REV IEW AND
SYNTHES IS How mutualisms arise in phytoplankton communities: building
eco-evolutionary principles for aquatic microbes
Elena Kazamia,1* Katherine Emma
Helliwell,1† Saul Purton2 and
Alison Gail Smith1
Abstract
Extensive sampling and metagenomics analyses of plankton communities across all aquatic envi-
ronments are beginning to provide insights into the ecology of microbial communities. In particu-
lar, the importance of metabolic exchanges that provide a foundation for ecological interactions
between microorganisms has emerged as a key factor in forging such communities. Here we show
how both studies of environmental samples and physiological experimentation in the laboratory
with defined microbial co-cultures are being used to decipher the metabolic and molecular under-
pinnings of such exchanges. In addition, we explain how metabolic modelling may be used to con-
duct investigations in reverse, deducing novel molecular exchanges from analysis of large-scale
data sets, which can identify persistently co-occurring species. Finally, we consider how knowledge
of microbial community ecology can be built into evolutionary theories tailored to these species’
unique lifestyles. We propose a novel model for the evolution of metabolic auxotrophy in
microorganisms that arises as a result of symbiosis, termed the Foraging-to-Farming hypothesis.
The model has testable predictions, fits several known examples of mutualism in the aquatic
world, and sheds light on how interactions, which cement dependencies within communities of
microorganisms, might be initiated.
Keywords
Eco-evolutionary dynamics, Foraging-to-Farming hypothesis, metabolite exchange, metagenomics,
microbial communities, mutualism, phytoplankton, vitamins.
Ecology Letters (2016) 19: 810–822
INTRODUCTION
Microorganisms are the ‘unseen majority’ of life on Earth. As
well as being numerically dominant, they also constitute the
major phylogenetic diversity, even within the Eukaryotes
where nearly every lineage is dominated by unicellular or
microscopic species, and where multicellularity is the excep-
tion rather than the rule (Fig. 1). Moreover, in a range of
ecosystems including the soil and ocean biomes, microorgan-
isms make the major impact on global processes such as the
biogeochemical cycling of carbon, nitrogen and sulphur (Falk-
owski et al. 2008; van der Heijden et al. 2008). They are par-
ticularly important in the aquatic environment because here a
subset of species, the phytoplankton, which comprise both
eukaryotic microalgae and cyanobacteria, are responsible for
primary production, contributing an estimated 50% of the
total global carbon fixation (Field et al. 1998), and sustaining
all other trophic levels. However, despite their importance,
our understanding of the ecology of the phytoplankton and
the associated microorganisms in the photic zone is limited,
due both to a lack of theoretical principles that are relevant
to their unique lifestyles, as highlighted by Prosser et al.
(2007), but also to the difficulty in studying many of these
species in the laboratory. Aquatic microorganisms are notori-
ously difficult to isolate from the natural environment, as only
an estimated 0.01–0.1% of oceanic marine bacterial cells
produce colonies by standard diagnostic plating techniques
(Connon & Giovannoni 2002), and most species lack morpho-
logical characters. One of the proposed explanations for the
difficulty in isolating species is that community interactions,
which are severed in axenic (single organism) laboratory cul-
tures, are vital for the survival of microorganisms (e.g. Joint
et al. 2010).
Photosynthetic algae are at the start of most aquatic food
chains, and their consumption by zooplankton is the first link
in a classic aquatic trophic cascade. However, many plank-
tonic algae have more complex lifestyles (Fig. 2). Mixotrophy,
where photosynthesis is combined with uptake of dissolved
organic carbon, is common throughout the algal lineages.
Alongside osmotrophic uptake of dissolved organic carbon
(osmotrophy), representatives of several ecologically signifi-
cant groups such as dinoflagellates, carry out phagotrophy by
1Department of Plant Sciences, University of Cambridge, Downing Street,
Cambridge CB2 3EA, UK
2Institute of Structural and Molecular Biology, University College London,
Gower Street, London WC1E 6BT, UK
†Present address: The Marine Biological Association of the UK, Citadel Hill,
Plymouth PL1 2PB, UK
*Correspondence and present address: Department of Civil and Environmen-
tal Engineering, MIT, 15 Vassar Street, Cambridge, MA 02139, USA. E-mail:
kazamia@mit.edu
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use,
distribution and reproduction in any medium, provided the original work is properly cited.
Ecology Letters, (2016) 19: 810–822 doi: 10.1111/ele.12615
grazing on bacterioplankton prey (Jones 2000). Evidence from
field studies in the North Atlantic ocean have demonstrated
that photosynthetic mixotrophs can account for a staggering
40–95% of bacterivory in certain regions of the ocean (Hart-
mann et al. 2012). This complements laboratory-based studies,
which have demonstrated phagotrophy in eukaryotic phyto-
plankton species typically considered strict autotrophs, such
as the picoalga Micromonas (McKie-Krisberg & Sanders
2014), a particularly remarkable example given its tiny cell
size (< 2 lm). As such, mixotrophy is increasingly being
recognised as a major contributor to plankton dynamics, chal-
lenging the classic distinction made between ‘phototrophic’
phytoplankton and heterotrophic zooplankton (Flynn et al.
2012).
Similarly, defining symbiotic interactions between aquatic
microbes is equally complex, since these often defy strict cate-
gorisation (with only a subset of examples shown in Fig. 2).
For example corals are one of the better-studied aquatic asso-
ciations, where a cnidarian exchanges metabolites with a
dinoflagellate from the Symbiodinium genus. Traditionally,
this has been considered a classic case of mutualism, as inor-
ganic waste metabolites from the animal host are exchanged
for organic nutrients fixed by dinoflagellate photosynthesis
(Muscatine & Porter 1977), benefitting both partners. How-
ever, experimental evidence shows that there is considerable
functional diversity within the Symbiodinium lineage, with
certain clades interacting with hosts in a manner that is clo-
ser to parasitism, by fixing and releasing significantly less
carbon than close relatives also capable of the association
(Stat et al. 2008). Furthermore, some species of Symbio-
dinium have been shown to switch their behaviour from
mutualism to parasitism depending on the manner of trans-
mission. S. microadriaticum, which infects jellyfish as an
endophotosymbiont, was experimentally enforced to infect its
host through horizontal transmission (defined as infectious
transfer among unrelated hosts) and this selected for an evo-
lutionary shift to parasitism (Sachs & Wilcox 2006). Simi-
larly, it has been observed that within the dynamic
environment of open oceans, mutualisms underpinning algal
blooms may turn to parasitism as the bloom reaches its cli-
max and fades, often accompanied by sudden and extensive
viral lysis (e.g. Yager et al. 2001).
That microbial interactions in the aquatic realm do not fit
known ecological modes of interaction is not surprising, since
historically these have been formulated to explain life in ter-
restrial biomes. Perhaps the simplest way of interpreting aqua-
tic microbial interactions, on a fundamental level, is through
the lens of characterising the metabolism of the constituent
species. We propose that symbioses in this context should be
classified as ‘active metabolic associations between two or
more organisms, with an implied ecology’ to distinguish from
the passive interactions that can be a by-product of living in a
shared environment. Passive interactions would include nutri-
ent exchange through metabolic by-product exudates, or fol-
lowing virus-induced lysis of cells. These give rise to a
dissolved pool of organic nutrients, made available to species
either at a different depth or significantly later in time, in pace
with circulation events such as seasonal upwelling along conti-
nental margins, in a process known as the ‘microbial loop’
(Azam et al. 1983). Similarly, trophic interactions would not
be strictly symbiotic as they constitute an active behaviour on
the part of only one of the species, rather than both. Follow-
ing this definition, a symbiotic interaction would require that
both species are alive during their association and affect each
other’s metabolism, cellular functions and lifestyle. While
physical associations are possible and frequent in the micro-
bial world, in our view they are not a pre-requisite for sym-
biosis, as metabolic exchanges could happen without contact.
We discuss the challenges associated with studying the physi-
cal aspects of microbial interactions later in the paper.
Furthermore, we consider that while not all symbiotic interac-
tions are specific, this should be a pre-requisite for mutualism,
which implies recurrent interactions and the potential for co-
evolution. Nonetheless, the mutualism need not be permanent,
but might operate under particular environmental conditions,
or stage of the life cycle.
An important development in recent years, which is revolu-
tionising the study of microbial communities, is that of ‘omics
methodologies that can collect whole systems data from envi-
ronmental samples, including aquatic ecosystems. Sequencing
of marker genes such as 16S rRNA genes for prokaryotes and
18S rRNA for eukaryotes has allowed the ‘metabarcoding’ of
the species diversity within these samples (Mende et al. 2013;
de Vargas et al. 2015). This is a culture-free method that can
track microbial species richness across global transects. Fur-
thermore, the sequencing of whole genomes from sampled
communities, a practice referred to as metagenomics, has
opened the possibility for comparisons of metabolic functions
across samples, and metatranscriptomics and metaproteomics
can confirm the expression of the genes and infer presence of
Figure 1 Unicellular organisms dominate the eukaryotic lineages. A
schematic diagram of the eukaryotic tree of life showing the major groups
(Dorrell & Smith (2011); Burki 2014). At present the positions of the
Haptophytes, Telonemids, Cryptomonads and Centrohelids remain
uncertain (Incertae sedis). Multicellularity has evolved only seven times
(highlighted with filled circles); all other lineages are essentially microbial.
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
Review and Synthesis How mutualisms arise between aquatic microbes 811
function, which gives a snapshot of the ecological state of a
community, allowing for comparisons in time or under differ-
ent conditions (e.g. Moran et al. 2013). On the other hand,
these whole state studies do not in themselves shed light on
the specific interactions of the microbes within, which is only
possible through physiological experimentation using defined
systems. Nonetheless, there are cross-links between the two.
Co-occurrence within metabarcoding data sets can be indica-
tors of active interactions. Similarly, it is possible to assess
whether a model laboratory system is widespread by looking
for functional genes that reflect it in metagenomic or meta-
transciptomic compilations.
In the following review, we synthesise recent knowledge
from these two complementary fields to draw conclusions on
what they can tell us about mutualisms in aquatic communi-
ties, with particular reference to microalgae. Furthermore, we
demonstrate how mechanistic understanding of a specific
interaction can explain eco-evolutionary aspects, leading to
Viral lysis
fixed 
carbon
nutrients
algaecide
Mutualism
PHOTOTROPHY
Phagotrophy
Dissolved 
organic
nutrients
Sunlight
Bacteria
Phytoplankton
Phytoplankton
exudate
MIXOTROPHY
Endosymbiosis
Parasitism
HETEROTROPHY
SY
MB
IOS
IS
Figure 2 Schematic of phytoplankton lifestyles. Ecologically significant groups, including diatoms, bloom and are subject to viral lysis and grazing by
heterotrophic zooplankton. This releases organic nutrients into solution, which both cyanobacteria and algae can utilise via mixotrophy. Moreover, many
algae such as dinoflagellates consume bacterial prey via phagotrophy, resulting in net CO2 release and O2 consumption. In addition to these trophic
processes is a complex series of interactions, or symbioses, which have shaped the ecology and evolution of microbes in aquatic communities. Many
examples of mutualism are known, where algae supply fixed carbon (photosynthate) in exchange for specific nutrients such as vitamins. Parasitism can also
arise, as in the case of senescing haptophytes, where bacterial partners that were initially mutualistic produce algaecides to accelerate the process, indicating
that interactions can be dynamic. Intimate physical associations, in the form of endosymbiosis, such as between the amoeboid protistan radiolarians and
haptophytes, are also frequent.
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
812 E. Kazamia et al. Review and Synthesis
establishment of theoretical principles in the burgeoning field
of microbial ecology.
WHOLE SYSTEMS APPROACHES TO STUDYING
INTERACTIONS WITHIN MICROBIAL COMMUNITIES
The advent of affordable high-throughput genomic analyses
has uncovered unexpected microbial diversity from a range of
biomes, including soil and aquatic environments, and has
expanded our horizons of the ‘known unknowns’ of all extant
life on earth (e.g. Pace 1997). Once it was possible to cata-
logue the genetic diversity into data sets, this opened the door
for investigations into the function of genes within organisms
as well as between interacting species. Chaffron et al. (2010)
presented one of the first studies of genomic correlates
between diverse sampling sites. The purpose was to uncover
consistent associations that could be indicative of ecological
interactions. Using network clustering and co-occurrence anal-
yses the investigators were able to identify putative novel
associations; for example, a lineage of cyanobacteria (belong-
ing to the halophilic Euhalothece) was observed to be associ-
ated with an uncharacterised lineage having no cultivated or
named representatives (a monophyletic sister group of the
Psychroflexus lineage of bacteroidetes).
The Sorcerer Global Ocean Survey (GOS) was the first glo-
bal scale effort to obtain metagenome DNA sequences from
communities of marine microbes (Venter et al. 2004). It
obtained 6.3 gigabases of DNA sequences from surface-water
samples collected along a transect from the Northwest Atlan-
tic to the Eastern Tropical Pacific. Information from the GOS
together with 30 smaller scale independent projects con-
tributed towards the Census of Marine Life and the Interna-
tional Census of Marine Microbes (ICoMM). Analysis of the
data compiled by ICoMM uncovered the ‘rare biosphere’ of
low-abundance microbial populations that account for most
of the observed phylogenetic diversity in the deep ocean, and
represent an inexhaustible source of genomic innovation
(Sogin et al. 2006). Interrogation of microbial metagenomic
sequence data collected as part of the Sorcerer II Global
Ocean Expedition revealed a high abundance of viral
sequences, representing approximately 3% of the total pre-
dicted proteins (Williamson et al. 2008). While the GOS pro-
jects clearly represent an important advance in allowing
microbial species composition and diversity to be catalogued
on global scales, species composition analysis was confined to
prokaryotic organisms, and there was little consideration of
interactions between the species.
The Tara Oceans Expedition, which was unveiled in the
spring of 2015, superseded all previous efforts in its magni-
tude, collecting ~ 35 000 samples across multiple depths at a
global scale over a period of 3 years (Bork et al. 2015; de
Vargas et al. 2015). The extent of the data set has provided
the means to determine the microbial ‘interactome’. For
example Lima-Mendez et al. (2015) focussed on data from
viruses to small metazoans collected at 68 ocean stations.
Co-occurrence detection techniques were applied to data sets
sub-classified into kingdoms (e.g. data exploring eukaryote
diversity focused on the hyper variable V9 region of the 18S
rRNA genes only) and also across kingdoms. Machine
learning techniques applied to the integrated network pre-
dicted 81 590 interactions based on correlations, and found
that the majority (~ 78%) of these were positive, that is to say
the presence of one species provided a supporting role for
another. Largely, these reflected the nature of trophic cas-
cades, for example zooplankton were commonly associated
with their preferred food, and parasites were associated with
their hosts, but interestingly, there were also a range of posi-
tive interactions observed between planktonic microorganisms
belonging to the same size category. The basis for these
interactions remains unknown, but it is possible that they rep-
resent mutualisms. Mining of the Tara interactome confirmed
that previously known mutualisms were captured by the net-
work analysis, such as the symbiosis between diatoms and
flavobacteria (Jolley & Jones 1977), and dinoflagellate associa-
tions with members of Rhodobacterales (Ruegeria sp.) (Miller
& Belas 2004). Moreover, certain interactions predicted by the
study could then be confirmed experimentally. For example
an endosymbiotic photosymbiotic interaction between an
acoel flatworm (Symsagittifera sp.) and a green microalga
(Tetraselmis sp.) was predicted by consistent V9-V9 co-occur-
rence in the Tara data set. Fifteen acoels specimens collected
independently were then used to validate the interaction, both
by laser scanning confocal microscopy and by molecular biol-
ogy through single cell 18S rDNA sequencing.
One of the main limitations of metagenomics and metabar-
coding, however, is that it does not link metabolic capabilities
directly to a particular species within the community. At best,
analysis of sequence data provides correlations, and confirma-
tion of direct interactions requires physiological and biochemi-
cal data, which are challenging to obtain with environmental
samples. Metatranscriptomics and metaproteomics can argu-
ably provide a bridge to link the two. Such analyses can
demonstrate the executed functions within microbial commu-
nities at time of sampling, and often reveal unexpected infor-
mation. For example while metagenomic analysis of biofilms
on the hulls of naval vessels indicated a preponderance of
bacteria, the majority of proteins identified by metaproteomics
using liquid chromatography-tandem mass spectrometry were
eukaryotic (Leary et al. 2014). Quantitative 18O and iTRAQ
analyses, coupled with measurement of photosynthetic pig-
ments confirmed that the communities were dominated by
diatoms. Similar inferences about the functional dynamics of
aquatic communities can be made from metatranscriptomic
analyses, and have been used to good effect to monitor suc-
cessions during algal blooms, (Cooper et al. 2014), to establish
the effect on the bacterial population associated with the
bloom (Wemheuer et al. 2014), or to show how nutrients
affect niche differentiation (Harke et al. 2016).
STUDYING THE METABOLIC BASIS FOR
MUTUALISMS BETWEEN MICROBES
Despite the considerable information that can be gained from
studies of environmental samples, inferring and characterising
interactions is at best correlative – a process once described as
‘akin to boiling dinner leftovers in a pot for 24 h, pureeing
heavily and then trying to attribute any spice or stew frag-
ment back to the original dish or constituent from which it
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
Review and Synthesis How mutualisms arise between aquatic microbes 813
derived’ (Heidelberg et al. 2010). To gain real mechanistic
understanding of interactions it is necessary to study defined
or model systems that can be co-cultured under controlled
conditions, enabling identification of the metabolic founda-
tions for the ecology, demonstrating directly the compounds
that are exchanged, and studying the molecular machinery
involved in the associations. Importantly, studies of model
systems generate testable hypotheses of how the interactions
might have evolved, which in turn will allow development of
eco-evolutionary principles.
The lifestyle of a unicellular organism is constrained by its
individual metabolism. Metabolic requirements that have to
be fulfilled to ensure survival but cannot be satisfied by the
abiotic environment create the ecological niche for mutualism.
For example microorganisms vary in their capacity to access
essential elements from inorganic molecules, frequently requir-
ing them in a specific ‘bioavailable’ form that is dependent on
the metabolic activity of other species.
Historically, the study of metabolic requirements in aquatic
microorganisms has focused largely on the adaptations of
individual species for acquiring nutrients, the latter classified
as either macro (C, N, O, H, P and S) or micro depending on
the quantity required. Micronutrients are required in much
lower amounts, but have essential functions. These include the
mineral micronutrients (e.g. Ni, Mo, Zn, Cu, Mn, Fe and
Co), involved in protein function, enzyme catalysis and elec-
tron transfer reactions, and a range of organic vitamins
required for enzyme cofactors. A particularly important exam-
ple is iron, which is limiting to algal growth in much of the
world’s oceans, including the equatorial Pacific and Southern
Oceans (Behrenfeld et al. 1996; Behrenfeld & Kolber 1999).
Many bacteria produce siderophores, organic chelators of
both FeII and FeIII, which allow them to sequester this scarce
nutrient. Specific mutualistic interactions have been described
in which microalgae engage with heterotrophic bacteria to
access this source of chelated Fe. For example several clades
of Marinobacter found in close association with two major
groups of marine algae, dinoflagellates and coccolithophores,
produced an unusual siderophore, vibrioferrin (VF), which
when chelated to iron undergoes photolysis at rates that are
10–20 times higher than siderophores produced by free-living
marine bacteria (Amin et al. 2009). Experiments confirmed
that photolysis of the chelates increased algal uptake of Fe-
VF by > 20-fold.
It is widely acknowledged that the two macronutrients most
limiting to phytoplankton are nitrogen and phosphorus (Tyr-
rell 1999). Only certain prokaryotic species (‘diazotrophs’) are
capable of fixing the inert dinitrogen gas into bioavailable
forms. In the photic zones of the ocean, these diazotrophs are
mainly cyanobacterial species of various morphologies and
lifestyles (Zehr & Kudela 2011). A proportion of these
exchange fixed nitrogen for photosynthate with diatoms, in a
symbiosis referred to as diatom-diazotroph associations. For
example Richelia intracellularis and Calothrix rhizosoleniae, fil-
amentous heterocyst-forming cyanobacteria, have been found
in mutualism with several diatom genera, including Hemi-
aulus, Rhizosolenia and Chaetoceros (Zehr & Ward 2002). The
interactions are highly dynamic, demonstrated by the fact that
the length, location and number of Richelia and Calothrix
trichomes per diatom partner, and phylogeny of the sym-
bionts, differ in each symbiosis (Jahson et al. 1995; Foster &
Zehr 2006).
Unicellular nitrogen-fixing cyanobacteria also are thought
to interact with microalgae. Using metagenomic techniques,
Zehr et al. (2003) identified two novel groups of unicellular
diazotrophic picocyanobacteria, UCYN-A and UCYN-B
(now formally classified as Crocosphaera watsonii). Whole-
genome amplification of UCYN-A (Candidatus Atelo-
cyanobacterium thalassa) revealed that it lacks genes for
photosystem II and the Krebs and Calvin cycles, but retains
sufficient electron transfer capacity through alternative elec-
tron donors to generate energy and reducing power from light
(Tripp et al. 2010). Since this metabolic capability is insuffi-
cient for an autotrophic lifestyle, it was hypothesised that
UCYN-A was mutualistic with photosynthetic picoeukaryotes
(PPEs), with which it frequently co-occurred. Microscopy of
individual cells coupled to secondary ion mass spectrometry
(referred to as nano-SIMS), in combinations with halogen
in situ hybridisation confirmed the interaction visually by
demonstrating the delivery of carbon from the PPEs to
UCYN-A cells (Thompson et al. 2012). This is a powerful
example of how single cell imaging techniques can be used to
show directly the transfer of metabolites between interacting
species. Further investigations revealed that at least two dif-
ferent UCYN-A phylotypes exist (Bombar et al. 2014), the
clade UCYN-A1, which is predominantly coastal and found
in symbiosis with an uncultured small prymnesiophyte, and
the clade UCYN-A2, its open ocean relative which is found in
symbiosis with the larger Braarudosphaera bigelowii. Studying
the geographical distribution of UCYN-A1 and UCYN-A2
and symbionts recorded within the Tara data set revealed a
strikingly consistent co-occurrence (Cabello et al. 2015),
despite the absence of conclusive evidence for physical associ-
ation in these relationships.
Mutualism based on vitamin exchange has also been
demonstrated between microalgae and heterotrophic bacteria
(e.g. Croft et al. 2005; Wagner-D€obler et al. 2010). Over half
of microalgal species surveyed across all lineages require
cobalamin (vitamin B12), ~ 22% require thiamine (B1) and
5% require biotin (B7) (Croft et al. 2006). In the case of thi-
amine and biotin, auxotrophic species have lost the ability to
synthesise the metabolite de novo, although often retain parts
of the metabolic pathway. For example thiamine-requiring
algae are commonly able to survive on one or more biosyn-
thetic intermediates (McRose et al. 2014). This is also true for
heterotrophic bacteria that are B-vitamin auxotrophs. Repre-
sentatives belonging to the abundant and ubiquitous SAR11
clade of marine chemoheterotrophic bacteria have genes for
all the thiamine biosynthetic enzymes except for thiC, encod-
ing an enzyme required for the synthesis of the pyrimidine
moiety, 4-amino-5-hydroxymethyl-2-methylpyrimidine (HMP)
(Carini et al. 2014). Interestingly, the authors found that while
the SAR11 isolate ‘Candidatus Pelagibacter ubique’ was able
to grow on HMP, addition of thiamine itself to laboratory
cultures did not rescue growth. The authors attribute this to
the absence of thiamine transporters in the Ca. P. ubique gen-
ome. They propose that vitamin cycling mediated through
partial precursors and the presence/absence of transporters
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
814 E. Kazamia et al. Review and Synthesis
requires cooperation and interactions within marine microbial
communities. Another study by Paerl et al. (2015) investigated
thiamine cycling between the marine bacterium Pseudoal-
teromonas sp. TW7 and cosmopolitan marine picoalga Ostreo-
coccus lucimarinus CCE9901. The bacterium was able to
enhance the bioavailability of the pyrophosphorylated form of
the vitamin, thiamine pyrophosphate (TPP) to O. lucimarinus.
Bacterial phosphatase activity was inferred to metabolise TPP
to thiamine monophosphate, which is better able to support
O. lucimarinus CCE9901.
Non-requirers of thiamine and biotin are able to synthesise
the compounds for their own metabolism but the underlying
genetic reason for vitamin B12 auxotrophy in algae is quite
different. This compound is made only by prokaryotes (War-
ren et al. 2002), in a process that requires more than 20
enzyme-catalysed steps from the common tetrapyrrole precur-
sor. Despite the widespread occurrence of B12 requirement
amongst algae, there is no phylogenetic relationship between
them, with auxotrophs and non-auxotrophs often found
within the same genus, for example Chlamydomonas nivalis
requires B12, but C. reinhardtii, does not. Vitamin B12 is used
primarily as an essential cofactor for the enzyme methionine
synthase (METH), the key enzyme of one-carbon (C1) meta-
bolism. An alternative B12-independent methionine synthase
(METE) exists, but is catalytically less efficient than METH
(Gonzalez et al. 1992). Auxotrophs have METH only,
whereas non-requirers either have both enzymes, as is the case
for C. reinhardtii, or METE only, such as Coccomyxa sp.
C-169 and Cyanidioschyzon merolae (Croft et al. 2005;
Helliwell et al. 2011), suggesting that B12-dependence arose
through the loss of METE numerous times in algal evolution.
Helliwell et al. (2015) were able to demonstrate this experi-
mentally in C. reinhardtii, which lost a functional copy of
METE in fewer than 500 generations of vitamin B12 supple-
mentation, indicating of the ease with which this might have
occurred in other lineages.
The most comprehensive analysis of vitamin B12 concentra-
tions in the ocean was along a transect off the coast of Cali-
fornia (USA), which detected little to no vitamin B12 in
surface ocean waters (Sa~nudo-Wilhelmy et al. 2012), provid-
ing evidence that this organic micronutrient might be limiting
for algal requirers. Indeed enrichment experiments showed
that addition of B12 stimulates phytoplankton growth in sam-
ples of water collected from temperate coastal areas (Sa~nudo-
Wilhelmy et al. 2006; Gobler et al. 2007), the Southern
Ocean’s Gerlache Straight (Panzeca et al. 2006), and the Ross
Sea (Bertrand et al. 2007). Since only bacteria are capable of
B12 biosynthesis, they must be the ultimate source of the vita-
min, and it has been suggested that acquisition is through
mutualism with bacterial producers (Croft et al. 2005). Several
laboratory co-cultures have been described where there is
delivery of vitamin B12 from bacteria to algae in exchange for
photosynthate, including for members of the Chlorophyta
(Croft et al. 2005; Kazamia et al. 2012), Alveolata (Wagner-
D€obler et al. 2010), and diatom (Heterokontophyta) lineages
(Durham et al. 2014). Even though many of the co-cultures
were the result of artificial combination, they are often excep-
tionally stable. For example co-cultures of the green alga
Lobomonas rostrata with the alpha-proteobacterium
Mesorhizobium loti persist at the same algal : bacterial ratio
(of ~ 1 : 30) over many rounds of sub-culturing (Kazamia
et al. 2012), and follow predictable dynamics indicative of reg-
ulation (Grant et al. 2014). Interestingly, not all combinations
of bacterial producers and algal auxotrophs led to stable co-
cultures (Kazamia et al. 2012), which is indicative of species-
specific associations and not simple metabolic fitting.
Looking for evidence of symbioses between algae and bacte-
ria for vitamin B12 acquisition in the natural environment,
Bertrand et al. (2015) identified Oceanospirillaceae ASP10-02a
as a possible vitamin B12 producer in sea-ice edge microbial
communities from the Southern Ocean, which are charac-
terised by extensive blooms of diatoms during the Antarctic
summer. Metatranscriptomics data showed that Oceanospiril-
laceae ASP10-02a contributed more than 70% of reads from
cobalamin biosynthesis-associated genes, and peptides of one
particular enzyme, CbiA, from this species were abundant in
a proteomics data set. Interestingly, they also observed tran-
scripts for proteins involved in uptake and salvage of B12
from other bacteria, such as Methylophaga, which does not
encode the complete biosynthetic pathway. This implies sev-
eral different phytoplankton–bacterial interactions for provi-
sion of this organic micronutrient that might involve both
positive and negative feedback loops.
The above examples describe studies of microbial interac-
tions where the metabolic requirement or auxotrophy is
known. However, is it possible to infer metabolic exchanges
based on known recurring species correlations? The large data
sets cataloguing microbial diversity offer this possibility.
Zelezniak et al. (2015) analysed a compilation of 16S rRNA
sequences to obtain the species composition for 1297 commu-
nities from habitats including soil, water and the human gut.
For 261 species whose genomes are sequenced and mapped,
the authors constructed whole-genome metabolic models using
the ModelSEED pipeline (Henry et al. 2010). Two metrics,
the metabolic resource overlap (MRO) and the metabolic
interaction potential (MIP), were used as indicators for
competition or possible mutualism respectively. On average,
communities had higher MRO scores than predicted by
chance, and intriguingly the authors found high MIP scores in
nutritionally rich habitats where incentive for metabolic
cross-feeding would be predicted to be lower. The ‘Species
METabolic interaction ANAlysis’ (SMETANA) algorithm
was used to identify metabolic exchanges in a community that
was modelled as living on minimal medium. It predicted that
the most frequently exchanged metabolites were amino acids
and sugars. SMETANA was verified against a well-studied
three-species bacterial community (Fig. 3a; Miller et al. 2010),
and co-cultures of the yeast Saccharomyces cerevisiae and
C. reinhardtii (Hom & Murray 2014), summarised in Fig. 3b.
The model correctly reproduced known exchanges and
identified further possible links in the system, namely that
S. cerevisiae might also be able to deliver aspartate, gluta-
mate, glutamine and serine to C. reinhardtii, although there is
as yet no experimental evidence that C. reinhardtii can be sup-
ported by these nutrients. This highlights an important limita-
tion of bioinformatics approaches when used in isolation,
namely that genetic capacity may not accurately predict physi-
ology. A further example of this comes from studies of the
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
Review and Synthesis How mutualisms arise between aquatic microbes 815
production and use of vitamin B12 amongst different phyto-
plankton classes. Cyanobacteria are known producers of B12,
and have been proposed to be a major source of the vitamin
to B12-requiring eukaryotic algae (Bonnet et al. 2010). How-
ever, biochemical and physiological investigations revealed
that cyanobacterial species such as strains of the abundant
marine genus Synechococcus produce a form of B12, pseudo-
cobalamin, which is considerably less bioavailable to eukary-
otic algae (Helliwell et al. 2016).
FROM METABOLIC FITTING TO COMPLEX
REGULATORY DYNAMICS
While exchange of nutrients is considered to be at the heart of
associations between marine microorganisms, there is often
more complicated ecology involved. For example Seyedsayam-
dost et al. (2011) describe a ‘Jekyll-and-Hyde’ association
between the bloom-forming coccolithophore Emiliania huxleyi
and the roseobacter Phaeobacter inhibens (BS107). During a
bloom, E. huxleyi can account for 80–90% of the phytoplank-
ton in an area, and up to 60% of the bacterial community
belong to the roseobacter clade (Alpha-proteobacteria)
(Gonzalez et al. 2000), so associations between the two are
thought likely. The reduced system described by Seyedsayam-
dost et al. (2011) was brought into the laboratory for analysis
and exhibited two stages. Initially P. inhibens (BS107) pro-
moted algal growth by biosynthesising auxins and antibiotics
against algal competitors, and E. huxleyi released dimethyl-
sulphopropionate (DMSP) in return, which the bacteria used
as a carbon source. However, when the algae began to
senesce, P. inhibens (BS107) switched its metabolism to the
production and secretion of selective algaecides, killing their
symbionts and switching to parasitism (Fig. 2).
A further hormone-regulated interaction between algae and
bacteria was described by Amin et al. (2015), who showed
that cultures of the ubiquitous diatom Pseudo-nitzschia multi-
series were regulated by a Sulfitobacter-related species of bac-
terium, referred to as SA11, through the secretion of the
auxin indole-3-acetic acid. The association was chosen based
on the previous observation of regular associations between
different geographical isolates of Pseudo-nitzschia multiseries
originating from the Atlantic Ocean and the north Pacific
Ocean with clades of bacteria belonging to Alpha-proteobac-
teria (Sulfitobacter), Gamma-proteobacteria (Marinobacter),
Beta-proteobacteria (Limnobacter) and Bacteroidetes (Cro-
ceibacter) (Amin et al. 2012). In the laboratory study, the Sul-
fitobacter cells were demonstrated to receive organic carbon
required for growth, as well as taurine, a sulphonated metabo-
lite from the diatom, and responded to stimulation by DMSP,
which diatoms also produce. In return, the bacteria enriched
the co-culture medium with ammonium, the preferred nitro-
gen source for diatoms, by switching their own metabolic
preference to nitrate (Amin et al. 2015).
The Pseudo-nitzschia genus of diatoms includes bloom-
forming toxin-producing species, as well as non-toxic repre-
sentatives. Working with isolates of Pseudo-nitzschia collected
from the Santa Cruz Wharf in California, Sison-Mangus et al.
(2014) compared the bacterial associations of toxic Pseudo-
nitzschia with non-toxic species. Different diatom strains had
their own unique bacterial communities. To investigate the
physiology of interactions, transplant experiments were per-
formed, where bacteria associated with one host were co-cul-
tured with a different Pseudo-nitzschia isolate. A change in
behaviour was shown for certain bacteria that were mutualis-
tic to their native diatom but were commensal or parasitic to
foreign hosts. Moreover, the algae exhibited plasticity with
regards to domoic acid toxin production, depending on the
bacterial species with which they were co-cultured: less
domoic acid was produced when in association with their cog-
nate bacteria.
Further evidence of complex regulatory symbiotic interac-
tions between marine microorganisms comes from the work
of Decelle et al. (2012). Using molecular techniques in cul-
ture-free studies it was shown that heterotrophic amoeboid
protists belonging to the Acantharia (Radiolaria), which are
some of the most abundant grazers in nutrient poor oceans,
often engage in photosymbiosis with Phaeocystis species, a lin-
eage of haptophyte eukaryotic microalgae ubiquitous in the
marine environment. Photosymbioses between heterotrophic
hosts and photosynthetic microalgae are widespread and
prevalent in the oceanic plankton (Decelle et al. 2015). In the
model interaction described by Decelle et al. (2012), more
than 100 individual acantharian protists were isolated from
seven geographical locations, and in each case were found to
contain Phaeocystis cells in endosymbiosis with the host.
There was no consistent relationship between the phylogenies
Chlamydomonas
 reinhardtii
Saccharomyces
cerevisiae
NH3
CO2
Aspartate
Acetate
Glutamine
Serine
(a)
(b)
Desulfovibrio vulgaris Geobacter sulfurreducens
Clostridium celluloyticum
H2
Eth
ano
l Pyruvate
Acetate
H2
Figure 3 Microbial systems with well-characterised metabolic exchanges.
These have been used to validate the SMETANA algorithm devised by
Zelezniak et al. (2015). In each case solid arrows represent known
exchanges tested in physiological studies and dotted arrows mark
potential novel interactions predicted by SMETANA. (a) A three-species
community based on cellobiose degradation (Miller et al. 2010).
SMETANA predicts that pyruvate and hydrogen may also be delivered to
G. sulfurreducens by C. cellulolyticum. (b) An algal-fungal mutualism
between C. reinhardtii and Saccharomyces cerevisiae (Hom & Murray
2014). As well as refining the likely forms of N and S that are exchanged,
SMETANA predicted that during co-culture growth aspartate, glutamine
and serine could also be delivered from the yeast to the alga.
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
816 E. Kazamia et al. Review and Synthesis
of the interacting organisms, implying a facultative mutualism
on the part of the Phaeocystis. Taken together with the obser-
vation that in each case the Phaeocystis species were also
known to have an extensive free-living population, the authors
inferred that the symbiosis was selected for by local biogeog-
raphy. However, the morphology of the haptophytes during
the endosymbiosis was altered significantly, which suggests
intricate metabolic associations that profoundly affect cellular
structure and function and remain to be unravelled.
UNDERSTANDING HOW SYMBIOSIS AFFECTS
EVOLUTION OF MICROORGANISMS AND VICE-VERSA
Within the natural environment, the complexity of microbial
communities remains challenging to interpret both function-
ally (i.e. ecologically) and from an evolutionary perspective,
particularly in the absence of theoretical models that link
microbial ecology to evolutionary theory. A pivotal question
about the evolution of interacting microorganisms is whether
metabolic exchanges are the outcomes of stable ecological
associations, or coincidental by-products of these exchanges
constrained by abiotic pressures.
In the oligotrophic oceans, habitats characterised by severe
nutrient limitation, there is a strong selective pressure for
streamlined genomes, leading to cells with lower DNA and
associated protein content, and therefore lower cellular
requirements for P and N (Dufresne et al. 2008). The domi-
nant producers in the tropical oligotrophic oceans are pico-
cyanobacteria belonging to the genus Prochlorococcus (Olson
et al. 1990), which have the smallest genomes of any free-
living phototroph, with some isolates encoding only ~ 1700
genes (Rocap et al. 2003). Similarly, the dominant hetero-
trophs in these regions belong to the SAR11 clade. Ca.
P. ubique, the first cultured member of the SAR11 clade, has
~ 1400 genes (Giovannoni et al. 2005). Although it encodes
complete biosynthetic pathways for all 20 amino acids it has
no pseudogenes, introns, transposons or extrachromosomal
elements, and the shortest intergenic spacers yet observed for
any cell.
However, reductive genome evolution often causes loss of
key functions. For example Prochlorococcus has a smaller
suite of oxidative-stress genes than its closest relatives from
the Synechococcus genus (Regelsberger et al. 2002). Specifi-
cally, no Prochlorococcus isolate encodes catalase-peroxidase
(katG), a haem-dependent enzyme that is thought to be the
primary defence against external hydrogen peroxide (H2O2)
(Morris et al. 2008; Scanlan et al. 2009). Morris et al (2011)
estimated that loss of this enzyme would reduce the cell quota
for Fe in Prochlorococcus MED4 by 0.2%. Laboratory experi-
ments demonstrated that Prochlorococcus grows better in the
presence of heterotrophic bacteria, which reduce the concen-
trations of H2O2 (Morris et al. 2008). It was shown that these
‘helpers’ of Prochlorococcus such as Alteromonas EZ55 encode
katG, and were able to deplete H2O2 from seawater to levels
that were no longer toxic to Prochlorococcus (Morris et al.
2011).
The work on Prochlorococcus led to the proposal of the
Black Queen Hypothesis (BQH; Morris et al. 2012), a game-
theory model for the evolution of mutualism in microbial
communities. To our knowledge, it is currently the only theo-
retical framework that links community microbial ecology to
the evolution of dependency in individual species. The BQH
(summarised in Fig. 4) posits that communities evolve to sus-
tain a division of labour amongst the individual players. If an
essential function is lost from a subset of species, this provides
selection pressure for maintaining the provision of a shared
‘public good’ in helper species. In the case described,
Prochlorococcus does not produce catalase but is protected
from H2O2 by mutualist heterotrophs.
The BQH therefore applies only to ‘leaky’ functions and
scenarios, where ‘public goods’ are traded against a back-
ground of severe nutrient limitation. This is in contrast to the
prediction by Zelezniak et al. (2015) that interactions abound
even under conditions of nutrient sufficiency. Moreover,
experimental evolution approaches provide evidence that loss
of function is the result of nutrient sufficiency. Growth of
C. reinhardtii in elevated CO2 over 1000 generations resulted
in several lines that exhibited a markedly reduced growth rate
at ambient levels, (Collins & Bell 2004). Similarly, after ~ 500
generations in 1 lg L
1 B12 (Helliwell et al. 2015), a level
> 100 higher than ambient (Sa~nudo-Wilhelmy et al. 2012) a
B12-dependent C. reinhardtii mutant arose due to the loss of
METE gene. It is worth mentioning that the evolved B12-
dependent clone of C. reinhardtii could be grown in co-culture
with B12-synthesising rhizobial bacteria in medium without
either B12 or a fixed carbon source, in apparently regulated
mutualism.
Figure 4 Black Queen Hypothesis (BQH). The Black Queen refers to the
Queen of Spades in the card game Hearts, where players try to avoid
ending up with this card, since it carries the greatest number of negative
points. In the microbial community illustrated, the ability to detoxify
H2O2 is analogous to the Queen of Spades, because it requires katG, an
enzyme with a high Fe cost. Helper bacteria, such as Alteromonas sp. act
as a sink for H2O2 and keep concentrations low enough for
Prochlorococcus and other members of the aquatic community, including
the numerically dominant heterotrophic Candidatus Pelagibacter ubique,
to survive. Prochlorococcus is the photosynthetic producer in the system,
fixing carbon that is made available to the other species in the
community.
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
Review and Synthesis How mutualisms arise between aquatic microbes 817
Taking these observations further it is possible to propose a
model for the evolution of mutualism among algal lineages
generally, using the delivery of B12 as example. If a B12-inde-
pendent alga such as C. reinhardtii that can use the vitamin
when available (a ‘Forager’) is in contact for prolonged peri-
ods with a bacterium that synthesises B12, this might cause
the loss of the algal METE. At this point the alga will be
dependent on the bacterial B12-producer, and it may well then
change its behaviour to ‘farm’ the bacterium, providing pho-
tosynthate or other nutrients, to ensure its persistence within
the vicinity, and therefore a secure supply of an essential
nutrient (Fig. 5). This hypothesis, which we term Foraging-to-
Farming, is an alternative but complementary scenario to the
BQH. The Foraging-to-Farming model proposes that mutual-
ism can evolve as accidental consequence of metabolic
exchanges, under fluctuating conditions of resource availabil-
ity. The starting point assumes the ability for both dependent
and independent lifestyles, but dependency evolves as a conse-
quence of recurrent ecological associations, which loosen the
pressure to maintain the genetic capacity required for inde-
pendence, thus reinforcing the mutualism. In the evolved metE
mutant of C. reinhardtii (Helliwell et al. 2015) dependence is a
consequence of a transposable element inserting into a single
gene, disrupting its function, but it is possible to envisage
multiple pathways to genetic degradation. Once genes are no
longer essential, the lack of selection pressure means that they
can accumulate deleterious mutations due to drift. Evidence
for this comes from the presence of METE pseudogenes in
several B12-dependent algal species (Helliwell et al. 2011).
Such proposed origins for the evolution of dependency are
not confined to B12, but have been found for other vitamins
(Helliwell et al. 2013). For instance analysis of the genomes of
individual members of the symbiotic microbiome of the tsetse
fly gut has revealed inactivation of genes involved in thiamine
biosynthesis, suggesting symbionts may ‘divide the labour’ of
producing this compound, each contributing intermediates of
different branches of the thiamine pathway, and thus sharing
the cost of maintaining a supply of the vitamin (Belda et al.
2010). Thiamine biosynthesis genes in bacteria are subject to
repression by elevated external levels of thiamine (Winkler
et al. 2002), again providing a possible explanation for ease of
their loss. Identification of pseudogenes of thiamine biosyn-
thetic genes in both the eukaryote host and bacterial
endosymbiont Sodalis glossinidius suggests this metabolic com-
plementation may have occurred recently. Similarly, we pro-
pose our theorem could be applied to production of other
metabolites, such as amino acids and nucleotides. In an inno-
vative study, Campbell et al. (2015) devised a system using
stochastic episomal segregation progressively to introduce
metabolic auxotrophies into a population of S. cerevisiae.
They found that despite a gradual loss of prototrophy for the
metabolites histidine, leucine, uracil and methionine, self-
establishing communities of S. cerevisiae could maintain meta-
bolic efficiency through cooperative metabolite exchange
(Campbell et al. 2015). The observation that cells stopped
making these metabolites in the presence of a ready-available
source from neighbouring cells could have contributed to
the evolution of dependence, thus reinforcing a stable and
obligate association, as would be predicted by the hypothesis.
The similarity between the BQH and the Foraging-to-Farm-
ing hypothesis is that they both lead to accidental depen-
dency, as an ecological cul-de-sac. However, in the BQH this
is driven by an abiotic pressure for streamlined genomes that
leads to loss of function. For the Foraging-to-Farming model,
the evolution of mutualism is driven by the presence of sym-
bionts. There is an argument that the evolution of dependency
is in the interest of the organisms being ‘farmed’, i.e. the pro-
viders of the public good or service. In the example we use,
the farming lifestyle of the alga would guarantee a supply of
fixed carbon for the vitamin B12 producers, and is therefore in
the interest of the bacteria. The function does not have to be
‘leaky’, therefore, but could be selected for. The metabolic
burden of producing B12 could be outweighed by the quanti-
ties of fixed carbon provided, a premise that can be tested
experimentally. Examples of rapid symbiont-driven evolution
abound in insect-endosymbiont literature (Himler et al. 2011;
White 2011) but have never been reported for aquatic
microorganisms. In contrast, the BQH assumes that the help-
ers are left burdened by the public function they deliver,
essentially having not evolved fast enough to lose it, as other
members of the community have. Being the last carriers of
this function, loss of helpers from the community would lead
to the collapse of the whole system. It is logical to hypothesise
from this that their numbers in the community would
Figure 5 Evolution of B12 auxotrophy in algae, an example of the
Foraging-to-Farming hypothesis. Algae with both isoforms of methionine
synthase (METE and METH) are unhindered in the absence of B12
(Helliwell et al. 2011), but remain facultative users of the vitamin if
available, much like foragers that take advantage of sporadic resources in
their environment. If a persistent supply of the vitamin is available for
sufficient time, for example from surrounding loosely associated bacteria,
the METE gene will be repressed and may be lost, so that the alga is now
completely dependent on bacteria for survival. However, fluctuating
environmental conditions may mean that vitamin B12 becomes scarce. In
such circumstances algae that release a carbon source will actively
maintain a viable population of bacteria, and will consequently have a
selective advantage over those that do not. Here, ‘farming’ the bacteria
for the resource becomes an evolutionarily stable strategy, turning a
previously loose interaction into an obligate one.
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
818 E. Kazamia et al. Review and Synthesis
therefore be as low as possible, without the total collapse of
the system, another testable aspect of the model. In both
instances, the net outcome is the partitioning of functions
between members of stable communities, where the commu-
nity metabolome, or ‘meta-metabolome’, is streamlined to
reduce redundancies.
PLACING EVOLUTIONARY THEORIES INTO AN
ECOLOGICAL CONTEXT THAT IS RELEVANT FOR
MICROORGANISMS
Valid evolutionary theories for microbial communities must
be relevant for the physical environment that the microbes
inhabit, while accommodating their unique lifestyles. In the
absence of complex behaviour (as contrasted with macroor-
ganisms), and a reliance on metabolic function as the main
determinant of lifestyles, the boundary between ecology and
evolution is blurred. The classical tenet that stable, repeated
ecological associations lead to evolutionary outcomes simply
may not hold, as evolutionary dynamics, manifested in genetic
differences that result in metabolic dependencies, may precede
and drive ecological associations. The fast growth rates of the
species in question argue further in favour of blurring of the
conventional distinction and directionality between ecology
and evolution.
Moreover, it remains an open question whether physical
associations are a pre-requisite for stable associations and
symbiosis, a tenet of classical terrestrial ecology (Boucher
1985). The work of Decelle et al. (2012) discussed above pre-
sents evidence of an ancient symbiosis, dated to approxi-
mately 92.8 Mya that requires contact but is nonetheless
facultative, with species that are known to engage in
endosymbiosis also abundant as free-living organisms. It has
also been argued that metabolic exchange could not be spe-
cies-specific, since this would require recognition of partners
at a distance, which is not feasible in the marine environment
(Droop 2007). However, developments in physical studies of
the marine environment are redefining the concept of an ‘op-
erational scale’ that is relevant to lifestyles of microbes
(Stocker 2012). The argument in favour of directed interac-
tions is that marine microorganisms are capable of chemo-
taxis, sensing and swimming not only along gradients of
dissolved micronutrients but also towards other species
(Grossart et al. 2001; Fenchel & Finlay 2004; G€ardes et al.
2011), with mean velocities exceeding 60–80 lm s
1 (H€utz
et al. 2011); for comparison swimming speeds for Escherichia
coli have been estimated at 15–30 lm s
1 (Chattopadhyay
et al. 2006). At these speeds, the experienced distance between
microorganisms is reduced, and species-specific interactions
may be possible. Moreover, the discovery of new physical
microstructures in the ocean may play a role in bringing
microbes into closer proximity. The role of ‘marine snow’ in
creating microhabitats is long recognised (Alldredge & Silver
1988; Kiørboe & Jackson 2001), whereas other structures,
such as marine microgels, have been characterised only
recently. In the latter case, the bacterial abundance in local
patches exceeds the seawater average by 104 fold (Verdugo
2012). Finally, it is important to note that a study of interac-
tions on these microscopic scales requires sampling and
preservation of biological material collected from the environ-
ment that is not so destructive or invasive as to eliminate
motility.
CONCLUSION
Overall, the increasing recognition of the importance of the
microbiome as a community of interacting microorganisms
undoubtedly owes a great deal to analysis of metagenomes,
metatranscriptomes and metaproteomes. As well as establish-
ing the identity of the many species present in an environmen-
tal sample, these methods offer the means to determine the
overall metabolic capability of a community. The increasing
depth of coverage is now facilitating integrated systems
approaches that can indicate hitherto unknown interactions.
However, just as interactions between microbes are intricate,
complex, and dynamic, an understanding of microbial ecology
requires a combination of several interdisciplinary and com-
plementary approaches. Defined combinations of known and
well-characterised partners in co-culture in the laboratory
have provided insight into the interactions at the molecular
and cellular levels, the results of which often explain field
observations, as well as indicate potential associations that
are then validated in environmental samples. More impor-
tantly they are providing the basis to develop principles in
ecology that represent the lifestyle and dynamics of microbial
communities.
ACKNOWLEDGEMENTS
EK is grateful for funding from UK Natural Environment
Research Council (NERC) and EU FP7 DEMA project, grant
agreement no. 309086. KEH was supported by the UK
Biotechnology and Biological Sciences Research Council
(BBSRC), grant BB/I013164/1.
AUTHORSHIP
All authors contributed to the ideas in this manuscript and to
its writing.
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Editor, Gregor Fussmann
Manuscript received 17 November 2015
First decision made 3 January 2016
Second decision made 19 March 2016
Manuscript accepted 7 April 2016
© 2016 The Authors Ecology Letters published by CNRS and John Wiley & Sons Ltd.
822 E. Kazamia et al. Review and Synthesis