critical review Assessment criteria include, paper format, content literature cited and article choice. In addition to the three articles used for analysis

  

Assessment criteria include, paper format, content literature cited and article choice. In addition to the three articles used for analysis, supporting references should also be used. A minimum of one unique supporting article is required in the Introduction and Conclusion sections. A student example paper has been uploaded to Blackboard. This paper is well-done and hits almost all the “Meets expectations” criteria in the rubric.

Summary sums up the strengths and weaknesses of each article; compares and contrasts articles to one another summary lacks some details, misses a strength/weakness of one of the articles; occasionally compares and contrasts but mainly lists each articles strengths and weakness separately summary lacks detail, includes either strengths or weaknesses; fails to compare and contrasts articles to one another

Significance establishes practical and theoretical significance of body of work; has your chosen article been cited by others; did your articles spark other researches hypotheses or questions; are there any practical applications; implication (social, political, technological, medical) to the research; cites at least one other supporting reference (unique from introduction) logic not clear to the theoretical significance of the body of work; not thorough in establishing its significance; cites at least one other supporting reference (unique from introduction) no connection to theoretical significance of body of work; fails to cite at least one supporting reference Literature cited Format one journal format chosen and used throughout in bibliography and in-text citations some in-text citations were not in the same format; 1-2 errors in bibliography consistency lacking for in-text citations; bibliography with 3+ formatting errors Subject Chosen articles were all on the same topic; topic was specific enough so that an analysis was possible topics were not consistent or were too broad/general each article was on a separate topic and the topics were without reasonable similarities Citation Each reference was used and cited correctly within the body of the paper; three focal references were analyzed; at least 5 references used references were occasionally cited incorrectly; three focal references were analyzed; 4 total references used two or fewer references were analyzed; no supporting references used Quantity minimum of 5, 1 unique to intro, 1 unique to discussion and 3 critically reviewed missing 1 unique missing 2 unique and/or 1 of critically reviewed. 

Host-Microbe Coevolution: Applying Evidence from Model
Systems to Complex Marine Invertebrate Holobionts

Paul A. O’Brien,a,b,c Nicole S. Webster,b,c,d David J. Miller,e,f David G. Bournea,b,c

aCollege of Science and Engineering, James Cook University, Townsville, QLD, Australia
bAustralian Institute of Marine Science, Townsville, QLD, Australia
cAIMS@JCU, Townsville, QLD, Australia
dAustralian Centre for Ecogenomics, University of Queensland, Brisbane, QLD, Australia
eARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, QLD, Australia
fCentre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, QLD, Australia

ABSTRACT Marine invertebrates often host diverse microbial communities, making
it difficult to identify important symbionts and to understand how these communi-
ties are structured. This complexity has also made it challenging to assign microbial
functions and to unravel the myriad of interactions among the microbiota. Here we
propose to address these issues by applying evidence from model systems of host-
microbe coevolution to complex marine invertebrate microbiomes. Coevolution is
the reciprocal adaptation of one lineage in response to another and can occur
through the interaction of a host and its beneficial symbiont. A classic indicator of
coevolution is codivergence of host and microbe, and evidence of this is found in
both corals and sponges. Metabolic collaboration between host and microbe is of-
ten linked to codivergence and appears likely in complex holobionts, where micro-
bial symbionts can interact with host cells through production and degradation of
metabolic compounds. Neutral models are also useful to distinguish selected mi-
crobes against a background population consisting predominately of random associ-
ates. Enhanced understanding of the interactions between marine invertebrates and
their microbial communities is urgently required as coral reefs face unprecedented
local and global pressures and as active restoration approaches, including manipula-
tion of the microbiome, are proposed to improve the health and tolerance of reef
species. On the basis of a detailed review of the literature, we propose three re-
search criteria for examining coevolution in marine invertebrates: (i) identifying sto-
chastic and deterministic components of the microbiome, (ii) assessing codivergence
of host and microbe, and (iii) confirming the intimate association based on shared
metabolic function.

KEYWORDS codivergence, coevolution, marine invertebrates, microbiome,
phylosymbiosis

Coevolution theory dates back to the 19th century (box 1), and coevolution iscurrently referred to as the reciprocal evolution of one lineage in response to
another (1). This definition encompasses a broad range of interactions such as predator-
prey, host-symbiont, and host-parasite interactions or interactions among the members
of a community of organisms such as a host and its associated microbiome (1, 2). In the
case of host-microbe associations, this has produced some of the most remarkable
evolutionary outcomes that have shaped life on Earth, such as the eukaryotic cell,
multicellularity, and the development of organ systems (3, 4). It is now recognized that
microbial associations with a multicellular host represent the rule rather than the

Citation O’Brien PA, Webster NS, Miller DJ,
Bourne DG. 2019. Host-microbe coevolution:
applying evidence from model systems to
complex marine invertebrate holobionts. mBio
10:e02241-18. https://doi.org/10.1128/mBio
.02241-18.

Editor Danielle A. Garsin, University of Texas
Health Science Center at Houston

Copyright © 2019 O’Brien et al. This is an
open-access article distributed under the terms
of the Creative Commons Attribution 4.0
International license.

Address correspondence to David G. Bourne,
david.bourne@jcu.edu.au.

Published 5 February 2019

MINIREVIEW
Host-Microbe Biology

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exception (4), but in complex associations of that kind, the extent to which coevolution
operates is often unclear.

BOX 1: A BRIEF HISTORY OF COEVOLUTION
Charles Darwin once explained the sudden and rapid diversification of flowering

plants as an “abominable mystery,” since it could not be explained by traditional
views of evolution alone (5). While his correspondent Gaston de Saporta speculated
that a biological interaction between flowering plants and insects might be the
cause of the phenomenon, it was not until nearly 100 years later that the concept of
coevolution developed. In a pioneering study, Ehrlich and Raven (6) observed that
related groups of butterflies were feeding on related groups of plants and specu-
lated this was due to a process for which they coined the name “coevolution.” Using
butterflies, they argued that plants had evolved mechanisms to overcome predation
from herbivores, which in turn had evolved new ways to prey on plants. Decades on,
the introduction of phylogenetics has shown that plants evolved in the absence of
butterflies, which colonized the diverse group of plants after their chemical defenses
were already in place (7). Nevertheless, the theory of coevolution was endorsed, and
two important points came to light. First, care must be taken when inferring
coevolution from seemingly parallel lines of evolution, and where possible, diver-
gence times and common ancestry should be included. Second, coevolution can
occur between communities of organisms (“guild” coevolution), as observed in the
case of flowering plants, where predation and pollination from a wide variety of
insects likely influenced the diversification of angiosperms (8).

Since coevolution can occur across multiple levels of interactions, multiple theories
have also developed. The Red Queen theory is based on the concept of antagonistic
coevolution and assumes that an adaptation that increases the fitness of one species
will come at the cost to the fitness of another (9). This type of coevolution has been
most pronounced in host-parasite interactions, where the antagonistic interactions are
closely coupled (10). However, coevolutionary patterns may also arise in the case of
mutualistic symbioses, which require reciprocal adaptations to the benefit of each
partner (11). Mutualistic coevolution is associated with a number of key traits that are
discussed further in this review, such as obligate symbiosis, vertical inheritance, and
metabolic collaboration. Third, coevolution has also recently been placed in context of
the hologenome theory (12), which suggests that the holobiont can act as a unit of
selection (but not necessarily as the primary unit) since the combined genomes
influence the host phenotype on which selection may operate (13, 14). However,
hologenome theory also acknowledges that selection acts on each component of the
holobiont individually as well as in combination with other components (including the
host). Thus, the entity that is the hologenome may be formed, in part, through
coevolution of interacting holobiont compartments, in addition to neutral processes
(12).

Given the ubiquitous nature of host-microbe associations and the huge metabolic
potential that microorganisms represent, it is not surprising that evidence of host-
microbe coevolution is emerging. Model representatives of both simple and complex
associations are being used to study coevolution, allowing researchers to look for
specific traits, signals, and patterns (1, 15). A well-known model system is the pea-aphid
and its endosymbiotic bacteria in the genus Buchnera. This insect has evolved special-
ized cells known as bacteriocytes to host its endosymbionts, which in turn synthesize
and translocate amino acids that are missing from the diet of the pea aphids (16).
Amino acid synthesis occurs through intimate cooperation between host and symbiont,
with some pathways missing from the host and some from the symbiont, such that the
relationship is obligate to the extent that the one organism cannot survive without the
other (17). The human gut microbiome has been extensively studied in complex
systems and has been shown to be intimately associated with human health. Gut

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microbes have been shown to be linked with human behavior and development
through metabolic processes, such as microbial regulation of the essential amino acid
tryptophan (18, 19). The human microbiome contains around 150-fold more nonre-
dundant genes than the human genome (20), and the metabolic capacity of microbes
residing in the intestine is believed to have been a driving evolutionary force in the
host-microbe coevolution of humans (2). In these examples, as well as many others
(21–23), both host and symbiont evolved to maintain and facilitate the symbiosis.
Furthermore, phylogenies of host and symbiont in these systems are often mirrored,
indicating that host and symbiont are diverging in parallel (16, 24, 25), a phenomenon
known as codivergence (26).

In the marine environment, invertebrates can host microbial communities as simple
and stable as that of the pea aphid or as complex and dynamic as that of the human
gut (Fig. 1). The Hawaiian bobtail squid, for example, maintains an exclusive symbiosis
with a single bacterial symbiont which it hosts within a specialized light organ (27). On
the other hand, corals host enormously diverse microbial communities, comprising
thousands of species-level operational taxonomic units (OTUs), which are often influ-
enced by season, location, host health, and host genotype (28–31). Marine sponges also
host complex microbial communities with diversity comparable to that of corals (32)
but with associations that are generally far more stable in space and time (33).
Less-diverse microbial communities are found in the sea anemone Aiptasia, where the
number of OTUs is generally in the low hundreds (34). Due to the close taxonomic
relationship of Aiptasia with coral and its comparatively simple microbial community, it
has been proposed as a model organism for studying coral microbiology and symbiosis
(34). Some marine invertebrates also include species along a continuum of microbial
diversities. Ascidians, for example, have been shown to host fewer than 10 (Polycarpa
aurata) or close to 500 (Didemnum sp.) microbial OTUs within their inner tunic (35).
Furthermore, species with low microbial diversity such as P. aurata can exhibit high
intraspecific variation, with as few as 8% of OTUs shared among individuals of the same
species (35). Taken together, the data from those studies highlight the vast spectrum
of associations that marine invertebrates form with microbial communities in terms of
diversity, composition, and stability (Fig. 1).

While previous research has provided a good understanding of the composition of
marine invertebrate microbiomes, our understanding of how the microbiome interacts
with the host, and of the potential to coevolve, is far more limited. Moreover, the

FIG 1 Spectrum of microbial diversity associated with different compartments of marine invertebrates. Microbial associations may involve a single symbiont
in a specialized organ or over 1,000 operational taxonomic units (OTUs) associated with tissues. The levels of OTUs reported in the figure represent the highest
recorded in the referenced study for that species. Reported levels of diversity may differ significantly within the same species across different studies.

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increasing number of studies generating tremendous volumes of host-associated
microbiome sequence data requires theoretical development to interpret these rela-
tionships. Coevolved microbial symbionts are presumed to be intimately linked with
host fitness and metabolism (36); therefore, understanding these relationships in
marine invertebrates will have direct implications for health and disease processes in
these animals. Three research criteria arise for examining coevolution in marine inver-
tebrates: (i) identifying stochastic and deterministic microbial components of the
microbiome, (ii) assessing codivergence of host and microbe, and (iii) confirming an
intimate association between host and microbe related to shared metabolic function
(metabolic collaboration). While each of these criteria may be fulfilled without the
involvement of coevolution (26, 37, 38), evidence of their existence in combination
provides a strong basis for establishing coevolution patterns (Fig. 2). This review
positions these three criteria in coevolution as representing a complementary approach
to the study of complex marine invertebrate microbiomes by drawing from examples
of model systems. Focussing on keystone coral reef invertebrates, this review also
evaluates the current evidence for each criterion. Finally, while parasites and pathogens
also contribute to host coevolution, the focus of this review is mutualistic symbionts;
thus, pathogens and parasitism are not discussed.

BOX 2: GLOSSARY
(i) Codivergence. Two organisms which speciate or diverge in parallel as illus-

trated by topological congruency of phylogenetic trees.
(ii) Coevolution. Reciprocal adaptation of one (or more) lineage(s) in response to

another (or others).
(iii) Holobiont. A host organism and its associated microbial community.
(iv) Hologenome. The collective genomes of a host and its associated microbial

community, which may act as a unit of selection or at discrete levels.
(v) Metabolic collaboration. Two or more oganisms that are linked through

metabolic interactions, generally to the benefit of one another.
(vi) Metagenome. The collective microbial genes recovered from an environmen-

tal sample, usually predominantly prokaryotic.
(vii) Metatranscriptomics. Quantification of the total microbial mRNA in a sample

as an indication of gene expression and active microbial functions.
(viii) Microbiome. The total genetic make-up of a microbial community associated

with a habitat.
(ix) Microbiota. The community of microorganisms residing in a particular habitat,

usually a host organism.
(x) Phylosymbiosis. The rentention of a host phylogenetic signal within its

associated microbial community.
(xi) Virome. The total viral genetic content recovered from an environmental

sample.

UNTANGLING PATTERNS OF HOST-MICROBE COEVOLUTION IN A WEB OF
MICROBES

(i) Phylosymbiosis and neutral theory—identifying stochastic and determinis-
tic components of the microbiome. Host-microbe coevolution may occur to some
degree at the level of the hologenome, i.e., reciprocal evolution of the host genome
and microbiome (12). Therefore, it is necessary to understand microbial community
structure and population dynamics within the host environment. This may illustrate (i)
that the microbiome associated with a host is structured through phylogenetically
related host traits and may therefore retain a host phylogenetic signal (phylosymbiosis)
and (ii) that certain microbes deviate from the expected patterns of neutral population
dynamics, i.e., stochastic births and deaths and immigration. It is likely that phylosym-
biosis and neutral population dynamics are linked; therefore, their potential to con-
tribute to coevolution is discussed together.

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Homocysteine + Serine
(host diet & metabolism)

Cystathionine B-synthase
(symbiont enzyme)

Cystathionine

Cystathionine y-lyase
(host enzyme)

Cysteine

S-H
CH2

C COOH H2N
H

Bacteria spp. 1

Host spp. A

d)

Host phylogeny Microbial dendrogram
Host species

A

B

C

D

a)

b)

Host phylogeny Microbial phylogeny

Bacteria spp. 1

A

B

C

D

Relative abundance of
microbes in host sample

Fr
eq

ue
nc

y
of

m
ic

ro
be

s
in

h
os

t Bacteria spp. 1

Bacteria spp.2
Low High

0

1

c)

FIG 2 Hypothetical scenario addressing three criteria for host-microbe coevolution in species A to D. (a) Phylosymbiosis
shown through hierarchical clustering of the microbial community, resulting in a microbial dendrogram which mirrors host
phylogeny. (b) Neutral model showing the expected occurrence of microbes based on neutral population dynamics (blue
line). As the relative abundance increases, so too does the occurrence in host samples. The members of bacterial species
group 1 (Bacteria spp. 1) are therefore more abundant than would be expected by chance and may indicate active selection,
while the members of Bacteria spp. 2 are less abundant. (c) Codivergence of the members of Bacteria spp. 1 with their hosts.
The members of Bacteria spp. 1 are found within the microbial community of each host species and appear to be actively
selected for. Their phylogeny indicates a host split at the strain level followed by diversification within each host species.
Congruence between host and microbial lineages suggests important host-microbe interactions and warrants further
investigation. (d) Metabolic collaboration between the members of Host spp. A and those of Bacteria spp. 1. Fluorescence
in-situ hybridization (FISH) confirms that the members of Bacteria spp. 1 are located within bacteriocyte cells in the tissues
of Host spp. A. Genome and transcriptome data for each species suggest that the amino acid cysteine is produced by the
activity of a metabolic pathway shared between host and microbe. In corals of the genus Acropora, for example, the
genome is incomplete with respect to biosynthesis of cysteine and represents a potential pathway for collaborations of host
and microbe (101). Hypothetically, the amino acids homocysteine and serine (potentially sourced from host diet and
metabolism) are combined to form cystathionine through the enzyme cystathionine V synthase (provided by the host’s
endosymbiont). The host enzyme cystathionine �-lyase then breaks down cystathionine to form cysteine.

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The term “phylosymbiosis” is not intended to imply coevolution (12, 38); however,
coevolution of a host and microbiome may reinforce patterns of phylosymbiosis. There
are many host traits that correlate with host phylogeny, some of which can act as
environmental filters, preventing the establishment of microbes in the host environ-
ment. Thus, neutral population dynamics, with host traits acting as an ecological filter
to microbial immigration, may be sufficient to result in phylosymbiotic patterns (39, 40).
However, host traits are not static; thus, the evolution of these microbial niches may
further drive the radiation of the microbes that reside within them. In turn, the
continuous colonization over many generations of a microbial community likely adds
to the selective pressure on host traits. Therefore, ecological filtering of microbes
through host traits and coevolution of a host and microbiome need not be mutually
exclusive in the appearance of phylosymbiosis (39). Moreover, assessing patterns of
phylosymbiosis and neutral population dynamics also allows the detection of microbes
that deviate from these patterns and may identify important microbial species that are
actively selected for (or against) by the host. In this context, neutral models can
simulate expected microbial abundance, allowing easier detection of microbes that do
not fit these patterns (41). This reasoning justifies consideration of phylosymbiosis and
microbial population dynamics in assessing coevolution in complex holobionts.

Patterns of phylosymbiosis are frequently detected in complex holobionts. One
particular study tested for phylosymbiosis across 24 species of terrestrial animals from
4 groups that included Peromyscus deer mice, Drosophila flies, mosquitos, and Nasonia
wasps and an additional data set of 7 hominid species (42). Since these animals (with
the exception of hominids) could be reared under controlled laboratory conditions,
environmental influences could be eliminated, leaving the host as the sole factor
influencing the microbial community. Under these conditions, phylosymbiotic patterns
were clearly observed for all five groups, with phylogenetically related taxa sharing
similar microbial communities and microbial dendrograms mirroring host phylogenies.
Similar patterns of phylosymbiosis have been observed in a growing number of
terrestrial systems, including all five gut regions in rodents (43), the skin of ungulates
(44), the distal gut in hominids (45), and roots of multiple plant phyla (46), providing
evidence that such patterns are common among host-associated microbiomes.

In the marine environment, two major studies, one involving 236 colonies across 32
genera of scleractinian coral collected from the east and west coasts of Australia (47)
and the other involving 804 samples of 81 sponge species collected from the Atlantic
Ocean, Pacific Ocean, and Indian Ocean and the Mediterranean Sea and Red Sea (32),
have provided the most convincing examples of phylosymbiosis. Both studies found a
significant evolutionary signal of the host with respect to microbial diversity and
composition. Specifically, mantel tests were used to delineate the finding that closely
related corals and sponges hosted more extensively similar microbial communities in
terms of composition than would be expected by chance. In the case of corals, the
similarity was seen in the skeleton and, to a lesser extent, in the tissue microbiome,
while the mucus microbiome was more highly influenced by the surrounding environ-
ment (47). However, both studies found that host species was the strongest factor in
explaining dissimilarity among microbial communities. Additional studies on both cold
water and tropical sponges have found similar phylogenetic patterns within the
microbiome of the host species (48, 49). Together, these results suggest that host
phylogeny (or associated traits) has a significant role in structuring associated microbial
communities, although there are additional factors related to host identity (and unre-
lated to phylogeny) that also likely play a major role.

Most studies to date have focused on the microbes that adhere to these patterns of
phylosymbiosis, though more-useful information arguably could be determined from
the microbes that do not. Since phylosymbiosis is a pattern that shows correlations
between microbiome dissimilarity and host phylogeny, it does not indicate active
microbial selection or cospeciation (38), and the species that deviate from these
patterns would be interesting targets for studies of codivergence and metabolic
collaboration (see below). Neutral models have been applied to three species of

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sponges, a jellyfish, and a sea anemone, and while neutral models have been shown to
fit well to the expectation of microbial abundance in sponges (which also show
phylosymbiosis), jellyfish and sea anemone microbiomes were found to be associated
with a higher level of nonneutrality (40). Potential reasons for nonneutrality include the
presence of a more sophisticated immune system in cnidarians that provides active
selection on certain microbial taxa and that the microbiomes in such cases are more
transient or a combination of the two. In summary, neutral population dynamics filtered
through phylogenetically related host traits likely result in, or at least contribute to, the
observed patterns of phylosymbiosis. This does not necessarily mean that the pattern
is unimportant or is not contributing to coevolution at the hologenome level, and it
may be that the communities of microbes that follow these patterns are responsible for
broad ecological functions (50). On the other hand, microbes that deviate from these
patterns may be responsible for more-specific functions and are of high interest to
those trying to identify symbionts and coevolution at the microbial species or strain
level.

(ii) Codivergence—microbial phylogeny and host phylogeny are congruent.
The second criterion in assessing host-microbe coevolution is that of whether individ-
ual microbial lineages and their hosts have matching phylogenies (22, 24, 51). Codi-
vergence implies a tightly coupled, long-term interaction between two species and can
potentially identify beneficial symbionts (or parasites) that have coevolved with the
host (26). However, it is also important that codivergence can arise due to processes
other than coevolution, such as one species adaptively tracking another, which would
imply that the evolution is not reciprocal, or two species responding independently to
the same speciation event or environmental stress (37). In known cases of coevolution,
phylogenies of hosts and their microbial symbionts are congruent (16, 51, 52). However,
in complex and uncharacterized systems, this strategy can be reversed to identify
potential symbionts. Therefore, the main value of investigating codivergence in com-
p

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