Marine metaproteomics: deciphering the microbial metabolic food web

Review

Omics: Fulfilling the Promise

Marine metaproteomics: deciphering the microbial metabolic food web Timothy J. Williams and Ricardo Cavicchioli School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia

Metaproteomics can be applied to marine systems to discover metabolic processes in the ocean. This review describes current breakthroughs regarding marine microbes in the areas of microbial procurement of nutrients, important and previously unrecognized metabolic processes, functional roles for proteins with previously unknown functions, and intricate networks of metabolic interactions between symbiotic microbes and their hosts. By recognizing that metaproteomics empowers our understanding of the roles that marine microbes play in global biogeochemical cycles, the achievements to date from this advancing field highlight the enormous potential that the future holds. Understanding metabolic processes in the ocean From shallow coastal waters to the abyssal depths, the Earth’s oceans are home to a huge diversity of microbes, representing all domains of life, and viruses. However, only a small subset of marine microbes has proven amenable to cultivation. Culture-independent techniques have allowed insights into both the phylogenetic diversity of marine microbes and the metabolic roles they perform within a marine community, including the contribution of microbes to biogeochemical cycling. One approach is to obtain and sequence DNA from the environment and determine the metabolic potential of the community via determination of the genes present (metagenomics). An overview of the metabolic activity and interactions within a microbial community can be inferred from analysis or combinations of RNA transcripts (metatranscriptome), proteins (metaproteome), or metabolites (metabolomics) (see Glossary). Both metatranscriptomics and metaproteomics provide information about the products of gene expression. Metaproteomics (community or environmental proteomics) informs about the final end product of transcription and translation (i.e., the in situ presence of a protein). In doing so, it provides insight into the outcome of regulation of gene expression, protein synthesis, and stability and turnover of mRNA and protein in response to environmental stimuli at the time of sampling [1,2]. Since the term ‘metaCorresponding author: Cavicchioli, R. ([email protected]). Keywords: marine microbiology; proteomics; marine ecology; metagenomics; marine nutrient cycle; ecophysiology. 0966-842X/ Crown Copyright ß 2014 Published by Elsevier Ltd. All rights reserved. http:// dx.doi.org/10.1016/j.tim.2014.03.004

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proteomics’ was first introduced 10 years ago [3] and the first report describing its application to a marine environment appeared in 2005 [4,5], metaproteomics has been successfully applied to an increasingly diverse range of marine and marine-derived systems (Table 1 and Figure 1). Glossary Autotrophy: utilization (reduction) of inorganic carbon (CO2) to generate organic carbon compounds for growth. Bacterioplankton: bacterial/archaeal component of plankton. Exoenzyme: enzyme that is secreted by a cell and functions outside that cell. Heterotrophy: utilization of organic carbon compounds for growth. Mass spectrometry (MS): analytical technique that ionizes chemical compounds to generate charged molecules and measures their mass-to-charge ratios. Metagenome: analogous to metaproteome, but pertaining to DNA rather than protein; refers to the total DNA sequences obtained from DNA extracted from an environmental sample. Using a ‘shotgun’ approach and randomly sequencing DNA, a metagenome provides an inventory of genes representing the organisms present within the community. Metaproteogenomics: combines metagenomics, to determine which organisms and genes are present and what functional potential is described by the genes, with metaproteomics, to determine which proteins have actually been synthesized by the cell. Compared with either metagenomics or metaproteomics alone, metaproteogenomics enables more robust conclusions to be drawn about the microorganisms present in a sample and the functions and microbial processes they perform. Metaproteome: in contrast to ‘proteome’, which refers to the complement of proteins synthesized by a single organism (usually a pure laboratory culture), metaproteome refers to the proteins represented by a community of microorganisms present in an environmental sample. Similar to proteomics, protein identifications for metaproteomics are achieved through the use of MS applied to peptides derived from total protein extracted from microbial biomass. In metaproteomics, not all proteins synthesized by an organism are detected. The coverage per organism depends on the representation of that organism in the community, the abundance of the protein in the cell, and a range of other methodological factors (e.g., ability of the protein to be extracted and ‘flown’ in the mass spectrometer). The metaproteome informs about the proteins synthesized by a microbial community at the time of sampling. Metatranscriptome: deriving from ‘transcript’, meaning RNA, a metatranscriptome represents the RNA species expressed by a microbial community present within an environmental sample. Being derived from DNA sequencing, RNA must be extracted and converted to cDNA using a reverse transcriptase process, before being sequenced using standard DNA sequencing technologies. Phototrophy: utilization of light energy for metabolic processes; phototrophic organisms can be either autotrophs or heterotrophs. Phytoplankton: photosynthetic organisms within plankton, especially unicellular algae (eukaryotes) and Cyanobacteria. Symbiotic interaction: a syntrophic interaction that is mutual or reciprocal between at least two organisms; usually, an intimate association between two or more organisms (hence, symbiont). In endosymbiosis, one or more organisms resides inside another (the host), including inside a cell (hence, endosymbiont). An example of a symbiotic association is sulfate-reducing bacteria benefiting from oxidized sulfur compounds produced by green sulfur bacteria and, conversely, green sulfur bacteria benefiting from reduced sulfur compounds produced by sulfate-reducing bacteria. Syntrophic interactions: interactions between organisms that enable benefit to be obtained from a process they perform; usually, the products of one organism are utilized by another as a nutrient source. For example, sulfatereducing bacteria benefiting from oxidized sulfur compounds produced by green sulfur bacteria.

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Table 1. Survey of metaproteomic studies conducted on marine and marine-derived environmentsa Location (position in Figure 1) Chesapeake Bay (A), North Atlantic Ocean

Method of sampling

Subject of analysis

Major findings (microbial processes)

Refs

Surface waters

Pioneering study, describes the application of metaproteomics in a marine environment

[4]

Surface waters

Pioneering study, SAR11 expresses proteorhodopsin in natural environment

[5]

Sargasso Sea, off Bermuda coast (C), North Atlantic Ocean

Seawater prefiltered through 3mm filters; microbial cells concentrated using tangentialflow filtration followed by centrifugation Seawater prefiltered through 0.8-mm filter; microbial cells concentrated using tangentialflow filtration, followed by centrifugation Cells in seawater concentrated by tangential-flow filtration, followed by centrifugation

Oligotrophic subtropical gyre, surface waters

[1]

South Atlantic gyre (open ocean) (D) and Benguela upwelling region, coastal Angola, Africa (E), South Atlantic Ocean

>0.8-mm fraction of seawater concentrated by tangential-flow filtration; cells later centrifuged and fractionated to enrich for membrane material

Open ocean, coastal/ upwelling along natural nutrient gradient, surface waters

Offshore Oregon (Newport) (B), North Pacific Ocean

Seawater prefiltered to enrich for <1.2 mm cells, then concentrated by tangential-flow filtration followed by centrifugation

Coastal upwelling system, surface waters

East Pacific Rise (EPR) (F), eastern Pacific Ocean; Guaymas basin (G), Gulf of California

Tube worms dissected and symbiont-containing tissue (‘trophosome’) removed and homogenized; homogenate fractionated by gradient centrifugation

Microbial community within the gutless marine worms Riftia pachyptila and/or Tevnia jerichonana in deep water (>2 km) at multiple hydrothermal sites, including Guaymas basin (sediment-hosted vents) and EPR (basalthosted vents)

Ace Lake (H), a marinederived, meromictic lake in Antarctica

Sequential size fractionation of biomass in lake water through a 20-mm prefilter onto filters (3, 0.8, and 0.1 mm)

Sampled at several depths

Bering Sea (I), North Pacific Ocean

Suspended and sinking particles in seawater captured on filters and traps, respectively; undisturbed sediments collected using multicores

Suspended and sinking particles at multiple depths and sediments on the continental shelf and basin

SAR11 ABC transporter proteins are dominant, especially for phosphate/ phosphonate; TRAP transporter proteins from SAR11 also detected; many proteins detected from Cyanobacteria (Prochlorococcus and Synechococcus) involved in photosynthesis and carbon fixation, as well as ABC transport TBDT proteins dominate at both coastal and open ocean sites, especially from Shewanella (coastal); rhodopsins found from different bacterial clades (Chloroflexi, Proteobacteria, Cyanobacteria, and Actinobacteria) at both open ocean and coastal sites; nitrification (ammonia oxidation) by ammonia-oxidizing Archaea; viral proteins abundant ABC and TRAP transporter proteins abundant, especially from SAR11, with specificities for nitrogen, carbon, and sulfur containing (amino acids, polyamines, and taurine); methylotrophy (methanol) by Betaproteobacteria (OM43 clade); viral proteins abundant Riftia gammaproteobacterial chemoautotrophic endosymbiont (Candidatus Endoriftia persephone) use sulfur oxidation to fuel CO2 fixation (both Calvin cycle and reductive tricarboxylic acid cycle, with the latter also assimilating organic acids acquired by TRAP transporters); local geochemistry (sediment versus basalt hosted) influences symbiont physiology: higher levels of proteins involved in thiosulfate oxidation and nitrate reduction at Guaymas versus EPR; higher levels of sulfide oxidation proteins and protontranslocating pyrophosphatase at EPR versus Guaymas; conspecific endosymbiont metaproteome from Tevnia (EPR) very similar to that of Riftia endosymbiont (EPR) Stratification of microbial processes within the water column [e.g., ABC transporters (amino acids, simple sugars) by SAR11 and Actinobacteria in upper (oxic) layer; ammonia assimilation and dissimilatory sulfide reduction by Chlorobium sp. in oxycline; >30% proteome coverage of a dominant Chlorobium sp.; possible anammox in bottom (anoxic) layer] Selective survival of alga-derived proteins, with compartmentalized (e.g., organelle) and cell membrane proteins showing high longevity and soluble secretory proteins

Offshore Oregon (Newport) (B), North Pacific Ocean

[27]

[26]

[60–63]

[17,18]

[67]

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Table 1 (Continued ) Location Figure 1)

(position

in

Method of sampling

Subject of analysis

North Sea, off Helgoland (J), Germany

Seawater prefiltered through 10mm filters then onto 3-mm filters (to collect algae/particleassociated bacteria), with some filtered onto 0.2-mm filters (for planktonic bacteria)

Surface waters, during phytoplankton bloom

Southern Ocean off Anvers Island (K), Antarctic Peninsula, West Antarctica

Seawater prefiltered through sequential 5.0- and 2.5-mm filters and concentrated by tangential-flow filtration; cells captured on 0.2-mm filters

Summer versus winter, surface waters

Newcomb Bay (L), Southern Ocean, East Antarctica

Sequential size fractionation of biomass in seawater through a 20-mm prefilter onto filters (3, 0.8, and 0.1 mm)

Surface waters

Botany Bay (M), Sydney, Australia, South Pacific Ocean

Sponges removed and microbial fraction collected using a series of centrifugation and filtration steps

Microbial community of the sponge Cymbastela concentrica in coastal waters

Nyegga pockmark (N), Storegga Slide, Norwegian Sea, offshore Norway

Sediments obtained by push core and retrieved with aid of a remotely operated vehicle

Cold methane seep

Mediterranean Sea, off the island of Elba (O), Italy

Worms removed from sediment via decantation, symbionts enriched via isopycnic centrifugation; density-gradient fractions used to enrich for specific symbionts

Microbial community within the gutless marine worm Olavius algarvensis in shallow marine sediments

South China Sea (P)

Seawater filtered through a 0.7mm (nominal) filter onto a 0.2mm filter concentrated using cross-flow ultrafiltration

Surface and mesopelagic seawater samples

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Major findings (microbial processes) more susceptible to microbial recycling during sinking in the water column Substrate-controlled succession of marine bacterioplankton: initial surge in Flavobacteria; a second phase where Reinekea (Gammaproteobacteria) and roseobacters (Alphaproteobacteria) peaked; and a third phase dominated by particular Flavobacteria and SAR92 clade (Gammaproteobacteria). SAR11 levels remained fairly constant. ABC and TRAP transporters employed for nutrient uptake by Alphaproteobacteria; Flavobacteria and SAR92 favor TBDTs and exoenzymes for processing complex alga-derived matter SAR11 and Rhodobacterales bacteria use ABC and TRAP transporters for nutrient uptake, abundant in summer and winter; taurine and glycine betaine are favored substrates for SAR11; proteins associated with nitrification detected in winter (not summer); chemolithoautotrophy via the 3hydroxypropionate/4-hydroxybutyrate cycle by ammonia-oxidizing Archaea; methylotrophy (methanol) by Betaproteobacteria (OM43 clade) Flavobacteria use abundant TBDT proteins and polymer-degrading exoenzymes to metabolize complex organic matter; SAR11 and Rhodobacterales use ABC and TRAP transporters for uptake of simpler nutrients; proteorhodopsin expressed by Flavobacteria and oligotrophic marine Gammaproteobacteria (OMG) Aerobic nitrification (ammonia oxidation) and anaerobic denitrification by Archaea and bacteria, respectively; transport of organic solutes by ABC and TRAP transporters, including sponge metabolites (dipeptides and halogenated aromatics); possible interactions with sponge host mediated by symbiont cell envelope proteins ANME; reverse methanogenesis pathway (oxidative), including putative novel step, and electron-accepting complexes; expression of gas vesicles. Sulfatereducing bacteria: complete dissimilatory sulfate-reduction pathway Symbionts (individual processes differ between the various symbionts) had novel putative pathway for assimilation of host waste products (acetate, propionate, succinate, and malate); CO and hydrogen used as energy sources; high-affinity uptake of organic substrates by ABC transporters; syntrophic sulfur cycling among symbionts; transposases actively expressed by symbionts Cyanobacteria proteins dominant component of particulate organic matter, but functional groups of proteins differ in distribution in surface versus mesopelagic waters; SAR11, Rhodospirillaceae, Prochlorococcus, and viruses were major contributors to dissolved proteins in the high molecular weight dissolved organic matter from surface seawater

Refs

[6]

[24,45]

[7]

[20]

[52]

[23,68]

[69,70]

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Table 1 (Continued ) Location (position in Figure 1) Jan Mayen vent fields (Q), Arctic mid-ocean ridge, Norwegian–Greenland Sea

Hydrate Ridge (R), offshore Oregon and Santa Monica Basin (S), offshore Los Angeles, California, North Pacific Ocean Bedford Basin (T), Nova Scotia, Canada, northwest Atlantic Ocean

Method of sampling

Subject of analysis

Major findings (microbial processes)

Refs

Sediments covered with white microbial mats sampled using a remotely operated vehicle

Hydrothermal vent sediments

[22]

Sediments sampled using a remotely operated vehicle

Cold methane seeps

Community dominated by sulfideoxidizing chemolithoautotrophic Epsilonproteobacteria; sulfate-reducing Deltaproteobacteria use Wood–Ljungdahl pathway for CO2 fixation; aerobic methane oxidizing Gammaproteobacteria express high levels of methane monooxygenase ANME and sulfate-reducing bacteria use strategies to overcome decreased bioavailability of trace metals in sulfidic conditions

Seawater prefiltered through a 2.7-mm filter, cells captured on 0.22-mm filters

Surface (5 m) and deeper (60 m) waters

Succession of marine bacterioplankton from winter to spring; seasonal increase in ABC and TRAP transporter proteins for scavenging organic substrates: Rhodobacterales transporters associated with spring phytoplankton bloom versus SAR11 transporters abundant in underlying waters; ARCTIC96BD-19 clade of Gammaproteobacteria heterotrophic, related SUP05 clade autotrophic by sulfur oxidation; methylotrophy (methanol) by Betaproteobacteria (OM43 clade); SAR324 clade of Deltaproteobacteria heterotrophic; nitrification (ammonia oxidation) and phosphate/phosphonate uptake by ammonia-oxidizing Archaea

[28]

[21]

a

Abbreviations: ABC, ATP-binding cassette; TBDT, TonB-dependent transporter; TRAP, tripartite ATP-independent periplasmic.

Metaproteomic methods begin with samples obtained directly from the environment; for planktonic microbes, biomass can be obtained via filtration of ocean water (e.g., [6,7]). Successful applications of metaproteomic approaches Q

depend on efficient recovery of proteins from the sample [8,9]. Proteins are subsequently extracted from the biomass and prepared for high-throughput mass spectrometry (MS). MS generates fragmentation spectra from peptides that are

N

J

I R

B

T

A

O

S

C G

Pacific Ocean

P

Atlanc Ocean

F

Pacific Ocean

D

E

Indian Ocean

M

Southern Ocean L

K H

TRENDS in Microbiology

Figure 1. Global geographic locations of metaproteome sampling sites. Letters refer to published studies described in Table 1. Figure constructed from a world map obtained from http://www.freeworldmaps.net.

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Review then searched against genomic and/or metagenomic databases to deduce the amino acid sequences of peptides, thereby providing identifications for proteins. The methods available for obtaining and processing samples using tandem MS, and the efficacy of different metaproteomic methods, are comprehensively discussed elsewhere [2,10–15]. The ability to make confident protein identifications depends greatly on the DNA sequence databases that are used, because database design and content can significantly affect the resulting peptide matches (e.g., [11]). To improve peptide identification from metagenome data, assembly methods have been developed for reconstructing peptide sequences rather than full genomes [16]. Metagenome data derived from sampling sites also ensures that protein identifications are not biased toward organisms for which genome sequences are publically available. This is particularly the case for highdiversity or novel ecosystems. The integration of metagenome with metaproteome analyses (‘metaproteogenomics’) provides an enhanced means of reconstructing microbial processes for a community (e.g., [6,17–21]). This integrated approach can be used to investigate shifts in both gene content and expression over time within a given community [7]. The value of having metagenome data, and the impact of both community complexity and novelty on being able to make protein identifications, is well illustrated by the study of a marine-derived Antarctic lake [17,18]. Metagenome data from samples taken from six depths of Ace Lake produced nearly 9 million gene predictions [18] and metaproteomics generated nearly half a million mass spectra [17,18]. Although more than 1800 proteins were identified [18], over 500 were assigned to a single species of green sulfur bacterium (Chlorobium sp. [17,18]). The green sulfur bacterium was so dominant in a zone of the lake that most of its predicted genome sequence (1631 genes) was assembled from metagenome data, enabling 12,718 peptides to be assigned to it, representing approximately 31% proteome coverage. By contrast, as few as 725 peptides were assigned to microbes in a deep zone of the lake. As taxonomic diversity increased with depth of the lake, the rate of metaproteomic identifications decreased, with the deepest depth having 67% of identifications to hypothetical proteins that lacked orthologs. A ‘meta-omics’ approach that includes metaproteomics and metatranscriptomics allows a direct comparison of peptide and transcript levels in situ [22]. Coupling metaproteomic data with geochemical and physicochemical conditions or nutrient gradients in a habitat is also a to infer biogeochemical cycling powerful way [7,18,23,24]. The use of metaproteomics with metabolomic analyses and enzyme assays is particularly instructive in elucidating metabolic processes in situ [23]. A novel proteomics approach has also been used to simulate natural conditions and assess the effects of environmentally relevant variables on a marine bacterium, including anthropogenic effects, by incubating laboratory cultures with different sources of natural seawater [25]. As with all research based on gene/protein discovery, the information gleaned from metaproteomic studies is predicated on having reliable (preferably experimentally 252

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based) knowledge of the function of orthologous proteins or protein complexes (including metabolic enzymes, transporters, energy transduction systems, and regulatory proteins). Moreover, the confidence of protein assignments to taxa is limited by the species present in databases; functional assignments are often, therefore, more robust than taxonomic assignments of proteins. In this review we focus on the application of metaproteomics for discerning metabolic processes performed by marine microbes, describing studies where metaproteomics has proven to be especially successful for learning about ecological processes. In so doing, the review highlights the value of metaproteomics for: (i) providing insight into how microbes procure substrates for growth in their natural environment, including targeting individual compounds; (ii) revealing the importance of certain metabolic processes in the ocean, particularly with respect to biogeochemical cycling; (iii) hypothesizing about novel mechanisms or pathways, or novel steps within known pathways, employed by microbes in their native habitat; and (iv) examining metabolic interactions between microbes in a given environment, including syntrophic and symbiotic relationships. Nutrient uptake Transporters for nutrient uptake represent the primary mechanism by which marine microorganisms obtain substrates from the environment. The metaproteomic study of Sowell et al. [26] was the first of its kind to demonstrate the importance to marine bacteria of nutrient acquisition via high-affinity transporters and to identify transporters that are expressed at high levels. This study used metaproteomics to investigate the bacterioplankton of the Sargasso Sea, an oligotrophic subtropical gyre in the North Atlantic Ocean, during a period when the water column was highly stratified and nutrients at the surface were hence highly depleted. The metaproteome was found to be dominated by proteins belonging to ATP-binding cassette (ABC) transporters from the SAR11 clade of bacteria. These are highaffinity primary transporters that utilize ATP hydrolysis to drive nutrient uptake and individual types of ABC transporters target various organic (including amino acids, dimethylsulfoniopropionate, taurine, polyamines, simple sugars, and phosphonates) and inorganic (iron and complexed phosphate) compounds. These are bioenergetically expensive systems, so microbes invest in the biosynthesis of ABC transporters that target substrates that are limiting, rather than synthesizing the full complement of ABC transporters encoded by their genomes. The availability of individual compounds can vary over time and many essential solutes can be imported by less bioenergetically expensive mechanisms or even by passive diffusion if present at high enough concentrations. This regulatory strategy therefore enables the microbes to better compete for the limited resources when they become available. In general, the most abundant component of ABC transporters in metaproteomic data sets are the periplasmic solute-binding protein (PBP) subunits, which are far more abundant than ATPase and/or permease components of these multiprotein complexes [1,7,24,26–28]. Integral membrane (e.g., permease) and associated (e.g., ATPase) proteins are more difficult to extract and solubilize from

Review biomass, thereby potentially reducing their frequency of detection relative to inherently soluble and ‘free’ proteins such as PBPs [7,27–29]. Nevertheless, PBPs are typically found at ratios that far exceed the cognate ABC importer to which they bind, so the relatively high abundance of PBPs can be largely attributed to high expression levels of PBPs to enhance the frequency of solute recruitment [30,31]. In the Sargasso Sea, abundances were highest for PBP subunits of ABC transporters for amino acids, sugars, polyamines, phosphate, and phosphonates, which suggests that this environment was phosphorus limited. Also detected for SAR11 were PBPs of tripartite ATP-independent periplasmic (TRAP) dicarboxylate transporters, which utilize an electrochemical ion gradient to drive solute uptake [32]. Because SAR11 bacteria are ‘passive’ (nonmotile) heterotrophs that are capable of growth under extreme nutrient limitation, they rely on a strategy of scavenging nutrients at low (nanomolar) concentrations rather than depending on the pursuit of nutrient upshifts, such as those that arise from phytoplankton blooms, that may be of limited duration [33]. Determining which ABC and TRAP transporters are synthesized by marine bacteria can also provide clues about which substrates are limiting in nutrient-replete habitats. An investigation of a bacterioplankton community from a highly productive, nutrient-rich coastal upwelling system of the Oregon shelf (Pacific coast, USA) also generated a metaproteome that was dominated by PBPs of ABC and TRAP transporters [26]. These transporter proteins matched to SAR11 as well as to another clade of Alphaproteobacteria, the metabolically versatile Roseobacter clade [34]. The high abundance of ABC transporters for amino acids, taurine, and polyamines, in association with glutamine synthetase, indicated that carbon and nitrogen were more limiting than phosphate in this environment. The metaproteome data also enabled inferences that highenergy carbon compounds such as sugars and carbon/nitrogen-containing compounds such as amino acids were fiercely sought after by coastal heterotrophic bacteria. Another category of transport system is the TonB-dependent transporters (TBDTs). Whereas ABC transporters tend to target simple and labile substrates, TBDTs are deployed for more complex substrates. TBDTs are outer membrane transporters that use a proton motive force for the uptake of macromolecules that are too large to diffuse via porins [35]. Through the use of outer membrane substrate-binding proteins and hydrolytic enzymes, TBDTs can bind and degrade biopolymers (e.g., polysaccharides, proteins, proteoglycan) and transport the resulting components into the cell. The metaproteomic study of Morris et al. [27] incorporated an extraction method that enriched for membrane proteins and as a result was particularly instructive for defining the importance of TBDTs in nutrient acquisition. The study evaluated surface seawater samples collected along a natural gradient in nutrient concentrations in the Southern Ocean that spanned the low-nutrient open ocean (South Atlantic gyre) to highnutrient coastal waters (Benguela upwelling region, Angola, Africa). This study not only revealed the importance of TBDTs in the open ocean; the fact that TBDTs and rhodopsins matched the same lineages suggested that

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phototrophic bacteria have the potential to use light energy to help fuel their transport activities. The importance of both ABC transporters and TBDTs in nutrient acquisition by bacterioplankton was underscored by the metaproteomic study of Teeling et al. [6], which focused on the bacterioplankton response to a coastal phytoplankton bloom during spring at Helgoland, an island in the North Sea. The study tracked the progression of heterotrophic bacterial taxa over time, finding the prebloom phase dominated by SAR11 and the Roseobacter clade, with the former remaining fairly constant throughout the subsequent bloom. The bacterioplankton response to the bloom was subdivided into three distinct phases of succession: an initial surge in Bacteroidetes (mostly Flavobacteria, including Ulvibacter and Formosa); a second phase where Reinekea (Gammaproteobacteria) and Roseobacter clade members (Alphaproteobacteria) peaked; and a third phase where the bacterioplankton was dominated by particular Flavobacteria (Polaribacter and Formosa) and the SAR92 clade (Gammaproteobacteria). Metaproteomics was used to quantify the levels of important proteins synthesized by bacteria to acquire nutrients. Flavobacteria were found to utilize TBDTs and exoenzymes (glycoside hydrolases, laminarinases, and sulfatases) for the uptake and breakdown of complex carbohydrates, especially algal polysaccharides. A similar reliance on TBDTs and glycoside hydrolases was employed by SAR92, whereas Alphaproteobacteria favored ABC and TRAP transporters. Thus, in parallel to the dynamic succession of individual bacterial clades, this study documented the relative contribution of different transport mechanisms to nutrient acquisition by heterotrophic bacteria [6]. A metaproteomic investigation of seasonal changes in bacterioplankton was conducted at coastal sites off the Antarctic Peninsula in West Antarctica. The study also found marked (and statistically significant) differences between the relative abundances of ABC transporter and TBDT proteins, consistent with the changes in community composition between winter and summer [24] (Figure 2). ABC transporter proteins were the most prevalent category of proteins across both seasons, constituting 13.7% of the metaproteome, with most matches to SAR11 and Roseobacter clade members. The study used MS spectral counts to determine that ABC transporter proteins were significantly more abundant in winter than in summer. By contrast, TBDT proteins constituted 11% and 2.5% of detected proteins in summer and winter, respectively, with spectral counts significantly higher in summer. This distribution was attributed to TBDTs matching mostly to Bacteroidetes (especially Flavobacteria), which target algagenerated biomass. These metaproteomic data for flavobacterial proteins were consistent with the knowledge that algal primary productivity is much lower during the dark polar winter. Seasonal and vertical partitioning was demonstrated for bacterial and archaeal proteins by the metaproteomic study of the water column of Bedford Basin, a stratified marine system that forms the north-western end of Halifax Harbour on Canada’s Atlantic coast [28]. This study compared surface and bottom waters for winter and spring associated with the Northwest Atlantic spring phytoplank253

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CO2

Zooplankton

CO2

NH4+

NH4+

Nitrificaon

Group I crenarchaeota

Phytoplankton Complex organic maer

CO2

Nitrifying betaproteobacteria

NO2–

Oxygenic photosynthesis

TBDT

Simple substrates :

Polyamines Amino acids Methanol Taurine DMSP Glycerol-3-PO4 Carboxylates Phosphonates Iron Sugars MEDH

Polysaccharides Proteins Oganophosphates

TBDT

Nitrospirae

CO2

ABC Transport TRAP Transport OMG

OM43

Methanol

? CO2

Flavobacteria

GSO

Rhodobacterales

Oceanospirillales

Carbohydrates DMSP

SAR11 Simple sugars Phosphonates Dicarboxylates

S2–or S0 ?

Amino acids Taurine Polyamines Simple sugars DMSP Iron

Amino acids Taurine Polyamines Simple sugars Glycerol-3-PO4 Oligopepdes Phosphonates Carboxylates

TRENDS in Microbiology

Figure 2. Simplified depiction of the metabolic characteristics of Antarctic Peninsula winter and summer microbial communities: eukaryotic groups (rectangles); bacterial clades (ellipses); archaeal clade (diamond); autotrophic groups (italics – uncertain for GSO); heterotrophs (normal text); predominantly found in winter (blue shading); summer (red); and abundant in both seasons (green). For heterotrophic groups, preferred substrates are shown under each group. Abbreviations: ABC, ATP-binding cassette; DMSP, dimethylsulfoniopropionate; GSO, gammaproteobacterial sulfur oxidizers; MEDH, methanol dehydrogenase; OMG, oligotrophic marine Gammaproteobacteria; TBDR, TonB-dependent receptor; TRAP, tripartite ATP-independent periplasmic transporter. Substrates used for growth inferred from [24].

ton bloom and found that ABC and TRAP transporters increased in abundance from winter to spring (especially for SAR11 and Rhodobacterales), at both the surface and bottom waters, consistent with a role in acquiring phytoplankton-derived organic compounds. The detection of high-affinity transporter proteins also provided informative about metabolic interactions of bacterial clades for which little is known about their ecology. One example is SAR324, a deep-branching clade of ubiquitous marine Deltaproteobacteria [36]. SAR324 has been regarded as metabolically versatile, with genomic, metagenomic, and metranscriptomic support for carbon fixation (via the Calvin cycle), heterotrophy, sulfur oxidation, and one-carbon metabolism [37–39]. The Bedford Basin metaproteome provided evidence of organic solutes being targeted by ABC transporters (sugars, amino acids, peptides, and polyamines), consistent with a heterotrophic metabolism [28]. The metaproteome also supported niche partitioning in Bedford Basin by two closely related clades of Gammaproteobacteria, ARCTIC96BD-19 and SUP05 [38,40], with the former being heterotrophic (uptake of dipeptides, sugars, taurine, and especially amino acids), and the SUP05 clade autotrophic by sulfur oxidation in hypoxic bottom water 254

[28]. Thus, despite the close phylogenetic relationship between ARCTIC96BD-19 and SUP05, members of the two clades were shown to utilize highly disparate metabolic strategies within this environment, with the former heavily reliant on scavenging of organic nutrients [28]. With transporters for nutrient uptake being important for microbial competitiveness, specific to nutrient availability, and abundant (particularly PBPs) in cells, metaproteomics has proven to be a very useful means of evaluating the ecophysiology of coastal and open ocean marine bacteria from tropical through to Antarctic environs. Recognizing important pathways in the environment Metaproteomics has been useful in highlighting the importance of metabolic processes in the ocean that had previously only been inferred from metagenomic or genomic evidence. The process of nitrification, whereby ammonia is oxidized to nitrite and nitrate, was long known to be mediated by bacteria, with the oxidation of ammonia to nitrite (nitrosification) mediated by ammonia-oxidizing bacteria (AOB) belonging to the Gammaproteobacteria and Betaproteobacteria. However, the recognition that

Review members of the Marine Group I Crenarchaeota (also called Thaumarchaeota) potentially played a role in marine nitrification emerged much later. The prevalence of archaeal ammonia monooxygenase (Amo) subunit gene amoA in marine metagenomes indicated the potential for ammonia-oxidizing Archaea (AOA) to perform oxidation of ammonia to nitrite in the ocean, including at the surface (e.g., [41–43]). The isolation of Candidatus Nitrosopumilus maritimus confirmed experimentally that Marine Group I Crenarchaeota are capable of oxidizing ammonia and fixing inorganic carbon [44]. The identification of Amo proteins in the South Atlantic [27] and the Southern Ocean [24] demonstrated the power of metaproteomics to verify archaeal nitrosification at the ocean surface. In both studies, the proteins showed the highest matches to Ca. N. maritimus. However, for the Southern Ocean metaproteome, AOA proteins were not detected in the summer, only in the winter, where they constituted almost a third of detected proteins. In the Southern Ocean, proteins that best matched AOA included those that belonged to the 3-hydroxypropionate/4-hydroxybutyrate cycle [24,45], a uniquely archaeal CO2 assimilation (autotrophic) pathway fuelled by ammonia oxidation. Other proteins from the Southern Ocean winter metaproteome were linked to CO2 assimilation by nitrite-oxidizing bacteria (Nitrospirae), as well as ammonia oxidation by AOB, via Amo from Nitrosospira (Betaproteobacteria) [24]. Collectively, the metaproteome data provided evidence for complete nitrification pathways. Metaproteomics has revealed the hitherto underappreciated importance of marine bacteria in the assimilation of C1 compounds such as methanol. Methanol may arise as a byproduct of marine phytoplankton growth or photochemical degradation of surface dissolved organ carbon [46,47]. One of the microbial processes inferred from the coastal metaproteomes of Oregon, Nova Scotia, and Antarctica was methylotrophy by aerobic bacteria [1,24,26,28]. Metaproteomics revealed methanol dehydrogenase from the OM43 clade of Betaproteobacteria [24,26,28], corroborating genome-based predictions that methanol and other C1 compounds are important substrates for bacterioplankton in coastal ecosystems [48]. One metaproteomic study even identified a key enzyme implicated in methanol assimilation by OM43 via the ribulose monophosphate pathway [28]. Reconstructing novel metabolic pathways Metaproteomics has been used to hypothesize novel pathways or to help ‘fill in’ gaps in known pathways or pathways proposed based on genomic evidence where key enzymes remain to be elucidated. This approach is analogous to the use of proteomics with laboratory isolates to identify candidate enzymes specific to a given pathway, such as the methylaspartate cycle in halophilic Archaea [49]. Once a solute has been imported by an ABC or a TRAP transporter, it becomes a substrate that is processed by metabolic enzymes. The metaproteome can provide evidence of the fate of substrates in the cytoplasm after they have been captured and imported by specific transporters, thereby providing a link between the two processes. Even if a complete pathway cannot be reconstructed from the

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metaproteome, key enzymes can indicate the fate of individual substrates. For example, in the Antarctic Peninsula metaproteomic data set, the identification of ABC transporter proteins and catabolic enzymes provided evidence that SAR11 imported and utilized glycine betaine and taurine as substrates [24,45]. Glycine betaine is a compatible solute that can protect cytoplasmic proteins against cold damage. However, the metaproteome data provided evidence that SAR11 uses this amino acid as a source of carbon and nitrogen via enzymes involved in the degradation pathway of glycine betaine to glycine [50]. Taurine (2aminoethanesulfonic acid), an organosulfate released by marine invertebrates, is known to support SAR11 growth [51]. Metaproteomics led to the identification of proteins required for taurine catabolism via a pathway that yields sulfite as a toxic byproduct; thus, proteins implicated in carbon and nitrogen assimilation, as well as sulfite detoxification, were detected [24]. As part of their metaproteomic investigation of the metabolic interactions between the marine worm Olavius algarvensis and its various bacterial endosymbionts, Kleiner et al. [23] proposed a novel bacterial pathway for the assimilation of certain organic acids. The dominant gammaproteobacterial symbiont was found to synthesize proteins consistent with the operation of a modified 3hydroxypropionate bi-cycle (3-HPB) for the assimilation of acetate, propionate, succinate, and malate (all fermentative waste products of O. algarvensis), but not CO2. This discovery was facilitated by density gradient-based separation of the O. algarvensis symbionts from each other and from host tissue before protein extraction (proteomicsbased binning [23]). Activities of the enzymes of this modified 3-HPB were verified experimentally (no activities were found for the two ‘missing’ enzymes present in the conventional 3-HPB for CO2 fixation), thus providing ‘wet-lab’ corroboration for an in silico pathway derived from the metaproteome [23]. Metaproteomics was employed to investigate a microbial community in marine cold seep sediments at Nyegga in the Norwegian Sea, dominated by free-living anaerobic methanotrophic Archaea (ANME), particularly members of clade ANME-1 [52]. Protein identifications supported the utilization of anaerobic oxidation of methane (AOM) by ANME-1 via reverse methanogenesis, whereby methane is oxidized to CO2 [53]. In this case, a reverse methanogenesis pathway had been proposed based on genomic/metagenomic evidence, albeit missing one enzyme [methylenetetrahydromethanopterin (H4MPT) reductase (Mer)] [53,54]. ANME-1 proteins identified as reverse methanogenesis enzymes were detected in the cold seep metaproteome, except for Mer [52]. Although absence of evidence is not evidence of absence, the Nyegga cold seep metaproteome provided support for the hypothesis that this step in ANME-1 is catalyzed by a homolog of methylene-tetrahydrofolate reductase (MetF) [52] that is presumably adapted to function with H4MPT (bifunctional or strictly H4MPT dependent) (Figure 3). The gene for MetF was found to be expressed in the sediment at levels (based on peptide count) comparable to reverse methanogenesis enzymes. As indirect support, proteins involved in proposed alternative pathways [53,54] were not detected [52]. As the 255

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Figure 3. Hypothetical pathway of anaerobic oxidation of methane mediated through the reverse methanogenesis pathway performed by the anaerobic methanotrophic Archaea (ANME)-1 clade of methanotrophic Archaea. All enzymes in this pathway were initially reconstructed based on genomic/ metagenomic evidence (gray), except for the oxidation of methyl-H4MPT to methylene-H4MPT, which metaproteomic data suggest is catalyzed by a homolog of MetF (white) that is presumably adapted to function with H4MPT (bifunctional H4MPT/tetrahydrofolate or strictly H4MPT dependent). Abbreviations: CoB, coenzyme B; CoM, coenzyme M; Fmd, formyl-MF dehydrogenase (complex); Fqo, F420H2-quinone oxidoreductase (complex); Ftr, formyl-MF:H4MPT formyltransferase; H4MPT, tetrahydromethanopterin; Hdr, CoB–S–S–CoM heterodisulfide reductase (complex); Mch, methenyl-H4MPT cyclohydrolase; Mcr, methyl-CoM reductase; MetF, methylene-tetrahydrofolate reductase homolog; MF, methanofuran; Mtr, H4MPT S-methyltransferase (complex). Based on [52].

authors noted, biochemical characterization of the MetF protein is required to test the hypothesis that it replaces Mer, but it was the metaproteome that initially provided MetF as a candidate for future investigation. In contrast to the above notable discoveries, in general important metabolic pathways are typically under-represented in current metaproteomes relative to transport functions. As a consequence of nutrient kinetics in marine microbes, processing of the imported substrate requires a relatively minimal number of cytoplasmic enzymes relative to extracytoplasmic proteins involved in solute capture [55], so the former tend to be low in abundance in metaproteomic data sets. Metaproteome coverage can be expanded by physical fractionation and enrichment of individual components of the ecosystem based on buoyant density [23] and sequential size fractionation using filters (e.g., [6,7,17–19]) (Table 1). This facilitates both metagenome and metaproteome coverage by subdividing biomass into fractions, thereby increasing representation of individual microbes, and reduces the complexity of samples leading to improved 256

coverage of DNA or protein and hence the resolution of community members. Fractionation by filtration also enables analysis of size partitioning of microbes occurring in the environment, including assessments of attached (such as to particulate matter or algal cells) versus planktonic forms (e.g., [7]). Metaproteomics has the potential to provide insights into important questions in marine biogeochemical cycling, but improved detection of cytoplasmic proteins is required. For example, metaproteomics has demonstrated the importance of phosphonate uptake by bacterioplankton (especially SAR11) for survival in phosphate-limited waters [1], but has yet to elucidate the fate of imported phosphonates once inside cells. Components of the cytoplasmic enzyme system responsible for phosphonate breakdown (C–P lyase) have been identified in oceanic SAR11 genomes, but the proteins have not been detected, presumably due to low gene expression levels compared with cognate ABC transporters [1]. In view of the ubiquity of SAR11 bacteria in marine environments [56], and the fact that methylphosphonate decomposition by bacterioplankton can lead to aerobic methane production [57], phosphonate degradation is not only crucial to oceanic phosphorus cycling, but is particularly relevant to global atmospheric methane levels. It is also possible that alternative liberation and assimilation pathways are used for the carbon moieties of phosphonates [58]. Metaproteomics offers the potential for identifying the fate of the carbon backbone of phosphonates. With increasing adoption of metaproteomics as a technique by the marine microbiology field, innovative ideas (e.g., investigations of AOM [29]) and technical approaches (e.g., proteomics-based binning [23]) will no doubt lead to the discovery of, and resolve questions about, novel metabolic pathways. This capacity should be greatly facilitated by the technological development of MS, which continues to see major advances in the sensitivity and throughput of protein detection and identification. Microbial interactions One limitation of proteomic studies of laboratory cultures is that potentially critical interactions between microbes that would occur within a natural community are not observed [59]. This is especially true for syntrophic and symbiotic interactions. For example, in quantifying proteins employed by bacteria to acquire nutrients, in the North Sea metaproteomic study [6] it was inferred that Flavobacteria that target biopolymers released simple substrates (especially monomers), making them available for other bacteria such as SAR11 and Roseobacter clade members. This was corroborated by a metaproteomic assessment of a Flavobacteria-dominated bacterioplankton community present in Newcomb Bay in East Antarctica [7]. Based on the detection of proteins involved in gliding motility and adhesion, the Antarctic study highlighted the importance of flavobacterial attachment to alga-derived detritus and possibly whole cells [7]. Both of these studies used DNA-based methods to ascertain the relative abundance of individual bacterial clades and used metaproteomics to determine the microbial interactions that were occurring at the time [6,7].

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within a specialized organ (the ‘trophosome’) [60,61]. Metaproteomic studies of the symbiont population revealed the concurrent functioning of dual carbon-fixation pathways (the Calvin cycle and the reductive tricarboxylic acid cycle). With sulfur oxidation proteins being especially abundant, the study also demonstrated the importance of oxidation of reduced sulfur compounds for energy metabolism [60–62].

Metaproteomics has proven to be valuable for studying the ecology of marine endosymbionts and identifying important metabolic interactions. The deep-sea giant marine tubeworms Riftia pachyptila and Tevnia jerichonana lack a mouth and gut and are therefore reliant for their nutrition on a single species of endosymbiotic gammaproteobacterium (Candidatus Endoriftia persephone) that is housed

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Figure 4. Overview of symbiotic metabolism between bacterial symbionts and the gutless marine worm Olavius algarvensis reconstructed using metaproteomics and metabolomics. The d1 and d4 symbionts are shown as a single cell, because most metabolic pathways were identified in the d1 symbiont and only a small fraction of the same pathways were identified in the d4 symbiont due to low metaproteome coverage. Abbreviations: 3-HPB, partial 3-hydroxypropionate bi-cycle; CM, cell material; CODH, carbon monoxide dehydrogenase (aerobic or anaerobic type); NiRes, nitrate respiration; OxRes, oxygen respiration; PHA, polyhydroxyalkanoate granule; S0, elemental sulfur; Sred, reduced sulfur compounds; SulOx, sulfur oxidation; Unk. TEA, unknown terminal electron acceptor. Constructed using an image provided by Manuel Kleiner (MPI Bremen) and based on [23].

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Review Symbiont TRAP transporters were highly abundant and presumably used to acquire organic acids that were subsequently assimilated by the reductive tricarboxylic acid cycle [63]. Integrating metaproteomic data with respirometry measurements of the metabolism of R. pachyptila from different hydrothermal sites revealed key differences in the ways in which nitrogen and sulfur metabolism were performed. These differences illustrated impressive physiological versatility bestowed by the symbionts to the tubeworm host in response to the disparate geochemistries of the local environment [60]. Furthermore, the metaproteomes of R. pachyptila and T. jerichonana symbionts from the East Pacific Ridge were found to be strikingly similar, which supports a hypothesis that the same symbiont has established a monospecific symbiosis with comparable physiological properties in both tubeworm hosts [61]. The marine worm O. algarvensis has symbiotic bacteria that reside within its body wall and grow on inorganic carbon and energy sources (sulfide and CO2), but in this case a multispecies bacterial consortium is present [23]. One symbiont, a sulfur-oxidizing gammaproteobacterium, was inferred to be capable of CO2 fixation via the Calvin cycle, with this autotroph in turn providing the host with organic matter for growth [23] (Figure 4). The sulfuroxidizing bacterium was itself provided with reduced sulfur compounds by sulfate-reducing deltaproteobacterial symbionts, allowing for sulfur cycling within the worm’s microbial consortium. In this study, metabolomics was used to identify organic compounds present in situ and it was inferred that the sulfate-reducing Deltaproteobacteria expressed ABC and TRAP transporters to import organic substrates derived either internally (via the coelom) or externally (via the cuticle). These transporter proteins were extremely abundant, detected at levels comparable to free-living marine microbes, but it is unclear whether the organic nutrients being scavenged by the ABC and TRAP transporters come from the external environment or are supplied internally within the worm [23]. In what is likely to be an overall nutrient-deplete environment, scavenging available sugars and polyamines from the environment, and carboxylates as waste products from the host, would be advantageous. Metaproteomic analysis of sponge symbionts also identified ABC and TRAP transporters, with the identities of the abundant PPBs consistent with the bacteria targeting dipeptides and halogenated compounds released by the sponge [20]. In the cases of the tubeworm and sponge symbionts, pathways for the intricate cycling of substrates could not have been discerned using metagenomic approaches alone. Given the difficulties of studying symbionts in the laboratory, particularly those associated with deep-sea creatures, the capacity to perform metaproteomics on environmental samples provides the only realistic means of evaluating what microbial processes are occurring and what metabolic interactions take place between microbial consortia members and their respective hosts. Hypothetical proteins One noteworthy aspect of many marine metaproteomes is the high proportion of proteins detected with no previously ascribed function, other than motifs or domains suggestive 258

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of function (e.g., [20,24,52]). For example, of the 187 AOA proteins detected in the metaproteome of the Antarctic Peninsula, Southern Ocean samples, 49 were annotated as hypothetical. Their only discernible characteristics included putative cell envelope function or proteins with signatures of catalytic domains (e.g., radical S-adenosyl methionine, oxidoreductase, permease) that may denote roles in cytoplasmic metabolism. From the metaproteomics analysis, possible functions for some of these hypothetical proteins were proposed based on their protein domain signatures in combination with knowledge about the taxonomy of community members and the microbial processes inferred to be occurring. These included putative flavobacterial exoenzymes that were proposed to target and degrade complex carbohydrates and polypeptides, as well as organophosphates and lipids [24]. In the sponge symbiont metaproteome [20], certain hypothetical proteins were also proposed to be cell envelope proteins. Those that possessed ankyrin repeat, tetratricopeptide, or adhesin domains were thought to mediate interactions between bacteria and the sponge host, including conferring resistance to phagocytosis if adventitiously ingested by the sponge [20,64]. The latter hypothesis was subsequently corroborated when ankyrin-repeat proteins from a gammaproteobacterial sponge symbiont were experimentally shown to interfere with phagocytosis [65]. The detection of these particular proteins, as well as the adhesion proteins and exoenzymes discussed above, illustrates the capacity of metaproteomics to detect surface and secreted proteins that interact directly with the extracellular milieu. However, secreted ‘free’ proteins that are released by cells into bulk seawater are less likely to be recovered by extraction techniques that obtain proteins from whole cells. By providing a functional context, metaproteomics provides ‘real-world’ opportunities for speculating about the functional properties of proteins, particularly those with previously unknown functions, and providing frameworks for hypothesis testing. Concluding remarks Metaproteomics has proven to be a powerful approach for deducing in situ metabolic activities of marine microbes and offers outstanding potential for making future discoveries. It is clear that metaproteomics works best when metagenome data for the environment is available. Metagenomics is instructive in assessing community composition and laying the blueprint for assessing the properties that microorganisms potentially possess, and metaproteomics builds crucially from this base to provide information about the cellular functions that are occurring to enable survival and growth in response to the environment at the time of sampling. In the marine environment, metaproteomics has proven to be particularly useful for learning how microbes acclimate to different nutrient regimes (e.g., limiting nutrients, nutrient flux, physical partitioning), temperature, light availability, and interactions with other microorganisms and metazoans. The wealth of knowledge gained through metaproteomics about metabolic processes impacts directly on our understanding of the roles that marine microbes play in

Review global biogeochemical cycles. This is well illustrated by understanding the important role that autotrophic marine microbes play in the fixation of CO2 and hence their contribution to the world’s oceans’ function as a carbon sink. By being able to penetrate the web of intertwined metabolic pathways inherent in complex consortia and symbiotic interactions, metaproteomics also provides the capacity for gaining ‘first insight’ into the ecological characteristics of microbes. With significant technological advances in both DNA sequencing and MS, the capacity to synergize high-coverage metagenomes and single amplified genomes with high-resolution metaproteomes means the potential for learning what microbes are doing in the ocean is growing in a rapid and cost-effective way. Of note, single-cell genomics provides a potentially useful and hitherto unexplored means for identifying proteins using metaproteomics. This is illustrated by the discovery that single amplified genomes of marine bacteria derived from environmental samples represent indigenous populations far better than genomes of laboratory isolates of the same species [66]. Because single amplified genomes better represent the community, provide blueprints for unculturable members of the marine community, and provide an improved means of utilizing metagenome data (e.g., fragment recruitment), single-cell genomics will improve metaproteome coverage of specific marine taxa. On a global scale the locations geographically represented by current metaproteomic analyses are a ‘drop in the bucket’ (Figure 1 and Table 1). Because metaproteomics has the capacity to investigate any marine system, long-term study locations that accumulate metadata over time offer great potential. This comes through the ability to integrate data and knowledge to aid interpretations, placing the outcomes of ‘snapshot’ metaproteomes into a broader ecological perspective, and ultimately to monitor dynamics and generate models suitable for predicting the impacts of ecosystem perturbation. Acknowledgments The authors thank Manuel Kleiner (Max Planck Institute for Marine Microbiology, Bremen, Germany) for generously providing the graphic for Figure 4 and acknowledge http://www.freeworldmaps.net for the world map used to create Figure 1. This work was supported by the Australian Research Council and the Australian Antarctic Science program. The authors acknowledge the positive and constructive comments made by the reviewers during the review process.

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