One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.
Organic molecules dissolved in seawater are cycled through the sunlit ocean by the billion marine microbes living in each litre of surface water1 (Fig. 1). This process involves almost half of the annual net primary production (NPP) of the ocean; therefore, even minor changes in its output lead to important effects on a global scale. Much remains unknown about the chemicals passing through the labile dissolved organic carbon (DOC) pool, largely because they are highly bioavailable and they are almost simultaneously produced and consumed by diverse marine microbes. Specifically, the surface ocean labile DOC pool has a turnover of about three days2, with steady-state concentrations in the range of nanomolar to picomolar3,4 for compounds abundant enough to be measured with existing methods and below this range for many others.
This low abundance of microbial metabolites in seawater presents a conundrum, as compounds supporting one of the most important fluxes in the carbon cycle of Earth are among the most challenging to study. In this Review, we summarize our current understanding of the sources and fate of marine microbial metabolites in the surface ocean and describe current and emerging analytical approaches for learning about their roles.
Marine sources of labile DOC
Most labile DOC of marine origin is produced by one of three sources: actively photosynthesizing phytoplankton, senescing and dead phytoplankton, or heterotrophic organisms.
Actively photosynthesizing marine phytoplankton generate exometabolites (metabolites released into surrounding seawater) that form a pool of carbon named ‘extracellular release’5 or ‘dissolved primary production’6 (Fig. 2). These released compounds are resources that are now lost from phytoplankton cells, and different hypotheses for the mechanisms underlying their release have been proposed7. For example, the million-fold concentration differential between the inside and outside of phytoplankton cell membranes8 could drive a molecular diffusion process by which healthy cells continually leak a fraction of their internal metabolites into seawater9. Leakage would be a passive process, and low-molecular-weight (<600 Da) and hydrophobic compounds (due to cell membrane composition) are more likely to leak out7,9,10. In active mechanisms of extracellular release, labile DOC would be excreted rather than lost from living phytoplankton, which enables control over the rates and composition of the released metabolites. Physiological stresses imposed by photosynthesis are likely to drive active carbon export, and several mechanisms related to stress have been proposed. For example, when carbon dioxide (CO2) is limiting, the principal carbon-fixation enzyme binds oxygen instead, which results in the production and release of toxic photorespiration products11 such as glycolate12. Conversely, when nutrients are limiting but inorganic carbon and irradiance are not, carbon fixation can outpace macromolecule synthesis13 and cause extracellular release of the excess fixed carbon in the form of polysaccharides and organic acids, which are referred to as ‘photosynthetic overflow’13,14,15,16. Nutrient stress has also been proposed to drive organic carbon excretion as a by-product of cells increasing their ATP/ADP ratio (that is, reaching a higher intracellular energy state) to mitigate the free-energy costs of transport of low concentration nutrients17. These nutrient-limitation-driven mechanisms should favour the excretion of carbon-rich compounds17. At points in the diel cycle and regions in the photic zone where light shock can occur, extracellular release from phytoplankton may occur in response to a redox imbalance18,19. Finally, phytoplankton actively release molecules that trigger behavioural or physiological changes in neighbouring microbes. These metabolites often have distinctive chemical structures and can function as defence compounds20, pheromones21 or toxins22,23. Given the different mechanisms and drivers of release, the chemical composition of phytoplankton exometabolites should differ from the composition of endometabolites (those present in the cell). This has indeed been observed for amino acids, carbohydrates and carboxylic acids24,25,26. Regardless of the release mechanism, the tight coordination in daily activity patterns between phytoplankton and heterotrophic bacteria that track the diel irradiance cycle18,27,28 establishes a major role for extracellular products of photosynthetic activity in carbon transfer in the surface ocean (Fig. 3).
Phytoplankton senescence and death liberate endometabolites that form a second large source of labile molecules29,30 (Fig. 2). For example, sloppy feeding (escape of organic matter during grazing) or egestion (release of organic matter remaining undigested in guts and food vacuoles of predators)31,32,33 is carried out by protist and zooplankton predators and results in the release of dissolved organic matter from phytoplankton prey, which liberates 10–30% of prey carbon. Viral lysis of phytoplankton cells releases various metabolites34,35, the composition of which depends on host reprogramming during infection36,37. Recent evidence suggests that microparasitic fungi also change the intracellular chemistry of their host, similarly modifying the composition of released metabolites38. Senescence or ‘autocatalytic cell death’ triggered by nutrient limitation or other stresses is also a source of metabolites10,29 and may be particularly important in declining blooms39,40.
Finally, heterotrophs, including bacteria, archaea and protists, are the third main source of metabolic by-products generated by excretion or viral lysis32,41,42,43 (Fig. 2; heterotrophic activities of mixotrophic protists are counted here44). Viral infection can modify bacterial endometabolomes45 through reprogramming of host metabolism45,46, which is an important component of labile DOC given estimates that one in three ocean bacteria are infected at any time34. Organic molecules originating from heterotrophic protists and zooplankton can be rich in organic nitrogen47 and are readily scavenged by bacteria33. Heterotrophic marine bacteria and archaea release thousands of different molecules48,49,50,51 that might serve as bacterial substrates52. Liberation of labile compounds also occurs during bacterial solubilization of polymeric components of particulate detritus53, such as proteins and polysaccharides, whose degradation products diffuse from the particle surface54,55,56,57.
Fraction of carbon routed through microbial metabolites
Each year, heterotrophic marine bacteria are predicted to process ~20 PgC from the labile DOC pool (Fig. 1), as estimated by both geochemical methods based on DOC reactivity2 and ecological approaches based on bacterial carbon demand58 (that is, bacterial secondary production plus respiration). This routing of recently fixed carbon to bacteria through labile DOC is one of the largest and most rapid fluxes of organic carbon in the biosphere. Two early estimates of marine carbon processed through the microbe–metabolite network were 10–50% (ref. 59) and 40% (ref. 58) of ocean NPP, and a recent compilation of bacterial carbon demand values is consistent with these (52% of NPP60). Partitioning of inputs among the three major sources estimated from published values for labile DOC release by microbial and zooplankton activities suggested that ~40% of labile DOC originates directly from phytoplankton as extracellular release from photosynthesizing cells, ~40% is released from phytoplankton death processes (senescence, sloppy feeding, viral and fungal lysis) and ~20% is released from heterotroph excretion and death processes60. The magnitude of this last source is constrained by its derivation from secondary production, and therefore from organic carbon pools diminished by respiratory losses61.
Molecular composition of labile DOC
The molecules that make up the labile DOC pool of the ocean have been highly challenging to identify. Early studies proposed that amino acids, carbohydrates, osmolytes and small carboxylic acids (in particular the photorespiration product glycolate) are the main substrates for surface ocean bacteria1,14,62,63. These compound classes were suggested by chemical analyses of plankton cells under the assumption that internal metabolite pools are proxies for released pools. Metabolites in intracellular pools are easier to measure than those in external pools because they typically have concentrations that are several orders of magnitude higher than in the surrounding seawater63 (Table 1; micromolar to millimolar14,64,65,66,67 internal versus picomolar to nanomolar3,4,67 external). Furthermore, endometabolite samples can be concentrated by capturing cells on filters. However, paired analyses of endometabolites and exometabolites in phytoplankton cultures reveal that internal pools do not closely correspond to external pools67, although viral lysis and sloppy feeding may be exceptions. This selective release of phytoplankton metabolites is not surprising but limits the accuracy of using endometabolomes to predict labile DOC composition. Nonetheless, endometabolite analyses of marine plankton have yielded candidates for the labile DOC inventory (Table 1). Examples include quaternary amines (for example, choline, dimethylglycine and trimethylamine-N-oxide), organic sulfur compounds (for example, gonyol, cysteate, dimethylsulfonioacetate and sulfolactate) and amino acid derivatives (for example, homarine, trigonelline and ornithine)18,65,67,68,69,70,71,72,73,74,75,76 (Table 1).
Labile DOC components can be coarsely categorized on the basis of their physiological and ecological roles in the microbe–metabolite network of the ocean. Here we define three broad categories that capture several of these roles: substrates, facilitators and ecological signals (Box 1).
Substrate metabolites are defined as the compounds that are actively assimilated by marine bacteria for carbon and energy, and transferred among microbes in quantities that sustain growth, reproduction, and the cycles of carbon and other elements. Amino acids77,78, polyamines79,80, carbohydrates81,82,83, sulfonate and sulfonium compounds18,69, carboxylic acids72,75,76,84, and nucleosides70,72,75 all function as bacterial substrates in surface seawater (Table 1). Molecules in this category contribute most directly to flux by serving as the conduits or ‘currencies’ that move carbon among marine microbes.
Facilitator metabolites are defined as molecules that enable biochemical reactions and can be reused and exchanged among microbes (Box 1). Those that have been identified in seawater include the soluble B vitamins (B1, B7 and B12)85,86,87, iron siderophores88,89 and other biosynthesized metal-binding molecules90,91, all of which have steady-state concentrations at the limit of bacterial uptake kinetics (<1 pM to tens of pM92,93,94,95), although concentrations can fluctuate in time and space. Both substrate and facilitator molecules are also considered ‘public goods’ if they are energetically expensive to synthesize and released by only a subset of the microbial community96; public goods can set the stage for metabolic dependencies within the microbial network of the ocean97.
Ecological signal metabolites or ‘infochemicals’ are defined as compounds that orchestrate specialized microbial interactions under specific conditions98,99. Sourced and shared by microbes, they serve as the medium for interactions by altering community physiological or behavioural features through chemicals passed among members (Box 1). Microbially produced hormones, such as indole acetic acid100, and quorum-sensing molecules, such as acyl homoserine lactones101, are among the ecological signal compounds thus far discovered in ocean communities or cultivated marine microorganisms. Molecules that inhibit growth or cause mortality42,75,102 are also categorized as ecological signal compounds in this Review because of their role in modifying physiology (albeit negatively) of other microbes. Both facilitator and ecological signal metabolites can indirectly contribute to labile DOC cycling by affecting the rates and routes of carbon flux without constituting a substantial mass fraction themselves.
Challenges to understanding roles of labile DOC
Although expertise in marine metabolites is growing, we cannot yet unravel the roles of labile DOC molecules in carbon flux and fate in the surface ocean103. Roadblocks to progress can be boiled down to one (long) sentence: hidden among the hundreds of thousands of mostly unknown organic molecules embedded in a million-fold higher salt concentration are the currencies of a very large carbon flux through a very small carbon reservoir. Here, we pull apart this sentence and explain in more detail the specific challenges it captures.
Hidden in the highly complex marine DOC pool…
Each of the tremendous number of distinct microbial organisms that occupy surface seawater104,105 can release tens to thousands of different molecules48,49,51,67,106,107,108,109. Genome-scale metabolic models based on flux balance analysis agree that microbial cells simultaneously maintain many hundreds of different endometabolites110 that can potentially be lost or exported as labile DOC. Some of these are predicted to be ‘costless’ metabolites, such as by-products of anabolic and catabolic pathways released without any fitness costs to the microbe111. Untargeted mass spectrometry (MS) and nuclear magnetic resonance (NMR) analyses have indeed uncovered hundreds of thousands of distinct organic features in marine DOC112,113, of which only 1–5% can be identified114,115,116. Manually intensive, low-throughput identification pipelines are currently the primary approach used to convert these unidentified compounds into chemical insight. Of course, the biological reactivities of all the unknown compounds are also unknown; therefore, biogeochemically important molecules cannot be singled out of this multitude. In short, we cannot identify which of these compounds are important substrates, facilitator metabolites or ecological signal metabolites, or are otherwise uninvolved in the labile DOC cycle.
…embedded in a salty matrix…
Salt is a frustrating problem for the analysis of marine DOC. In MS analysis, non-volatile salts interfere with ion formation and degrade spectral quality117. In NMR analysis, salts reduce probe sensitivity118. Accordingly, the development of methods to remove organic compounds from their salty matrix has been an essential endeavour in chemical oceanography. Strategies that have been explored include water and salt removal via tangential flow filtration (TFF)119, reverse osmosis/electrodialysis120 and metabolite capture on solid-phase extraction resins121,122. Yet only 10–40% of marine DOC is captured with these methods, with a bias towards moderate- (>300 Da) and high- (>1,000 Da) molecular-weight compounds. In particular, small and polar metabolites, which are characteristics of many labile biomolecules, are lost during TFF or reverse osmosis/electrodialysis and are not well retained on solid-phase extraction resins such as the styrene-divinylbenzene polymer PPL122. Other saline fluids that are more easily analysed for metabolite content have higher concentrations of molecules in a lower concentration of salt, for example, millimolar metabolite concentrations (up to million-fold higher than seawater) in 1–10 ppt salt solutions (up to 30-fold lower than seawater) characteristic of blood and urine. For now, the state-of-the-art techniques used to isolate organic molecules from seawater remain strongly biased against the low-molecular-weight and polar exometabolites122, which form the majority of components of labile DOC.
…is a small metabolite reservoir with a very large flux
Labile DOC release is largely balanced over time by its consumption by heterotrophic bacteria, which maintain individual compounds in the picomolar-to-low-nanomolar concentration range18,93,123,124,125 or lower. Specific uptake affinities for DOC components in oligotrophic marine bacteria are among the highest reported, for example, 150-fold higher than for well-studied model bacteria93. Oligotrophic bacteria (those that can survive on low organic matter concentrations) are so efficient at depleting the labile DOC pool that calculations suggest that they must simultaneously scavenge for at least 34 different substrates to grow at one generation per day92. Copiotrophic marine bacteria (those that require higher organic matter concentrations) have lower substrate affinities but higher maximum uptake rates that allow them to rapidly draw down local substrate spikes on the order of 100 nM to 1 μM (ref. 126). It may be possible for a single bacterial taxon to switch between these life history strategies127,128, but it is more probable that genetic makeup (for example, genome size, content and regulation) locks a heterotrophic bacterium into either a high- or low-affinity strategy129,130,131. Regardless of how affinity is apportioned among cells, the communities of marine bacteria in aggregate are capable of both high affinity and fast uptake to maintain low concentrations of labile DOC components in seawater, and are considerably better at detecting DOC than our state-of-the art chemical methods. Although targeted chemical methods have the sensitivity to directly measure some classes of metabolites in seawater, for example, amino acids132, sugars133 and organic sulfur molecules69, untargeted methods that aim to maximize the number and novelty of detected molecules are challenged by the low natural concentrations4.
The difficulty of characterizing the ‘small reservoir’ of labile DOC within the total DOC pool is intertwined with its ‘large flux’. Cycling rates of metabolites are not predictable by their concentration in seawater and may even be inversely related134. For example, dimethylsulfoniopropionate (DMSP) has been estimated to support up to 10% of total bacterial carbon demand in the marine photic zone135 yet has a steady-state concentration in the surface ocean of just ~3 nM (ref. 136; Box 2). The most common method for estimating flux of recently fixed carbon into bacterial cells is to measure exudates released from 14C-labelled phytoplankton cells in the absence of bacterial uptake32, the so-called dissolved primary production. These estimates of carbon available for bacterial scavenging span a wide range (from 4% to 47% of NPP15) and provide no information on the specific compounds involved. Another approach captures the combined flux of labile DOC from all principal sources by determining the bacterial carbon demand as a percentage of ecosystem NPP. Results from this methodology suggest that ~40–60% of NPP is accessible to heterotrophs across a variety of marine environments, but with considerable uncertainties58,60. Moreover, these methods cannot directly observe carbon flux on the time scales (seconds to minutes) and space scales (micrometres) of many microbial processes137,138,139.
Analytical methods for marine microbial metabolites
Chemical methodological advances
Although there are now more than 18,500 metabolites catalogued in the Kyoto Encyclopedia of Genes and Genomes (KEGG) compound database140, an untold number, including many with central roles in biogeochemical cycling, are still missing. A strategic approach is needed to focus on those currencies most relevant in driving the carbon cycle of the ocean. Molecular-level characterization of marine DOC has been a goal for decades in chemical oceanography and organic geochemistry, but has been thwarted by the salt and concentration challenges detailed above as well as by instrument limitations. Metabolite identification has emerged as a substantial bottleneck because the complex mixtures contain numerous isobaric and isomeric compounds that are poorly represented in current reference databases that are biased towards human metabolites and human-associated metabolites. Advances in both MS and NMR have now begun to crack this DOC black box (Fig. 4). The advent of electrospray ionization141 enabled the transfer of polar molecules directly into mass spectrometers. Mass resolution and accuracy have dramatically improved with Fourier-transform-based analysers such as Fourier transform ion cyclotron resonance cells142 and Orbitrap detectors143, which now routinely enable mass accuracy to levels below parts per million for thousands of molecules within complex mixtures. Chromatographic columns such as hydrophilic interaction chromatography and new mixed-mode resins can deliver specific fractions of the labile DOC pool for characterization144. Moreover, picomoles of individual compounds are sufficient to trigger fragmentation spectra for identification. Although typically less sensitive than MS for molecular detection, NMR provides structural information that better enables identification. Higher-field NMR magnets145 and advanced small-diameter probes provide better analyte detection with lower salt sensitivity146, and nanomoles of individual molecules are currently required for structural identification. Two-dimensional NMR approaches147 have been developed to obtain complete covalent geometry of molecules, sometimes with stereochemistry148. Further advances in MS and NMR technology offer promise for improved DOC characterization in the near future, including better data deconvolution strategies149 and improved methods for integrating data for unknown compound identification150. The compounds that have been successfully identified in marine metabolomes (Table 1) represent only a small fraction of total metabolite diversity.
Although MS and NMR offer the best potential for identifying biologically labile molecules in marine DOC, the salt problem has yet to be solved. Derivatization protocols show promise for this challenge, in particular those that target functional groups common in biologically produced compounds (for example, alcohol and amine groups4 and carbonyl moieties151). Recent application of derivatization methods are enabling detection in seawater at nanomolar (NMR and gas chromatography/MS)152 to picomolar (liquid chromatography/MS)4 concentrations. Identification of polar metabolites by direct injection of seawater into mass spectrometers has also been demonstrated recently for marine culture media, with limits of detection averaging 600 nM over a range from 10 nM to 3.2 µM (ref. 153).
Chemical methods are now better able to measure bacterial uptake of labile metabolites. Isotopically labelled compounds can be tracked into individual cells using nano-secondary ion MS154,155 and chemical-tagging tools156,157,158,159. As sampling volume requirements decrease and instrument sensitivities increase, single-cell measurements of internal and external metabolites will draw tighter associations between microbes and molecules160,161. High-resolution magic-angle spinning NMR probes provide access to real-time metabolism in vivo, even in the presence of high salt concentrations162. Flux measurements at the required temporal and spatial scales are on the horizon, with advances in tracking isotope incorporation through intracellular metabolic pathways163,164, cellular uptake of individual metabolites162 and fluid-flow devices coupled to high-resolution imaging137. These multiple approaches are chipping away at the barriers to progress.
Biological methodological advances
Labile metabolites are defined as those susceptible to microbial transformation, which makes evidence of biological processing an effective operational definition for labile DOC. Biology-based screening approaches fall into two categories: those that use biological signals alone to generate hypotheses regarding important compounds and those that couple biological signals with chemical analysis. In the former category, gene, transcript and protein inventories suggest which molecules are produced and consumed. These biosensor strategies do not require disruption of steady-state interactions and instead survey intact natural communities (using metagenomics, metatranscriptomics and metaproteomics) or model organism systems (using genomics, transcriptomics and proteomics). This approach has offered insight into metabolite flux in phytoplankton blooms165,166, oligotrophic seawater167,168, model communities66,74 and ocean-wide surveys169,170. It has been used to construct co-occurrence networks of microbes and metabolites171,172, and has provided insight into the choreographed daily cycles of metabolite-driven phytoplankton–bacteria interactions in the surface ocean18,27,167,173 (Fig. 3). The approach can be expanded to regional, global and full-ocean-depth scales to illuminate large-scale patterns in labile DOC transformations. Biological screening methods that rely solely on microbial response, however, are ultimately constrained by inadequate and slowly advancing gene annotation, an area for which investments in technology and new approaches are sorely needed.
The second category of biological screening is coupled to chemical analysis. This typically requires steady-state disruption, altering either the accumulation or utilization of DOC by modifications to the microbial community (for example, removing phytoplankton or bacteria68,75,100 or adding viruses45) or by manipulation of environmental parameters (for example, irradiance174), followed by chemical analysis of the altered pools. Drawdown studies introduce bacteria into a DOC pool and rely on chemical analysis to identify features that are depleted70, such as characterization of bacterial substrate use by different species70. Mutant screening studies introduce bacteria with disrupted genes into a DOC pool and rely on chemical analysis to identify features that are no longer depleted, for example, identification of the phytoplankton exometabolite dihydroxypropanesulfonate (DHPS) from its accumulation in a transporter mutant assay69. Enzymatic activity assays use selective digestion by high-specificity bacterial enzymes to quantify labile compounds within complex mixtures, for example, hydrolases that degrade laminarin into diagnostic sugar units that are readily measured175. Other biological screening strategies that are currently used primarily in the field of biochemistry have promise for adoption in ecological studies. Vesicular transport assays embed transporters in synthetic membrane vesicles in an inside-out orientation, trapping target metabolites in the vesicle for chemical analysis176. Metabolite–protein binding assays detect enzymes that bind to known metabolites, for instance, identification of substrates of Escherichia coli enzymes that previously lacked functional annotation177. Finally, activity-based protein profiling uses chemical probes with reporter tags that mimic metabolites and form covalent bonds with microbial enzymes, for instance, to identify novel catabolic enzymes that degrade cellulose178. The coupling of biological screening with chemical tools holds promise for pinpointing the hidden chemical currencies of the surface ocean and the genes and enzymes that transform them.
Modelling microbial metabolism
Modelling approaches are being used to extract carbon-cycle-relevant insights from observations of the microbe–metabolite network of the ocean. The challenge for models is to bridge a spatial scale spanning 13 orders of magnitude, from cell metabolism at the scale of 10–6 m to ocean flux at the scale of 107 m. Component models that focus on specific portions of this spatial scale already exist or are being developed. At the microbial end, earlier models of DOC release by phytoplankton sought a mechanistic understanding based on parameters such as phytoplankton size, nutrient status and photosynthetic output179,180,181. More recent models use genomic data to address the biochemical basis for metabolite production and consumption. Metabolic models based on flux balance analysis182 typically optimize for generation of new biomass, but could optimize for other physiological or ecological traits183 such as metabolite release, abiotic stress tolerance or carbon use efficiency184. Phylometabolic modelling integrates comparative genomics with insights from biochemistry and ecology to reconstruct metabolic innovations that affect metabolite production and consumption, such as complementary organic matter exchange between phytoplankton and bacteria17. Multicell metabolic models for single colonies or multispecies communities185 uncover rules governing metabolite exchange and provide parameters for models working at regional to global scales186,187.
In the transition from cellular scales to regional and global scales, hard-fought details of metabolite chemistry and biology must be simplified but not trivialized. The need to identify the optimal balance between excessive detail and oversimplification has emerged as a crucial barrier to incorporating microbial processes into global models188, along with high computational costs, limited conceptual foundation, and lack of data to formulate and evaluate the more complex models. Nonetheless, global and regional DOC dynamics can be captured through nutrient–phytoplankton–zooplankton–detritus (NPZD) modules, which are widely used to compare historical and future climates189,190. These models approximate the details of microbe–metabolite networks with bulk functions (such as Michaelis–Menten equations for substrate uptake) and use simplified rules to track substrates and energy through core metabolic pathways189. Conceptual convergence between models at different scales can potentially be leveraged, for example, by linking cell growth output from steady-state flux balance analysis models with resource allocation rules applied to NPZD models.
The recently developed ‘emergent’ models, in which microbial community structure and function emerge from a wider set of possibilities, combine microbial genomic or physiological data with a dynamic physical–chemical ocean model to observe biogeochemical outcomes. Outputs from emergent models have revealed, for example, a predictable assembly of communities based on functional repertoire rather than taxonomic affiliation191 and matched distributions and abundance of model microbes with their real-world counterparts across ocean light and temperature gradients192. An inherent struggle with these models is parameterizing the bioenergetic cost of a gene or gene function191,193,194. More work is needed to overcome these challenges, but it is clear that successful modelling of labile DOC flux at regional and global scales will close one of the largest knowledge gaps in the global carbon cycle.
Computational data science approaches
Software solutions that respond to the needs for interdisciplinarity and integration in microbiome science are emerging195,196,197,198, including those that build microbe–metabolite networks with machine-learning tools199. Other strategies address metabolite-related gene annotation by merging information on ‘genes without a metabolite’ with information on ‘metabolites without a gene’. For example, the metabolite annotation and gene integration (MAGI)200 method identifies patterns of metabolite–gene associations by scoring the consensus in occurrence between the two datasets. The crowd-sourced Global Natural Product Social Molecular Networking (GNPS)201 database improves metabolite identification and annotation by enabling comparisons of fragmentation spectra. Finally, the Paired Omics Data Platform links matched genomic and metabolomic data deposited in public repositories202. As annotations improve, in silico reconstructions can serve as knowledge repositories that facilitate data integration of reactions and pathways and enable predictions of microbial biosynthetic capabilities as environmental conditions, genetic perturbations and fitness functions111,203,204 vary. These informatic-centric approaches offer starting points for improved inventories of the microbial metabolites and identification of genes with important roles in surface ocean carbon flux.
Despite both progress and interest, the ability to co-investigate chemical compounds and their genetic determinants across space and time remains a bottleneck to characterizing microbe–metabolite networks. Data sharing is imperative among marine chemists and microbiologists to enable discoverability, integration and interoperability of data across software tools. Moreover, data exchange through software is necessary to leverage a growing public database that merges marine bacterial, archaeal and eukaryotic genomes205,206, metagenomes207,208,209, metatranscriptomes210 and metaproteomes211, and annotation resources for chemical oceanography201,212. Integrative strategies will lead to characterization of the genes that link microbial activity to the production and consumption of key metabolites.
Microbial currencies in a warming ocean
The well-recognized downward export of particulate organic carbon from the surface ocean to deep ocean waters and sediments (the ‘biological carbon pump’) is globally important because it isolates carbon from the atmospheric pool for hundreds to thousands of years213,214. The microbial remineralization of labile carbon to its inorganic form is globally important because it diverts carbon from the biological carbon pump, reducing net community production and influencing air–sea CO2 fluxes215,216. The quantitative importance of labile DOC remineralization becomes clear by considering that it constitutes >0.1% of the total DOC pool yet accounts for 86% of total DOC turnover2. This implies that rapidly cycled microbial metabolites are among the most important individual conduits of ocean carbon.
Recent studies have provided a framework for predicting how phytoplankton-derived components of labile DOC might be altered under future climate scenarios, despite often complex and species-specific responses. Increasing temperature has been shown to enhance total carbon release by phytoplankton15. Evidence suggests that increased ribosome efficiency under higher temperatures will decrease phosphorus demand217,218,219 and will lower the N:P stoichiometry of labile DOC as rRNA synthesis needs are lessened. Mismatches between phytoplankton photosynthetic flux (weakly affected by temperature) and metabolism (strongly affected by temperature) can have diverse impacts on cellular resource allocation and metabolism219. Increased CO2 concentrations can decrease photorespiration rates and alter the release of photorespiration products such as glycolate220,221. Finally, a warming climate is predicted to favour smaller phytoplankton cells, which are better able to compete for nutrients in a stratified ocean222,223, shifting labile DOC chemistry towards metabolite profiles characteristic of cyanobacteria and green algae18,224. As these predictions are being formulated, the microbial functions underlain by the production and cycling of the substrates, facilitators and ecological signals exchanged via the labile DOC pool are being recognized.
Details of the metabolic currencies that transfer carbon between microbes to sustain the surface ocean carbon cycle have until recently been largely invisible to scientists. Importantly, climate–carbon feedback loops mediated by the labile DOC reservoir depend on this microbe–metabolite network. The resilience of the ocean to planetary change will rely on responses of the network to temperature increases, ocean acidification and other linked environmental changes. With advances in the chemical, biomolecular and data sciences, more of these nearly invisible molecules and their roles in the ocean carbon economy are being recognized. The future promises rapid scientific advances in understanding the chemical currencies of the surface ocean carbon cycle, at a time when increased knowledge is needed to safeguard against the effects of global change.
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This Review arose from discussions supported by the CIFAR and developed further with support from the Moore Foundation (5503 to M.A.M., E.B.K. and A.S.E.; 9335 to S.A.A.), the Simons Foundation (542391 to M.A.M.; 253417 to E.B.K.; 504183 to E.M.B.; 509034SCFY20 to R.B.; 721225 to S.T.D.; 687269 to A.M.E.; 542389 to N.M.L.; 345889 to A.E.S.; and 735079 to A.V.), the US NSF (OCE-1756105 to N.R.B.; Major Research Equipment DBI-1946970 to A.S.E.; OCE-1924554 to M.A.S.; CAREER DEB-1749544 to A.S.; OCE-BSF 1635070 to DS.; and OCE-1829831 to M.B.S.), the Paul M. Angell Family Foundation (to S.T.D.), and the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-06159 to L.L.; RGPIN-2015-06078 to A.C.R.). This is NSF Center for Chemical Currencies of a Microbial Planet (C-CoMP) publication number 001.
The authors declare no competing interests.
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Moran, M.A., Kujawinski, E.B., Schroer, W.F. et al. Microbial metabolites in the marine carbon cycle. Nat Microbiol 7, 508–523 (2022). https://doi.org/10.1038/s41564-022-01090-3
Nature Microbiology (2022)