytoplankton operate on miniscule margins, incurring an N-cost equivalent to 0.2% of total N in iron-limited Synechococcus 61 and 0.044% in vitamin B12-starved diatom Phaeodactylum tricornutum 62 . Therefore, maintenance of ~ 1% of N in N-lipids represents a non-negligible N-cost, implying the structure and function of N-lipids is preferable to P-lipids in some physiological scenarios beyond simple P-limitation. In experimental and modeling tests of PC and the N-based betaine lipid diacylglyceryltrimethylhomoserine (DGTS), Bolik et al. 63 found DGTS forms thicker, more rigid, and more repulsive membranes than the P-lipid, and Künzler et al. 64 showed betaine lipid localization outside of chloroplasts in the higher plant, Lycopodium annotinum . Abundant research has demonstrated highly specific lipid molecule localization in photosystems and thylakoid membranes 40 , 65 , 66 , but less is known about extraplastidial membrane lipid function and subcellular distribution in phytoplankton and bacteria; therefore, more work is needed to determine the role and localization of lipids in marine microbes, and whether other protein complexes also require specific membrane lipid components for proper functionality. The ecological implications of the variation in lipid C:P are also significant. In contrast to cited membrane lipid C:P ratios of ~ 40:1 in phytoplankton and bacteria in culture 4 , 9 , the Atlantic surface lipidome C:P changed in tandem with POC:POP, from a lipid C:P of ~ 83:1 to an upper limit of ~ 214:1, and the lipid fraction of total P concomitantly increased where paired samples were measured. This implies that, though N- and S-lipids are substituted for P-lipids as lipid C:P increases, other cellular P reservoirs are reallocated at a greater rate than the lipidome due to a minimum lipid P quota. It is unclear whether this is an Atlantic-specific phenomenon, where the AE1319 transect (with paired lipid and POM measurements) transitioned from an N-stressed, eukaryote-dominated community north of the Gulf Stream to the P-stressed, cyanobacteria-dominated Sargasso Sea 2 , 3 . Previous studies of particulate C, N, and P in the global ocean have found a more variable POC:POP in the Atlantic 1 , 4 , as well as more variable microbial stoichiometry regulation in response to P-limitation than N-limitation 3 , 7 . Similarly, genes for P-uptake, organic P catabolism, and phospholipid renovation are overrepresented in North Atlantic strains of both autotrophic and heterotrophic microorganisms 37 , 67 , all suggesting lipid substitution should be especially prevalent in the Atlantic Ocean. Accordingly, we found the highest lipid C:P coincided with high POC:POP communities in the Sargasso Sea. However, we found that these P-stressed communities devoted a ~ 3-fold greater fraction of total P to lipids than the N-stressed communities north of the Gulf Stream, which is in contrast to previous research indicating microbes in the North Pacific commit an order of magnitude greater fraction of P-uptake to P-lipid synthesis than Sargasso Sea communities 12 . This may be a function of greater P-lipid-turnover in the Pacific, due to the drastically higher PO 4 concentrations, but it may suggest Atlantic and Pacific microbes have fundamentally different approaches to lipidomic regulation, even in low-latitude, cyanobacteria-dominated communities 3 . Understanding how lipid stoichiometry is regulated in predominantly N-stressed environments like the Pacific Ocean, or trace metal-scarce regions like the Southern Ocean, will further elucidate the patterns of microbial physiology and elemental distribution throughout the global ocean. Our results highlight the plasticity of that distribution within the microbial lipidome, and the effects of that modulation on total particulate stoichiometry throughout the Atlantic Ocean. Methods and Data Availability Detailed methods available in Holm et al 29 . In brief, a total of 344 1–2 L seawater samples from 73 stations along four transects were collected via CTD-rosette mounted Niskin bottles,filtered onto 0.22 µm Durapore filters (Millipore Sigma), and the filters were wrapped in combusted aluminum foil and immediately flash frozen in liquid nitrogen and stored in the headspace of a liquid nitrogen dewar. Samples were extracted via a modified Bligh and Dyer protocol 68 , then analyzed via high performance liquid chromatography-high resolution accurate mass-mass spectrometry, as detailed in Popendorf et al 39,69 . Mass spectral data was then processed through the xcms 70 , CAMERA 71 , and LOBSTAHS 72 pipelines using the R programming language 73 ; the map in Fig. 1 was produced using the R-package ggOceanMaps 74 . Lipid identification, abundance, and mixed layer depth data was available through Holm et al. 29 , where full analytical methods can be found, except for lipid classes PDPT, DGCS, OL, sulfur-amino-lipids (SAL; Supplementary Fig. 2), and betaine-like lipids (BLL), which were confirmed via published ms/ms fragmentation patterns 23 , 75 , adduct hierarchies 72 , and retention time patterns. In addition to the 938 unique lipid molecules in the original dataset, we identified and quantified 77 additional lipids including pigments, increasing the number of unique annotated molecules by 8% and total lipid abundance by 9%. Commercial standards are not available for these lipid classes, so we used a best-matched-standard approach similar to Heal et al. 76 based on known ionization differences for similar headgroup functional groups (i.e. reduced headgroup N ionizes more efficiently than reduced S and glycolipid headgroups). Best-matched standards are detailed in Supplemental Table 3. Liu et al. 77 also published a reanalysis of the original dataset, including unannotated mass spectral features; our targeted approach is complementary to their untargeted statistical cluster analysis. Inorganic nutrient data was reproduced from Baer et al. (2017) 2 , Durkin et al. (2016) 78 , and Van Mooy et al. (2015) 79 . Particulate organic carbon, nitrogen, and phosphorus data was reproduced from Lomas et al. 3 via the Biological and Chemical Oceanographic Data Management Office 80 . Statistical Methods A statistical test was considered significant below a p -value of < 0.05 and significance was reported at four significance levels: p < 0.0001, p < 0.001, p < 0.01, and p < 0.05. Correlation was determined using Spearman rank order correlation except when testing linearity, where Pearson correlation coefficients were calculated. Loess smoothing was used to show trendlines across latitude, with parameters detailed in figure captions. Declarations Acknowledgements We thank C. Dean for G. oceanica biomass. Funding for this work was provided by the NSF and Simons Foundation. References Tanioka T et al (2022) Global patterns and predictors of C:N:P in marine ecosystems. Commun Earth Environ 3:1–9 Baer SE, Lomas MW, Terpis KX, Mouginot C, Martiny AC (2017) Stoichiometry of Prochlorococcus, Synechococcus, and small eukaryotic populations in the western North Atlantic Ocean. Environ Microbiol 19:1568–1583 Lomas MW et al (2021) Varying influence of phytoplankton biodiversity and stoichiometric plasticity on bulk particulate stoichiometry across ocean basins. Commun Earth Environ 2:1–10 Inomura K, Deutsch C, Jahn O, Dutkiewicz S, Follows MJ (2022) Global patterns in marine organic matter stoichiometry driven by phytoplankton ecophysiology. Nat Geosci 15:1034–1040 Redfield AC, Ketchum BH, Richards FA (1963) The influence of organisms on the composition of sea-water. in Liefer JD et al (2024) Latitudinal patterns in ocean C:N:P reflect phytoplankton acclimation and macromolecular composition. Proc. Natl. Acad. Sci. U.S.A. 121, e2404460121 Moreno AR, Martiny AC (2018) Ecological Stoichiometry of Ocean Plankton. Annual Rev Mar Sci 10:43–69 Kwiatkowski L, Aumont O, Bopp L, Ciais P (2018) The Impact of Variable Phytoplankton Stoichiometry on Projections of Primary Production, Food Quality, and Carbon Uptake in the Global Ocean. Glob Biogeochem Cycles 32:516–528 Geider R, La Roche J (2002) Redfield revisited: variability of C:N:P in marine microalgae and its biochemical basis. Eur J Phycol 37:1–17 Wakeham SG, Lee C, Hedges JI, Hernes PJ, Peterson MJ (1997) Molecular indicators of diagenetic status in marine organic matter. Geochim Cosmochim Acta 61:5363–5369 Edwards BR (2023) Lipid Biogeochemistry and Modern Lipidomic Techniques. Annu Rev Mar Sci 15:485–508 Van Mooy BAS et al (2009) Phytoplankton in the ocean use non-phosphorus lipids in response to phosphorus scarcity. Nature 458:69–72 Villar E et al (2018) The Ocean Gene Atlas: exploring the biogeography of plankton genes online. Nucleic Acids Res 46:W289–W295 Lauro FM et al (2009) The genomic basis of trophic strategy in marine bacteria. Proceedings of the National Academy of Sciences 106, 15527–15533 Dupont CL et al (2012) Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage. ISME J 6:1186–1199 Westermann LM et al (2023) Bacterial catabolism of membrane phospholipids links marine biogeochemical cycles. Sci Adv 9:eadf5122 Sebastián M et al (2016) Lipid remodelling is a widespread strategy in marine heterotrophic bacteria upon phosphorus deficiency. ISME J 10:968–978 Schubotz F, Xie S, Lipp JS, Hinrichs K-U, Wakeham SG (2018) Intact polar lipids in the water column of the eastern tropical North Pacific: abundance and structural variety of non-phosphorus lipids. Biogeosciences 15:6481–6501 Kabeya N et al (2018) Genes for de novo biosynthesis of omega-3 polyunsaturated fatty acids are widespread in animals. Sci Adv 4:eaar6849 Russell NJ, Nichols DS (1999) Polyunsaturated fatty acids in marine bacteria — a dogma rewritten. Microbiology 145:767–779 Cañavate JP, Armada I, Hachero-Cruzado I (2017) Interspecific variability in phosphorus-induced lipid remodelling among marine eukaryotic phytoplankton. New Phytol 213:700–713 Lowenstein DP, Mayers K, Fredricks HF, Van Mooy BAS (2021) Targeted and untargeted lipidomic analysis of haptophyte cultures reveals novel and divergent nutrient-stress adaptations. Org Geochem 161:104315 Fulton JM et al (2014) Novel molecular determinants of viral susceptibility and resistance in the lipidome of Emiliania huxleyi. Environ Microbiol 16:1137–1149 Hunter JE, Frada MJ, Fredricks HF, Vardi A, Van Mooy BAS (2015) Targeted and untargeted lipidomics of Emiliania huxleyi viral infection and life cycle phases highlights molecular biomarkers of infection, susceptibility, and ploidy. Front Mar Sci 2 Li Y et al (2017) Sphingolipids in marine microalgae: Development and application of a mass spectrometric method for global structural characterization of ceramides and glycosphingolipids in three major phyla. Anal Chim Acta 986:82–94 Kwiatkowski L et al (2020) Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections. Biogeosciences 17:3439–3470 Deutsch C, Weber T (2012) Nutrient Ratios as a Tracer and Driver of Ocean Biogeochemistry. Annual Rev Mar Sci 4:113–141 Follows MJ, Dutkiewicz S, Grant S, Chisholm SW (2007) Emergent Biogeography of Microbial Communities in a Model Ocean. Science 315:1843–1846 Holm HC et al (2022) Global ocean lipidomes show a universal relationship between temperature and lipid unsaturation. Science 376:1487–1491 Holm H, Van Mooy BAS (2022) hholm/OceanLipidome: Version 1.0.2. Zenodo https://doi.org/10.5281/zenodo.7035947 Giovannoni SJ, Vergin KL (2012) Seasonality in Ocean Microbial Communities. Science 335:671–676 Huang B et al (2019) Betaine lipid and neutral lipid production under nitrogen or phosphorus limitation in the marine microalga Tisochrysis lutea (Haptophyta). Algal Res 40:101506 Lomas MW, Bonachela JA, Levin SA, Martiny AC (2014) Impact of ocean phytoplankton diversity on phosphate uptake. Proceedings of the National Academy of Sciences 111, 17540–17545 Becker KW et al (2018) Daily changes in phytoplankton lipidomes reveal mechanisms of energy storage in the open ocean. Nat Commun 9:5179 Liefer JD et al (2019) The Macromolecular Basis of Phytoplankton C:N:P Under Nitrogen Starvation. Front Microbiol 10 Browning TJ, Moore CM (2023) Global analysis of ocean phytoplankton nutrient limitation reveals high prevalence of co-limitation. Nat Commun 14:5014 Carini P et al (2015) SAR11 lipid renovation in response to phosphate starvation. Proc Natl Acad Sci USA 112:7767–7772 Martin P, Dyhrman ST, Lomas MW, Poulton NJ, Van Mooy BAS (2014) Accumulation and enhanced cycling of polyphosphate by Sargasso Sea plankton in response to low phosphorus. Proceedings of the National Academy of Sciences 111, 8089–8094 Popendorf KJ, Lomas MW, Van Mooy BA (2011) Microbial sources of intact polar diacylglycerolipids in the Western North Atlantic Ocean. Org Geochem 42:803–811 Lipids in Photosynthesis. (Springer Neth, (2009) 10.1007/978-90-481-2863-1 Martin P, Van Mooy BA, Heithoff A, Dyhrman ST (2011) Phosphorus supply drives rapid turnover of membrane phospholipids in the diatom Thalassiosira pseudonana. ISME J 5:1057–1060 Geiger O, López-Lara IM, Sohlenkamp C (2013) Phosphatidylcholine biosynthesis and function in bacteria. Biochim et Biophys Acta (BBA) - Mol Cell Biology Lipids 1831:503–513 Ustick LJ et al (2021) Metagenomic analysis reveals global-scale patterns of ocean nutrient limitation. Science 372:287–291 Flombaum P et al (2013) Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. Proceedings of the National Academy of Sciences 110, 9824–9829 Van Mooy BAS, Rocap G, Fredricks HF, Evans CT, Devol AH (2006) Sulfolipids dramatically decrease phosphorus demand by picocyanobacteria in oligotrophic marine environments. Proceedings of the National Academy of Sciences 103, 8607–8612 Bent SM et al (2024) Lipid biochemical diversity and dynamics reveal phytoplankton nutrient-stress responses and carbon export mechanisms in mesoscale eddies in the North Pacific Subtropical Gyre. Front Mar Sci 11 Jones RA et al (2021) Phosphorus stress induces the synthesis of novel glycolipids in Pseudomonas aeruginosa that confer protection against a last-resort antibiotic. ISME J 15:3303–3314 Smith AF et al (2019) Elucidation of glutamine lipid biosynthesis in marine bacteria reveals its importance under phosphorus deplete growth in Rhodobacteraceae. ISME J 13:39–49 Geiger O, González-Silva N, López-Lara IM, Sohlenkamp C (2010) Amino acid-containing membrane lipids in bacteria. Prog Lipid Res 49:46–60 Vences-Guzmán MÁ, Geiger O, Sohlenkamp C (2012) Ornithine lipids and their structural modifications: from A to E and beyond. FEMS Microbiol Lett 335:1–10 Kim S-K et al (2018) Bacterial ornithine lipid, a surrogate membrane lipid under phosphate-limiting conditions, plays important roles in bacterial persistence and interaction with host. Environ Microbiol 20:3992–4008 Diercks H et al (2015) Accumulation of Novel Glycolipids and Ornithine Lipids in Mesorhizobium loti under Phosphate Deprivation. J Bacteriol 197:497–509 Okazaki Y et al (2013) A new class of plant lipid is essential for protection against phosphorus depletion. Nat Commun 4:1510 Bendif EM et al (2019) Repeated species radiations in the recent evolution of the key marine phytoplankton lineage Gephyrocapsa. Nat Commun 10:4234 Schleyer G et al (2019) In plaque-mass spectrometry imaging of a bloom-forming alga during viral infection reveals a metabolic shift towards odd-chain fatty acid lipids. Nat Microbiol 4:527–538 Bisseret P et al (1984) Occurrence of phosphatidylsulfocholine, the sulfonium analog of phosphatidylcholine in some diatoms and algae. Biochim et Biophys Acta (BBA) - Lipids Lipid Metabolism 796:320–327 Laber CP et al (2018) Coccolithovirus facilitation of carbon export in the North Atlantic. Nat Microbiol 3:537–547 Vardi A et al (2009) Viral Glycosphingolipids Induce Lytic Infection and Cell Death in Marine Phytoplankton. Science 326:861–865 Moore CM et al (2013) Processes and patterns of oceanic nutrient limitation. Nat Geosci 6:701–710 Boysen AK et al (2021) Particulate Metabolites and Transcripts Reflect Diel Oscillations of Microbial Activity in the Surface Ocean. mSystems 6, e00896-20 Mackey KRM et al (2015) Divergent responses of Atlantic coastal and oceanic Synechococcus to iron limitation. Proceedings of the National Academy of Sciences 112, 9944–9949 Bertrand EM et al (2013) Methionine synthase interreplacement in diatom cultures and communities: Implications for the persistence of B12 use by eukaryotic phytoplankton. Limnol Oceanogr 58:1431–1450 Bolik S et al (2023) Lipid bilayer properties potentially contributed to the evolutionary disappearance of betaine lipids in seed plants. BMC Biol 21:275 Künzler K, Eichenberger W, Radunz A (1997) Intracellular localization of two betaine lipids by cell fractionation and immunomicroscopy. Z Naturforsch C J Biosci 52:487–495 Kern J, Zouni A, Guskov A, Krauß N (2009) Lipids in the Structure of Photosystem I, Photosystem II and the Cytochrome b6f Complex. In: Wada H, Murata N (eds) Lipids in Photosynthesis: Essential and Regulatory Functions. Springer Netherlands, Dordrecht, pp 203–242. doi: 10.1007/978-90-481-2863-1_10 . Mizusawa N, Wada H (2012) The role of lipids in photosystem II. Biochim et Biophys Acta (BBA) - Bioenergetics 1817:194–208 Sosa OA, Repeta DJ, DeLong EF, Ashkezari MD, Karl DM (2019) Phosphate-limited ocean regions select for bacterial populations enriched in the carbon–phosphorus lyase pathway for phosphonate degradation. Environ Microbiol 21:2402–2414 Bligh EG, Dyer WJ, A RAPID METHOD, OF TOTAL LIPID EXTRACTION AND PURIFICATION (1959) Can J Biochem Physiol 37:911–917 Hummel J et al (2011) Ultra Performance Liquid Chromatography and High Resolution Mass Spectrometry for the Analysis of Plant Lipids. Front Plant Sci 2 Smith CA, Want EJ, O’Maille G, Abagyan R, Siuzdak GXCMS (2006) Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification. Anal Chem 78:779–787 Kuhl C, Tautenhahn R, Böttcher C, Larson TR, Neumann SCAMERA (2012) An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets. Anal Chem 84:283–289 Collins JR, Edwards BR, Fredricks HF, Van Mooy BAS (2016) LOBSTAHS: An Adduct-Based Lipidomics Strategy for Discovery and Identification of Oxidative Stress Biomarkers. Anal Chem 88:7154–7162 R Core Team (2020) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vihtakari M (2024) ggOceanMaps: Plot Data on Oceanographic Maps Using ‘Ggplot2’ Smith AF et al (2021) A novel class of sulfur-containing aminolipids widespread in marine roseobacters. ISME J 15:2440–2453 Heal KR et al (2021) Marine Community Metabolomes Carry Fingerprints of Phytoplankton Community Composition. mSystems 6. 10.1128/msystems.01334-20 Liu W et al (2025) Unraveling plankton adaptation in global oceans through the untargeted analysis of lipidomes. Sci Adv 11:eads4605 Durkin CA, Van Mooy BAS, Dyhrman ST, Buesseler KO (2016) Sinking phytoplankton associated with carbon flux in the Atlantic Ocean. Limnol Oceanogr 61:1172–1187 Van Mooy BAS et al (2015) Major role of planktonic phosphate reduction in the marine phosphorus redox cycle. Science 348:783–785 Lomas MW, Martiny A (2013) Depth profile data from R/V Atlantic Explorer AE1319 in the NW Atlantic from Aug-Sept. https://hdl.handle.net/1912/26396 (2020) Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryFigureTables.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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06:32:32","extension":"xml","order_by":40,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":186675,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS25885170structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/ebec50c2fa5646a4e0fcdb32.xml"},{"id":96237880,"identity":"45c22d5d-0d32-4d82-9368-dcb9da988bcf","added_by":"auto","created_at":"2025-11-19 06:32:31","extension":"html","order_by":41,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":197704,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/0b9e44a648e2426b1e4a5743.html"},{"id":96253284,"identity":"5cf99310-5810-4157-9469-f24be97aabbd","added_by":"auto","created_at":"2025-11-19 07:42:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138117,"visible":true,"origin":"","legend":"\u003cp\u003eCruise transects (a) with month and year indicated by color and shape, respectively; (b) concentrations in the mixed layer by latitude of dissolved inorganic phosphate (PO4, red) and dissolved inorganic nitrogen (DIN, i.e. combined nitrate and nitrite, blue) in micromolar (μM); and (c) stoichiometric ratios by latitude of nitrogen to phosphorus (N/P, blue), sulfur to phosphorus (S/P, red), and carbon to phosphorus (C/P, green) in particulate membrane lipids in the mixed layer. Values of PO4 and DIN at 0 μM indicate the concentration was below the detection limit. Inorganic nutrient data (b) reproduced from Baer et al. 2017, Durkin et al. 2016, Van Mooy et al. 2015. Red, blue, and green lines (c) indicate loess-smoothed lipid N:P, S:P, and C:P ratio moving averages with a smoothing span of 0.4 and shaded 95% confidence intervals.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/0eeb20e63c4dcb99fdc3e102.png"},{"id":96251768,"identity":"53aaffed-3912-48de-849f-260b9b4a7882","added_by":"auto","created_at":"2025-11-19 07:40:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62732,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between lipid stoichiometric ratios and total particulate organic carbon:phosphorus (POC:POP) ratios in the North Atlantic Ocean. Both lipid C:P (a) and lipid S:P (b) are positively correlated with POC:POP (Lipid C:P Spearman rho = 0.64, p = \u0026lt;0.0001; Lipid S:P Spearman rho = 0.82, p = \u0026lt;0.0001). Regressions indicate linear relationship below POC:POP 200:1, above which lipid substitution attenuates (Lipid C:P vs. POC:POP: adjusted R\u003csup\u003e2\u003c/sup\u003e = 0.21, p = 0.0175; Lipid S:P vs. POC:POP: adjusted R\u003csup\u003e2\u003c/sup\u003e = 0.55, p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/bc5960209298b625c3beb433.png"},{"id":96237842,"identity":"9f6787cd-7ff2-47ba-88b7-b4a8f0c1a36f","added_by":"auto","created_at":"2025-11-19 06:32:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":82358,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between lipid stoichiometric ratios and total particulate organic carbon:phosphorus (POC:POP) ratios in the North Atlantic Ocean. Both lipid C:P (a) and lipid S:P (b) are positively correlated with POC:POP (Lipid C:P Spearman rho = 0.64, p = \u0026lt;0.0001; Lipid S:P Spearman rho = 0.82, p = \u0026lt;0.0001). Regressions indicate linear relationship below POC:POP 200:1, above which lipid substitution attenuates (Lipid C:P vs. POC:POP: adjusted R\u003csup\u003e2\u003c/sup\u003e = 0.21, p = 0.0175; Lipid S:P vs. POC:POP: adjusted R\u003csup\u003e2\u003c/sup\u003e = 0.55, p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/63d0bd74c924e237098cd9b9.png"},{"id":96257039,"identity":"94c4a52a-2d3e-4265-8f5f-c7a19bcc3d33","added_by":"auto","created_at":"2025-11-19 07:51:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":831672,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/043664bf-88e1-4ffd-a04a-a13f5ac58c70.pdf"},{"id":96237845,"identity":"8cb5d313-d8ed-4604-8b80-af27a3d74cde","added_by":"auto","created_at":"2025-11-19 06:32:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1658410,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8022751/v1/75cbb50c88102453efa002e7.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Lipid stoichiometry and biomarkers reflect microbial acclimation and nutrient stress across the Atlantic Ocean","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince the relationship was first discovered in marine particulate organic matter (POM) almost seventy years ago, the canonical \u0026ldquo;Redfield\u0026rdquo; ratio of 106 carbon (C) to 16 nitrogen (N) to 1 phosphorus (P) atoms has undergone significant revision. Though an ocean-scale view yields an average ratio of ~\u0026thinsp;106:16:1, the figure belies significant heterogeneity. Inter- and intra-specific variations in elemental quota, community spatial heterogeneity, and circulation processes all influence the global averages that Redfield, Ketchum, and Richards illuminated\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. A portion of this variation is due to changing cellular proportions of macromolecules like lipids, proteins, and carbohydrates; up- or downregulation of these macromolecule groups results in variations in bulk stoichiometry across small and large spatial scales\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, though ocean models and studies of particulate stoichiometry frequently assume carbohydrates, lipids, and proteins have fixed elemental ratios based on culture studies\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, macromolecular stoichiometry in the open ocean is largely unknown.\u003c/p\u003e\u003cp\u003ePolar membrane lipids comprise\u0026thinsp;~\u0026thinsp;10\u0026ndash;20% of suspended organic matter in the ocean\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The amphiphilic nature of these molecules induces them to form bilayers, and they are the primary interface separating living microbes from their immediate environment. Due to lipid C abundance and the headgroup requirement of a monosaccharide or heteroatom moiety to provide polarity (e.g. P, N, and sulfur, S), the lipidome also functions as a labile reservoir of cell C and both major limiting macronutrients (i.e. N and P). For instance, under N- or P- limitation, microbes can substitute lipid headgroups with a non-limiting heteroatom to mobilize a limiting element for other cellular processes\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, genes for lipid degradation and fatty-acid β-oxidation are widespread among phytoplankton, protists, and heterotrophic bacteria, and are globally distributed\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Therefore, lipid abundance and differential expression directly affects the availability of labile organic carbon and influences the global cycles of P and N\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eLipids can also function as biomarker molecules, indicating physiological states of microbial homeostasis, community structure, and P- and N- stress\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, many of the lipid biomarkers in modern use can be ambiguous with respect to source, as most membrane lipids and fatty acids have been detected in taxa in multiple kingdoms\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Additionally, indicators of nutrient stress in some species, such as the ratio of the sulfur-based lipid sulfoquinovosyldiacylglycerol (SQDG) to the phospholipid phosphatidylglycerol (PG), have been found not to apply in others\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, recent studies using high resolution mass spectrometry have uncovered promising, taxonomically-diagnostic molecules that may address these ambiguities\u003csup\u003e\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, ushering in an exciting era of precise chemo-physiological inference.\u003c/p\u003e\u003cp\u003eFinally, global climate change is predicted to cause large-scale alterations to ocean temperature, stratification, and nutrient distribution\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These effects are likely to propagate through microbial community structure, population distributions, macromolecule allocation, and cellular stoichiometry, and therefore the stoichiometry of particulate and dissolved organic matter available for heterotrophic uptake and respiration\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Modelling the modern ocean and predicting future changes to elemental cycles requires a detailed understanding of microbial stoichiometry, ecophysiology, and acclimation strategy\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, there is a dearth of \u003cem\u003ein-situ\u003c/em\u003e analytical measurements to inform macromolecule stoichiometry predictions made by these models. To that end, we performed the first study of polar lipid stoichiometry across an ocean basin, identified several clade-specific biomarkers of nutrient stress, and elucidated the structure of a novel biomarker lipid to diagnose N- and P-stress in globally abundant phytoplankton.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eVariability of lipid and bulk particulate organic matter stoichiometry\u003c/h2\u003e\u003cp\u003eTo understand the distribution of essential elements (C, N, P, S) in organic matter throughout the global ocean, we must resolve the variability of macromolecule pool stoichiometry. Using a publicly available dataset\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e of polar membrane lipids, energy storage triacylglycerols (TAG), and chloropigments in particulate organic matter samples from the western Atlantic Ocean (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cb\u003eMethods and Data Availability\u003c/b\u003e), we calculated the molar contribution of each element in the lipidome and evaluated the influence of inorganic nutrient availability on membrane lipid stoichiometry and bulk stoichiometry.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePolar lipid species distributions were relatively constant below the equator and more varied in the Northern Hemisphere (Supplementary Figs.\u0026nbsp;1, 2), reflecting seasonal stratification patterns, nutrient availability, and emergent microbial communities\u0026mdash;to the south of ~\u0026thinsp;10 \u0026deg;N, relatively high dissolved phosphate ([PO\u003csub\u003e4\u003c/sub\u003e]) and dissolved inorganic nitrogen (DIN, i.e. [nitrate\u0026thinsp;+\u0026thinsp;nitrite]) concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) resulted in stable, relatively homogenous microbial communities and lipidomes. Above ~\u0026thinsp;10 \u0026deg;N, where sampling spanned rapidly changing spring and summer bloom populations\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, surface PO\u003csub\u003e4\u003c/sub\u003e concentrations were close to the limit of detection from ~\u0026thinsp;10 \u0026deg;N up to the Gulf Stream at ~\u0026thinsp;41 \u0026deg;N, where DIN concentrations were also drawn down to the limit of detection in most of the mixed layer up to the north end of the transect in the Labrador Sea. Despite these diverse conditions, coherent signals in lipidome and bulk stoichiometry clearly emerged.\u003c/p\u003e\u003cp\u003eAcross the entire Atlantic Ocean, lipid C:P, N:P, and S:P ratios in the mixed layer were all negatively correlated with [PO\u003csub\u003e4\u003c/sub\u003e] (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary Fig.\u0026nbsp;1), indicating increased expression of non-P-based lipids in P-scarce environments. While substitution of phospholipids by N-, S-, and C-based lipid headgroups has been well documented in cultures and the environment\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, we find that that this lipid renovation is also clearly detectable as a change in the bulk macromolecule stoichiometry at large scales. Lipid C:P and S:P in the mixed layer showed wide ranges, from ~\u0026thinsp;83:1 to ~\u0026thinsp;215:1 (mean\u0026thinsp;=\u0026thinsp;132:1\u0026thinsp;\u0026plusmn;\u0026thinsp;28) and 0.3 to 1.3 (mean\u0026thinsp;=\u0026thinsp;0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2), respectively, while N:P was more tightly constrained, ranging from 0.95:1 to 1.9:1 (mean\u0026thinsp;=\u0026thinsp;1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2). All three ratios reached maxima in the Sargasso Sea, reflecting acute P-scarcity and widespread headgroup substitution (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c). In contrast, lipid stoichiometry was not significantly correlated with DIN, despite culture studies demonstrating lipid responses to N-limitation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, suggesting whole-community headgroup substitution in the Atlantic Ocean is more strongly influenced by PO\u003csub\u003e4\u003c/sub\u003e availability.\u003c/p\u003e\u003cp\u003eTo assess the influence of lipid stoichiometry on bulk stoichiometry, we quantified the contributions of polar lipid C, N, and P and pigment N relative to bulk particulate pools, and evaluated their relationships in the context of changing nutrient availability. In the 128 surface (\u0026le;\u0026thinsp;40m) samples from North Atlantic cruise AE1319 (~\u0026thinsp;30\u0026deg;N-55\u0026deg;N) where lipids and particulate organic C, N, and P (POC, PON, and POP) were simultaneously measured, membrane lipid C constituted up to 17% of total C (mean\u0026thinsp;=\u0026thinsp;8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4%), and lipid N comprised up to ~\u0026thinsp;4%, with a mean of 1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8%. Lipid P contained up to 23% of total P (10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9%), highlighting the magnitude of POP that can be contributed by the P-rich lipidome (Supplementary Fig.\u0026nbsp;1, Supplementary Table\u0026nbsp;1; particulate CNP data previously published in Lomas et al.\u003csup\u003e33\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eBulk particulate stoichiometry showed strong correlations with nutrient availability (as reported by Lomas et al.\u003csup\u003e3\u003c/sup\u003e, Supplementary Fig.\u0026nbsp;4), with membrane lipid stoichiometry, and with relative lipid contributions to total C, N, and P. The ratios of particulate C:P and C:N were both negatively correlated with PO\u003csub\u003e4\u003c/sub\u003e and DIN, and Lomas et al.\u003csup\u003e3\u003c/sup\u003e found C:P and N:P to be positively correlated with N:P vertical flux ratios. These responses are consistent with previous research showing that an increase in C:P and C:N under P- and N-limitation, respectively, is a common response among diverse species\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, we found lipid ratios were most strongly correlated with POC:POP (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), not PON:POP, and only lipid S:P was correlated with POC:PON (Spearman ρ (rho)\u0026thinsp;=\u0026thinsp;0.54, p\u0026thinsp;=\u0026thinsp;0.01). Bulk POC:POP was highly correlated with lipid C:P (Spearman ρ\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;=\u0026thinsp;7.71 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e) and lipid S:P (Spearman ρ\u0026thinsp;=\u0026thinsp;0.82, p\u0026thinsp;=\u0026thinsp;1.86 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e), showing clear simultaneous regulation of lipid and bulk stoichiometry across environmental gradients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This relationship is strongest below a POC:POP ratio of ~\u0026thinsp;200:1, and is highly linear below that threshold in the case of S:P (Adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.55, p\u0026thinsp;=\u0026thinsp;9.9 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e), reflective of consistently greater headgroup substitution as POC:POP increases. However, in both lipid C:P and lipid S:P, there is a distinct attenuation in the lipid ratio response above POC:POP of ~\u0026thinsp;200:1, suggesting there is an upper physiological limit beyond which microbes cannot substitute headgroups, and therefore a minimum P quota in the community polar lipidome. Indeed, below POC:POP of 200:1, bulk stoichiometry does not significantly change if lipid mass is subtracted, reflecting the in-step modulation of lipid and bulk stoichiometry; but above 200:1, bulk POC:POP would be significantly greater if lipids were removed due to the high proportion of lipid P that cannot be substituted (Supplementary Fig.\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLipidome contributions to total POC, PON, and POP also varied also as a function of bulk stoichiometric ratios (Supplementary Fig.\u0026nbsp;6). Lipid C:POC was negatively correlated with POC:POP (Spearman ρ = -0.39, p\u0026thinsp;=\u0026thinsp;0.029), reflecting a decreasing lipid fraction of total C under P-stress, while lipid P:POP was positively correlated with POC:POP (Spearman ρ\u0026thinsp;=\u0026thinsp;0.40, p\u0026thinsp;=\u0026thinsp;0.026), supporting the hypothesis of non-substitutable P quota in the lipidome. The increase in bulk C:P and concomitant decrease in membrane lipid C:POC would require an increase in a C-rich non-membrane lipid pool like carbohydrates or energy-storage lipids, like eukaryotic triacylglycerols (TAG). However, TAG C did not correlate with POC:POP (Spearman rho = -0.19, p\u0026thinsp;=\u0026thinsp;0.39), possibly because of variable microbial communities or because relative abundance of TAG is highly dependent on sampling time-of-day\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, so the source of the increase in POC:POP is unclear. Lipid N:PON correlated positively with POC:PON (Spearman ρ\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;=\u0026thinsp;2.50 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), and lipid N:PON was negatively correlated with PON:POP (Spearman ρ = -0.66, p\u0026thinsp;=\u0026thinsp;5.2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). This supports previous evidence showing protein N strongly influences cellular N:P levels (citation\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and references therein); however it also suggests that, despite relatively lower contributions of lipid N to total PON (mean\u0026thinsp;=\u0026thinsp;~\u0026thinsp;1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8%), there may also be a minimum N quota in the lipidome, which can increase to nearly 4% of total N, as DIN becomes scarce and protein decreases as a fraction of total POM\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e (Supplementary Fig.\u0026nbsp;6). We also quantified pigment N content, which comprised 0.07\u0026ndash;2.2% of total PON (mean\u0026thinsp;=\u0026thinsp;0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39%). This is slightly lower than previous estimates based on cultures\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, likely due to detrital material. Pigment N:PON was not significantly correlated with either [PO\u003csub\u003e4\u003c/sub\u003e] or [DIN], in contrast with previous hypotheses of pigment N modulation in response to N-stress\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u0026mdash;however, given the latitudinal range and inconsistent time-of-day of sampling, it is possible that other environmental drivers influenced pigment content more than DIN availability. Overall, these results confirm that lipid stoichiometry is highly variable and its regulation is central to cell elemental allocation, contrary to previous hypotheses of discrete pools of fixed stoichiometry (e.g. polyphosphate or pigments)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEvaluating existing lipid indicators of nutrient-stress\u003c/h3\u003e\n\u003cp\u003eThe expansion of oligotrophic gyres due to climate change raises the need for easily detectable biomarkers to indicate nutrient limitation in major taxa\u0026mdash;the traditional method for assessing nutrient limitation, i.e. nutrient addition experiments, are time consuming and complex\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, and an experiment\u0026rsquo;s results are only applicable for relatively small regions. In contrast, lipid biomarker ratios are readily detectable via mass spectrometry and can be measured at ocean-wide scales, even where macronutrient concentrations are at or below the limit of detection. The two most well-described lipidomic indicators of nutrient limitation in phytoplankton are the ratios of S-lipid sulfoquinovosyldiacylglycerol to P-lipid phosphatidylglycerol (SQDG:PG) and the ratio of N-based betaine lipids to the P-lipid phosphatidylcholine (BL:PC). They are well-demonstrated markers of P-stress in cyanobacteria and eukaryotic phytoplankton, respectively\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, and reflect marked differences in P-availability between ocean basins\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and along ocean transects (usually from an area of high-P to low-P)\u003csup\u003e38,39\u003c/sup\u003e. Both ratios increase under P-stress, and decrease when P is more available. However, their interpretation is less clear between mixed communities due to diverse steady-state lipid abundances and stress responses between species. For example, SQDG and PG are produced by all known oxygenic phototrophs\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, but a P-stressed cyanobacteria \u003cem\u003eProchlorococcus\u003c/em\u003e SQDG:PG ratio can range from ~\u0026thinsp;30\u0026ndash;130 while a P-stressed diatom \u003cem\u003eThalassiosira pseudonana\u003c/em\u003e may have a ratio of almost 400\u003csup\u003e12,21,22,41\u003c/sup\u003e. Further, though many eukaryotes increase their ratios of betaine- to phospho-lipids under P-limitation, most P-lipids can be found at significant abundances in both bacteria and eukaryotes\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, increasing the potential ambiguity of these markers and highlighting the need to evaluate them at this scale.\u003c/p\u003e\u003cp\u003eIn the mixed layer, we found the highest SQDG:PG and BL:PC ratios coincided with the lowest PO\u003csub\u003e4\u003c/sub\u003e concentrations between ~\u0026thinsp;10\u0026ndash;30\u0026deg;N in the Sargasso Sea, predictably indicating the region of highest P-stress (Supplementary Fig.\u0026nbsp;7). However, the two markers diverge south of the equator and at higher northern latitudes, and only BL:PC showed a significant negative relationship with [PO\u003csub\u003e4\u003c/sub\u003e] across the combined transects (Supplementary Fig.\u0026nbsp;8; Spearman ρ = -0.28, p\u0026thinsp;=\u0026thinsp;0.01). Moreover, the latitude of maximum P-stress differed between the two, with the highest values for SQDG:PG and BL:PC measured at ~\u0026thinsp;15\u0026deg;N and ~\u0026thinsp;30\u0026deg;N, respectively. These differential responses may indicate taxonomically variable P-stress in different regions\u0026mdash;cyanobacteria could be experiencing greater P-stress than eukaryotes nearer to the equator and in the Southern Hemisphere, as suggested by increased lipid C:P and S:P (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and by metagenome-inferred P-stress in \u003cem\u003eProchlorococcus\u003c/em\u003e in the South Atlantic\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e; it may also simply reflect greater relative abundance of cyanobacteria at lower latitudes\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, as \u003cem\u003eProchlorococcus\u003c/em\u003e produces significantly more SQDG relative to total lipids than other phototrophs\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Therefore, despite these ratios appearing to be strong indicators of P-stress within individual species and within similar microbial communities\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, this uncertainty emphasizes the need for environmental markers with higher taxonomic specificity.\u003c/p\u003e\u003cp\u003eOrnithine lipids (OL) are a compelling candidate for bacteria-specific community analysis\u0026mdash;OL biosynthesis genes occur in around half of genome-sequenced bacteria\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, but no known archaea or eukaryotes\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. And despite OL synthesis requiring two costly N atoms per headgroup (compared to one N atom in most known N-containing membrane lipids), OL upregulation in response to P-stress has been documented in several cultured heterotrophic bacteria, including some strains of SAR11\u003csup\u003e17,37,51\u003c/sup\u003e. We measured OL abundance along the combined transects and in relation to the dominant bacterial membrane lipid, PE. In the mixed layer, we detected a range of OL relative abundances from 0.05% of total lipids in the Labrador Sea to 1.25% in the Sargasso Sea, in concert with drastically elevated log\u003csub\u003e10\u003c/sub\u003eOL:PE, which increased from \u0026minus;\u0026thinsp;2.27 to -0.90 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplemental Figs.\u0026nbsp;7, 9). OL:PE is also significantly negatively correlated with [PO\u003csub\u003e4\u003c/sub\u003e] (Supplemental Fig.\u0026nbsp;8; Spearman ρ = -0.46, p\u0026thinsp;=\u0026thinsp;1.6 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e) indicating there is sufficient P-stress in dominant heterotrophic bacteria to necessitate the use of \u0026ldquo;luxury\u0026rdquo; N in N-rich OL.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe glycolipid, glucuronosyl diacylglycerol (GADG, often labelled GlcADG), which has been more recently discovered in the ocean, has been shown to increase drastically in P-limited bacteria\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e and higher plants\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and we find it to be an effective marker of low P-availability in heterotrophic bacteria. Carini et al.\u003csup\u003e37\u003c/sup\u003e found GADG glycosyltransferases are overrepresented in strains of SAR 11 endemic to the Sargasso Sea relative to other ocean regions, and measured significantly increased abundance of GADG under P-limited conditions. In cultures of one North Atlantic strain, relative abundance of GADG to the typical dominant membrane lipid, PE, increased from undetectable under replete conditions to an average log\u003csub\u003e10\u003c/sub\u003e GADG:PE ratio of -0.61, with GADG comprising an average of ~\u0026thinsp;25% of total lipids\u0026mdash;an order of magnitude higher than in known marine eukaryotes\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Along our combined transects, log\u003csub\u003e10\u003c/sub\u003e GADG:PE ranged from \u0026minus;\u0026thinsp;2.81 to a maximum of -0.41 in the Sargasso Sea (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e., Supplementary Fig.\u0026nbsp;7) and is highly negatively correlated with [PO\u003csub\u003e4\u003c/sub\u003e] (Supplemental Fig.\u0026nbsp;8; Spearman ρ = -0.56, p\u0026thinsp;=\u0026thinsp;5.8 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e). Therefore, despite minor GADG production in some eukaryotes\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, GADG:PE appears to be a strong environmental indicator of microbial lipid renovation in response to P-scarcity, likely driven by heterotrophic bacteria. In comparison with GADG:PE, both measures are highly correlated (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.89, p\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e) and have maxima at the same latitude, confirming P-scarcity responses in the most prevalent marine bacteria.\u003c/p\u003e\n\u003ch3\u003eNovel marker of N- and P- stress in ubiquitous coccolithophores\u003c/h3\u003e\n\u003cp\u003eLastly, we present a novel metric, the ratio of two haptophyte-specific lipid classes which are easily detectable via mass spectrometry as a handful of molecular ions (Supplementary Table\u0026nbsp;2), that can indicate differential N- and P-stress responses in the ubiquitous and globally significant coccolithophore, \u003cem\u003eGephyrocapsa huxleyi\u003c/em\u003e, enabling ecological nutrient-stress inferences where DIN and PO\u003csub\u003e4\u003c/sub\u003e measurements are near and below the limit of measurement (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). In developing this measure, we have elucidated the structure of a novel lipid headgroup, thus far only detected in the morphospecies \u003cem\u003eG. huxleyi\u003c/em\u003e/\u003cem\u003eG. oceanica\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e (Supplementary Figs.\u0026nbsp;10, 11). Combined with another recently discovered lipid, phosphatidyl-S,S-dimethylpropanethiol\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (PDPT), which has only been detected in marine haptophytes including \u003cem\u003eG. huxleyi\u003c/em\u003e and is highly upregulated under N-limitation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, the molecules function as an easily detectable and taxonomically distinct indicator of N- and P- stress in the open ocean.\u003c/p\u003e\u003cp\u003eThe novel lipid class, first detected but uncharacterized by Schleyer et al.\u003csup\u003e55\u003c/sup\u003e, contains only sulfur, carbon, hydrogen, and oxygen, and therefore avoids the typical membrane lipid requirement for P or N. It has an S-based analogous structure to the prominent eukaryotic membrane lipid, diacylglycerylcarboxyhydroxymethylcholine (DGCC), substituting di-methylated sulfur instead of tri-methylated nitrogen\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e (Supplementary Fig.\u0026nbsp;10). Therefore, we propose the nomenclature diacylglycerylcarboxyhydroxysulfocholine (DGCS). Reanalysis of previously published culture data\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e shows significant upregulation in N-limited \u003cem\u003eG. huxleyi\u003c/em\u003e, and non-significant increases under P-limitation (Supplementary Fig.\u0026nbsp;11). However, though DGCS comprises only\u0026thinsp;~\u0026thinsp;0.2\u0026ndash;1.3% of polar lipids in \u003cem\u003eG. huxleyi\u003c/em\u003e and \u003cem\u003eG. oceanica\u003c/em\u003e cultured in nutrient-replete conditions (Supplementary Fig.\u0026nbsp;11), DGCS is present throughout the Atlantic Ocean mixed layer and accounts for almost 3% of the total polar lipid pool in the most nutrient-poor Atlantic samples, irrespective of haptophyte relative abundance (Supplementary Fig.\u0026nbsp;12). Its relative abundance in the photic zone is negatively correlated with [PO\u003csub\u003e4\u003c/sub\u003e] (Spearman rho = -0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;2.2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e) and [DIN] (Spearman rho = -0.80, p\u0026thinsp;\u0026lt;\u0026thinsp;2.2 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e), and though Schleyer et al.\u003csup\u003e55\u003c/sup\u003e found it to be downregulated in response to viral infection, we did not detect a well-documented biosignature of viral infection of \u003cem\u003eG. huxleyi\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, suggesting viruses were not a major stressor during this study. This evidence indicates DGCS is responsive not only to N-limitation, but to N- and P-stress, and appears to be a major adaptation and acclimation strategy for these coccolithophores in nutrient-scarce environments. The other biomarker lipid class, PDPT, has only been detected in marine haptophytes, and has been previously identified as a strong indicator of N-limitation in cultured G. \u003cem\u003ehuxleyi\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Across the transect, PDPT comprised an average of ~\u0026thinsp;1% of total polar lipids, increasing to ~\u0026thinsp;5% above the Gulf Stream where DIN concentrations dropped below the limit of detection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary Figs.\u0026nbsp;1, 13), and PDPT relative abundance in the photic zone negatively correlated with [DIN] (Spearman rho = -0.33, p\u0026thinsp;=\u0026thinsp;2.1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). When the two headgroups are combined into a ratio of DGCS:PDPT, the metric shows a clear maximum in the P-scarce Sargasso Sea and decreases to a minimum north of the Gulf Stream where a eukaryote bloom had reduced [DIN] to below the limit of detection (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), cleanly elucidating a transition from P- to N-stress in the North Atlantic. The consistent abundance of N-stress marker PDPT throughout the transects, superseded by abundance of DGCS in the Sargasso Sea, supports hypotheses of widespread N-limitation in the Atlantic overridden by proximal P-limitation in the Sargasso Sea, inferred from metagenome\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e and nutrient-addition meta analyses\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), demonstrating the power of a single lipidomic dataset to diagnose nutrient stress across ocean-wide geochemical gradients in multiple microbial clades. Thus, all three indices, GADG:PE, OL:PE, and DGCS:PDPT appear to have the capacity to indicate nutrient stress with more taxonomic and functional group resolution than previously developed lipid indicators, which will aid predictions and diagnoses of nutrient stress due to enhanced stratification and the expansion of oligotrophic gyres driven by global climate change.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLipids are a large, labile component of both living and non-living marine organic matter, and the elemental composition of the lipid pool has a significant influence on the biogeochemical cycling of C, N, P, and S. Traditionally, the stoichiometry of polar membrane lipids in marine microbes is assumed to have a fixed proportion of C and P, with a negligible or non-existent contribution of N. We found significantly more N in polar lipids than is frequently cited in the literature\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, comprising an average\u0026thinsp;~\u0026thinsp;1% and up to 4% of total N in the mixed layer, comparable to total N in all measured metabolites in the North Pacific\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Proteomic adaptive responses to nutrient scarcity in phytoplankton operate on miniscule margins, incurring an N-cost equivalent to 0.2% of total N in iron-limited \u003cem\u003eSynechococcus\u003c/em\u003e\u003csup\u003e61\u003c/sup\u003e and 0.044% in vitamin B12-starved diatom \u003cem\u003ePhaeodactylum tricornutum\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Therefore, maintenance of ~\u0026thinsp;1% of N in N-lipids represents a non-negligible N-cost, implying the structure and function of N-lipids is preferable to P-lipids in some physiological scenarios beyond simple P-limitation. In experimental and modeling tests of PC and the N-based betaine lipid diacylglyceryltrimethylhomoserine (DGTS), Bolik et al.\u003csup\u003e63\u003c/sup\u003e found DGTS forms thicker, more rigid, and more repulsive membranes than the P-lipid, and K\u0026uuml;nzler et al.\u003csup\u003e64\u003c/sup\u003e showed betaine lipid localization outside of chloroplasts in the higher plant, \u003cem\u003eLycopodium annotinum\u003c/em\u003e. Abundant research has demonstrated highly specific lipid molecule localization in photosystems and thylakoid membranes\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, but less is known about extraplastidial membrane lipid function and subcellular distribution in phytoplankton and bacteria; therefore, more work is needed to determine the role and localization of lipids in marine microbes, and whether other protein complexes also require specific membrane lipid components for proper functionality.\u003c/p\u003e\u003cp\u003eThe ecological implications of the variation in lipid C:P are also significant. In contrast to cited membrane lipid C:P ratios of ~\u0026thinsp;40:1 in phytoplankton and bacteria in culture\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, the Atlantic surface lipidome C:P changed in tandem with POC:POP, from a lipid C:P of ~\u0026thinsp;83:1 to an upper limit of ~\u0026thinsp;214:1, and the lipid fraction of total P concomitantly increased where paired samples were measured. This implies that, though N- and S-lipids are substituted for P-lipids as lipid C:P increases, other cellular P reservoirs are reallocated at a greater rate than the lipidome due to a minimum lipid P quota. It is unclear whether this is an Atlantic-specific phenomenon, where the AE1319 transect (with paired lipid and POM measurements) transitioned from an N-stressed, eukaryote-dominated community north of the Gulf Stream to the P-stressed, cyanobacteria-dominated Sargasso Sea\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Previous studies of particulate C, N, and P in the global ocean have found a more variable POC:POP in the Atlantic\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, as well as more variable microbial stoichiometry regulation in response to P-limitation than N-limitation\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Similarly, genes for P-uptake, organic P catabolism, and phospholipid renovation are overrepresented in North Atlantic strains of both autotrophic and heterotrophic microorganisms\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e, all suggesting lipid substitution should be especially prevalent in the Atlantic Ocean. Accordingly, we found the highest lipid C:P coincided with high POC:POP communities in the Sargasso Sea. However, we found that these P-stressed communities devoted a\u0026thinsp;~\u0026thinsp;3-fold greater fraction of total P to lipids than the N-stressed communities north of the Gulf Stream, which is in contrast to previous research indicating microbes in the North Pacific commit an order of magnitude greater fraction of P-uptake to P-lipid synthesis than Sargasso Sea communities\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This may be a function of greater P-lipid-turnover in the Pacific, due to the drastically higher PO\u003csub\u003e4\u003c/sub\u003e concentrations, but it may suggest Atlantic and Pacific microbes have fundamentally different approaches to lipidomic regulation, even in low-latitude, cyanobacteria-dominated communities\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Understanding how lipid stoichiometry is regulated in predominantly N-stressed environments like the Pacific Ocean, or trace metal-scarce regions like the Southern Ocean, will further elucidate the patterns of microbial physiology and elemental distribution throughout the global ocean. Our results highlight the plasticity of that distribution within the microbial lipidome, and the effects of that modulation on total particulate stoichiometry throughout the Atlantic Ocean.\u003c/p\u003e"},{"header":"Methods and Data Availability","content":"\u003cp\u003eDetailed methods available in Holm et al\u003csup\u003e29\u003c/sup\u003e. In brief, a total of 344 1\u0026ndash;2 L seawater samples from 73 stations along four transects were collected via CTD-rosette mounted Niskin bottles,filtered onto 0.22 \u0026micro;m Durapore filters (Millipore Sigma), and the filters were wrapped in combusted aluminum foil and immediately flash frozen in liquid nitrogen and stored in the headspace of a liquid nitrogen dewar. Samples were extracted via a modified Bligh and Dyer protocol\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e, then analyzed via high performance liquid chromatography-high resolution accurate mass-mass spectrometry, as detailed in Popendorf et al\u003csup\u003e39,69\u003c/sup\u003e. Mass spectral data was then processed through the xcms\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e, CAMERA\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, and LOBSTAHS\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e pipelines using the R programming language\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e; the map in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e was produced using the R-package ggOceanMaps\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Lipid identification, abundance, and mixed layer depth data was available through Holm et al.\u003csup\u003e29\u003c/sup\u003e, where full analytical methods can be found, except for lipid classes PDPT, DGCS, OL, sulfur-amino-lipids (SAL; Supplementary Fig.\u0026nbsp;2), and betaine-like lipids (BLL), which were confirmed via published ms/ms fragmentation patterns\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, adduct hierarchies\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, and retention time patterns. In addition to the 938 unique lipid molecules in the original dataset, we identified and quantified 77 additional lipids including pigments, increasing the number of unique annotated molecules by 8% and total lipid abundance by 9%. Commercial standards are not available for these lipid classes, so we used a best-matched-standard approach similar to Heal et al.\u003csup\u003e76\u003c/sup\u003e based on known ionization differences for similar headgroup functional groups (i.e. reduced headgroup N ionizes more efficiently than reduced S and glycolipid headgroups). Best-matched standards are detailed in Supplemental Table\u0026nbsp;3. Liu et al.\u003csup\u003e77\u003c/sup\u003e also published a reanalysis of the original dataset, including unannotated mass spectral features; our targeted approach is complementary to their untargeted statistical cluster analysis.\u003c/p\u003e\u003cp\u003eInorganic nutrient data was reproduced from Baer et al. (2017)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, Durkin et al. (2016)\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, and Van Mooy et al. (2015)\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Particulate organic carbon, nitrogen, and phosphorus data was reproduced from Lomas et al.\u003csup\u003e3\u003c/sup\u003e via the Biological and Chemical Oceanographic Data Management Office\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Methods\u003c/h2\u003e\u003cp\u003eA statistical test was considered significant below a \u003cem\u003ep\u003c/em\u003e-value of \u0026lt;\u0026thinsp;0.05 and significance was reported at four significance levels: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Correlation was determined using Spearman rank order correlation except when testing linearity, where Pearson correlation coefficients were calculated. Loess smoothing was used to show trendlines across latitude, with parameters detailed in figure captions.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe thank C. Dean for \u003cem\u003eG. oceanica\u003c/em\u003e biomass. Funding for this work was provided by the NSF and Simons Foundation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTanioka T et al (2022) Global patterns and predictors of C:N:P in marine ecosystems. Commun Earth Environ 3:1\u0026ndash;9\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaer SE, Lomas MW, Terpis KX, Mouginot C, Martiny AC (2017) Stoichiometry of Prochlorococcus, Synechococcus, and small eukaryotic populations in the western North Atlantic Ocean. Environ Microbiol 19:1568\u0026ndash;1583\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLomas MW et al (2021) Varying influence of phytoplankton biodiversity and stoichiometric plasticity on bulk particulate stoichiometry across ocean basins. Commun Earth Environ 2:1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInomura K, Deutsch C, Jahn O, Dutkiewicz S, Follows MJ (2022) Global patterns in marine organic matter stoichiometry driven by phytoplankton ecophysiology. Nat Geosci 15:1034\u0026ndash;1040\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRedfield AC, Ketchum BH, Richards FA (1963) The influence of organisms on the composition of sea-water. in\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiefer JD et al (2024) Latitudinal patterns in ocean C:N:P reflect phytoplankton acclimation and macromolecular composition. \u003cem\u003eProc. Natl. Acad. Sci. U.S.A.\u003c/em\u003e 121, e2404460121\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoreno AR, Martiny AC (2018) Ecological Stoichiometry of Ocean Plankton. Annual Rev Mar Sci 10:43\u0026ndash;69\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwiatkowski L, Aumont O, Bopp L, Ciais P (2018) The Impact of Variable Phytoplankton Stoichiometry on Projections of Primary Production, Food Quality, and Carbon Uptake in the Global Ocean. Glob Biogeochem Cycles 32:516\u0026ndash;528\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeider R, La Roche J (2002) Redfield revisited: variability of C:N:P in marine microalgae and its biochemical basis. Eur J Phycol 37:1\u0026ndash;17\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWakeham SG, Lee C, Hedges JI, Hernes PJ, Peterson MJ (1997) Molecular indicators of diagenetic status in marine organic matter. Geochim Cosmochim Acta 61:5363\u0026ndash;5369\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEdwards BR (2023) Lipid Biogeochemistry and Modern Lipidomic Techniques. Annu Rev Mar Sci 15:485\u0026ndash;508\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Mooy BAS et al (2009) Phytoplankton in the ocean use non-phosphorus lipids in response to phosphorus scarcity. Nature 458:69\u0026ndash;72\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVillar E et al (2018) The Ocean Gene Atlas: exploring the biogeography of plankton genes online. Nucleic Acids Res 46:W289\u0026ndash;W295\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLauro FM et al (2009) The genomic basis of trophic strategy in marine bacteria. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 106, 15527\u0026ndash;15533\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDupont CL et al (2012) Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage. ISME J 6:1186\u0026ndash;1199\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWestermann LM et al (2023) Bacterial catabolism of membrane phospholipids links marine biogeochemical cycles. Sci Adv 9:eadf5122\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSebasti\u0026aacute;n M et al (2016) Lipid remodelling is a widespread strategy in marine heterotrophic bacteria upon phosphorus deficiency. ISME J 10:968\u0026ndash;978\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchubotz F, Xie S, Lipp JS, Hinrichs K-U, Wakeham SG (2018) Intact polar lipids in the water column of the eastern tropical North Pacific: abundance and structural variety of non-phosphorus lipids. Biogeosciences 15:6481\u0026ndash;6501\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKabeya N et al (2018) Genes for de novo biosynthesis of omega-3 polyunsaturated fatty acids are widespread in animals. Sci Adv 4:eaar6849\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRussell NJ, Nichols DS (1999) Polyunsaturated fatty acids in marine bacteria \u0026mdash; a dogma rewritten. Microbiology 145:767\u0026ndash;779\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCa\u0026ntilde;avate JP, Armada I, Hachero-Cruzado I (2017) Interspecific variability in phosphorus-induced lipid remodelling among marine eukaryotic phytoplankton. New Phytol 213:700\u0026ndash;713\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLowenstein DP, Mayers K, Fredricks HF, Van Mooy BAS (2021) Targeted and untargeted lipidomic analysis of haptophyte cultures reveals novel and divergent nutrient-stress adaptations. Org Geochem 161:104315\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFulton JM et al (2014) Novel molecular determinants of viral susceptibility and resistance in the lipidome of Emiliania huxleyi. Environ Microbiol 16:1137\u0026ndash;1149\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHunter JE, Frada MJ, Fredricks HF, Vardi A, Van Mooy BAS (2015) Targeted and untargeted lipidomics of Emiliania huxleyi viral infection and life cycle phases highlights molecular biomarkers of infection, susceptibility, and ploidy. Front Mar Sci 2\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Y et al (2017) Sphingolipids in marine microalgae: Development and application of a mass spectrometric method for global structural characterization of ceramides and glycosphingolipids in three major phyla. Anal Chim Acta 986:82\u0026ndash;94\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwiatkowski L et al (2020) Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections. Biogeosciences 17:3439\u0026ndash;3470\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeutsch C, Weber T (2012) Nutrient Ratios as a Tracer and Driver of Ocean Biogeochemistry. Annual Rev Mar Sci 4:113\u0026ndash;141\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFollows MJ, Dutkiewicz S, Grant S, Chisholm SW (2007) Emergent Biogeography of Microbial Communities in a Model Ocean. Science 315:1843\u0026ndash;1846\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHolm HC et al (2022) Global ocean lipidomes show a universal relationship between temperature and lipid unsaturation. Science 376:1487\u0026ndash;1491\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHolm H, Van Mooy BAS (2022) hholm/OceanLipidome: Version 1.0.2. Zenodo \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.7035947\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.7035947\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiovannoni SJ, Vergin KL (2012) Seasonality in Ocean Microbial Communities. Science 335:671\u0026ndash;676\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang B et al (2019) Betaine lipid and neutral lipid production under nitrogen or phosphorus limitation in the marine microalga Tisochrysis lutea (Haptophyta). Algal Res 40:101506\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLomas MW, Bonachela JA, Levin SA, Martiny AC (2014) Impact of ocean phytoplankton diversity on phosphate uptake. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 111, 17540\u0026ndash;17545\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBecker KW et al (2018) Daily changes in phytoplankton lipidomes reveal mechanisms of energy storage in the open ocean. Nat Commun 9:5179\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiefer JD et al (2019) The Macromolecular Basis of Phytoplankton C:N:P Under Nitrogen Starvation. Front Microbiol 10\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrowning TJ, Moore CM (2023) Global analysis of ocean phytoplankton nutrient limitation reveals high prevalence of co-limitation. Nat Commun 14:5014\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarini P et al (2015) SAR11 lipid renovation in response to phosphate starvation. Proc Natl Acad Sci USA 112:7767\u0026ndash;7772\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartin P, Dyhrman ST, Lomas MW, Poulton NJ, Van Mooy BAS (2014) Accumulation and enhanced cycling of polyphosphate by Sargasso Sea plankton in response to low phosphorus. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 111, 8089\u0026ndash;8094\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePopendorf KJ, Lomas MW, Van Mooy BA (2011) Microbial sources of intact polar diacylglycerolipids in the Western North Atlantic Ocean. Org Geochem 42:803\u0026ndash;811\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLipids in Photosynthesis. (Springer Neth, (2009) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-90-481-2863-1\u003c/span\u003e\u003cspan address=\"10.1007/978-90-481-2863-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartin P, Van Mooy BA, Heithoff A, Dyhrman ST (2011) Phosphorus supply drives rapid turnover of membrane phospholipids in the diatom Thalassiosira pseudonana. ISME J 5:1057\u0026ndash;1060\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeiger O, L\u0026oacute;pez-Lara IM, Sohlenkamp C (2013) Phosphatidylcholine biosynthesis and function in bacteria. Biochim et Biophys Acta (BBA) - Mol Cell Biology Lipids 1831:503\u0026ndash;513\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUstick LJ et al (2021) Metagenomic analysis reveals global-scale patterns of ocean nutrient limitation. Science 372:287\u0026ndash;291\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFlombaum P et al (2013) Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 110, 9824\u0026ndash;9829\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Mooy BAS, Rocap G, Fredricks HF, Evans CT, Devol AH (2006) Sulfolipids dramatically decrease phosphorus demand by picocyanobacteria in oligotrophic marine environments. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 103, 8607\u0026ndash;8612\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBent SM et al (2024) Lipid biochemical diversity and dynamics reveal phytoplankton nutrient-stress responses and carbon export mechanisms in mesoscale eddies in the North Pacific Subtropical Gyre. Front Mar Sci 11\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones RA et al (2021) Phosphorus stress induces the synthesis of novel glycolipids in Pseudomonas aeruginosa that confer protection against a last-resort antibiotic. ISME J 15:3303\u0026ndash;3314\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith AF et al (2019) Elucidation of glutamine lipid biosynthesis in marine bacteria reveals its importance under phosphorus deplete growth in Rhodobacteraceae. ISME J 13:39\u0026ndash;49\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeiger O, Gonz\u0026aacute;lez-Silva N, L\u0026oacute;pez-Lara IM, Sohlenkamp C (2010) Amino acid-containing membrane lipids in bacteria. Prog Lipid Res 49:46\u0026ndash;60\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVences-Guzm\u0026aacute;n M\u0026Aacute;, Geiger O, Sohlenkamp C (2012) Ornithine lipids and their structural modifications: from A to E and beyond. FEMS Microbiol Lett 335:1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim S-K et al (2018) Bacterial ornithine lipid, a surrogate membrane lipid under phosphate-limiting conditions, plays important roles in bacterial persistence and interaction with host. Environ Microbiol 20:3992\u0026ndash;4008\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiercks H et al (2015) Accumulation of Novel Glycolipids and Ornithine Lipids in Mesorhizobium loti under Phosphate Deprivation. J Bacteriol 197:497\u0026ndash;509\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkazaki Y et al (2013) A new class of plant lipid is essential for protection against phosphorus depletion. Nat Commun 4:1510\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBendif EM et al (2019) Repeated species radiations in the recent evolution of the key marine phytoplankton lineage Gephyrocapsa. Nat Commun 10:4234\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchleyer G et al (2019) In plaque-mass spectrometry imaging of a bloom-forming alga during viral infection reveals a metabolic shift towards odd-chain fatty acid lipids. Nat Microbiol 4:527\u0026ndash;538\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBisseret P et al (1984) Occurrence of phosphatidylsulfocholine, the sulfonium analog of phosphatidylcholine in some diatoms and algae. Biochim et Biophys Acta (BBA) - Lipids Lipid Metabolism 796:320\u0026ndash;327\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaber CP et al (2018) Coccolithovirus facilitation of carbon export in the North Atlantic. Nat Microbiol 3:537\u0026ndash;547\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVardi A et al (2009) Viral Glycosphingolipids Induce Lytic Infection and Cell Death in Marine Phytoplankton. Science 326:861\u0026ndash;865\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoore CM et al (2013) Processes and patterns of oceanic nutrient limitation. Nat Geosci 6:701\u0026ndash;710\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoysen AK et al (2021) Particulate Metabolites and Transcripts Reflect Diel Oscillations of Microbial Activity in the Surface Ocean. \u003cem\u003emSystems\u003c/em\u003e 6, e00896-20\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMackey KRM et al (2015) Divergent responses of Atlantic coastal and oceanic Synechococcus to iron limitation. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 112, 9944\u0026ndash;9949\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBertrand EM et al (2013) Methionine synthase interreplacement in diatom cultures and communities: Implications for the persistence of B12 use by eukaryotic phytoplankton. Limnol Oceanogr 58:1431\u0026ndash;1450\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBolik S et al (2023) Lipid bilayer properties potentially contributed to the evolutionary disappearance of betaine lipids in seed plants. BMC Biol 21:275\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026uuml;nzler K, Eichenberger W, Radunz A (1997) Intracellular localization of two betaine lipids by cell fractionation and immunomicroscopy. Z Naturforsch C J Biosci 52:487\u0026ndash;495\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKern J, Zouni A, Guskov A, Krau\u0026szlig; N (2009) Lipids in the Structure of Photosystem I, Photosystem II and the Cytochrome b6f Complex. In: Wada H, Murata N (eds) Lipids in Photosynthesis: Essential and Regulatory Functions. Springer Netherlands, Dordrecht, pp 203\u0026ndash;242. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-90-481-2863-1_10\u003c/span\u003e\u003cspan address=\"10.1007/978-90-481-2863-1_10\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMizusawa N, Wada H (2012) The role of lipids in photosystem II. Biochim et Biophys Acta (BBA) - Bioenergetics 1817:194\u0026ndash;208\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSosa OA, Repeta DJ, DeLong EF, Ashkezari MD, Karl DM (2019) Phosphate-limited ocean regions select for bacterial populations enriched in the carbon\u0026ndash;phosphorus lyase pathway for phosphonate degradation. Environ Microbiol 21:2402\u0026ndash;2414\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBligh EG, Dyer WJ, A RAPID METHOD, OF TOTAL LIPID EXTRACTION AND PURIFICATION (1959) Can J Biochem Physiol 37:911\u0026ndash;917\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHummel J et al (2011) Ultra Performance Liquid Chromatography and High Resolution Mass Spectrometry for the Analysis of Plant Lipids. Front Plant Sci 2\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith CA, Want EJ, O\u0026rsquo;Maille G, Abagyan R, Siuzdak GXCMS (2006) Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification. Anal Chem 78:779\u0026ndash;787\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuhl C, Tautenhahn R, B\u0026ouml;ttcher C, Larson TR, Neumann SCAMERA (2012) An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets. Anal Chem 84:283\u0026ndash;289\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCollins JR, Edwards BR, Fredricks HF, Van Mooy BAS (2016) LOBSTAHS: An Adduct-Based Lipidomics Strategy for Discovery and Identification of Oxidative Stress Biomarkers. Anal Chem 88:7154\u0026ndash;7162\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Core Team (2020) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVihtakari M (2024) \u003cem\u003eggOceanMaps: Plot Data on Oceanographic Maps Using \u0026lsquo;Ggplot2\u0026rsquo;\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith AF et al (2021) A novel class of sulfur-containing aminolipids widespread in marine roseobacters. ISME J 15:2440\u0026ndash;2453\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeal KR et al (2021) Marine Community Metabolomes Carry Fingerprints of Phytoplankton Community Composition. \u003cem\u003emSystems\u003c/em\u003e 6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/msystems.01334-20\u003c/span\u003e\u003cspan address=\"10.1128/msystems.01334-20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu W et al (2025) Unraveling plankton adaptation in global oceans through the untargeted analysis of lipidomes. Sci Adv 11:eads4605\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDurkin CA, Van Mooy BAS, Dyhrman ST, Buesseler KO (2016) Sinking phytoplankton associated with carbon flux in the Atlantic Ocean. Limnol Oceanogr 61:1172\u0026ndash;1187\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Mooy BAS et al (2015) Major role of planktonic phosphate reduction in the marine phosphorus redox cycle. Science 348:783\u0026ndash;785\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLomas MW, Martiny A (2013) Depth profile data from R/V Atlantic Explorer AE1319 in the NW Atlantic from Aug-Sept. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hdl.handle.net/1912/26396\u003c/span\u003e\u003cspan address=\"https://hdl.handle.net/1912/26396\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8022751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8022751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe stoichiometry of particulate organic matter (POM) in the ocean influences the global carbon, nitrogen, and phosphorus cycles, but elemental distributions within macromolecule classes are not well constrained. Using publicly available datasets of lipid abundances, nutrient concentrations, and POM stoichiometry, we conduct the first basin-scale survey of lipid stoichiometry along a north-south transect spanning the western Atlantic Ocean from ~\u0026thinsp;40\u0026deg;S to ~\u0026thinsp;55\u0026deg;N, and demonstrate that surface ocean lipid stoichiometry is highly variable, is primarily linked to phosphate (P) availability, and is strongly correlated with POM stoichiometry. We evaluate lipid biomarkers of microbial nutrient stress and find they are not uniformly in agreement (i.e. some indicate P-stress in regions where others do not). To that end, we describe a novel polar lipid class, diacylglycerylcarboxyhydroxysulfocholine, thus far detected only in the coccolithophore genus \u003cem\u003eGephyrocapsa\u003c/em\u003e, potentially indicative of nitrogen (N) and phosphorus stress. We also advance three new biomarkers of nutrient stress, specific to oligotrophic heterotrophic bacteria and to the globally significant coccolithophore, \u003cem\u003eG. (ex Emiliania) huxleyi\u003c/em\u003e. We find they effectively elucidate a transition from proximal N- to P-stress in the Atlantic Ocean.\u003c/p\u003e","manuscriptTitle":"Lipid stoichiometry and biomarkers reflect microbial acclimation and nutrient stress across the Atlantic Ocean","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 06:32:26","doi":"10.21203/rs.3.rs-8022751/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"97a2c78a-9c61-4cca-8d52-7343d98e5ba8","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":58142510,"name":"Earth and environmental sciences/Ocean sciences/Marine chemistry"},{"id":58142511,"name":"Earth and environmental sciences/Ecology/Biogeochemistry/Element cycles"},{"id":58142512,"name":"Earth and environmental sciences/Ecology/Biooceanography/Microbial biooceanography"}],"tags":[],"updatedAt":"2026-04-24T17:45:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-19 06:32:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8022751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8022751","identity":"rs-8022751","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}