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\begin{document}

\title{Codominance of two symbiont genera within the same coral host is
associated with elevated symbiont productivity and lower host
susceptibility to thermal stress}



\author[1]{Evelyn Abbott}%
\author[2]{Groves Dixon}%
\author[1]{Mikhail Matz}%
\affil[1]{University of Texas at Austin}%
\affil[2]{University of Texas}%


\vspace{-1em}



  
  \date{May 24, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
As sea surface temperature increases, many coral species that used to
harbor symbionts of the genus Cladocopium have become colonized with the
thermally tolerant genus, Durusdinium. Here, we asked how symbionts of
one genus react to the presence of another symbiont genus within the
same coral host, and what effect this has on the host. We used
previously published data from Acropora hyacinthus corals hosting
Cladocopium and/or Durusdinium symbionts and looked at gene expression
in all three symbiotic partners depending on the relative proportions of
symbiont genera within the host. We find that both Cladocopium and
Durusdinium change their expression most when their proportions are
nearly equal (the state that we call ``codominance''): both genera
elevate expression of photosynthesis and ribosomal genes, suggesting
increase in photosynthesis and growth (i.e. higher productivity). At the
same time, the coral host also elevates production of ribosomes
suggesting faster cellular growth, and, when heated, shows less
pronounced stress response. These results can be explained in two ways.
One explanation is that increased competition between symbionts
heightens their productivity, which benefits the host, making it more
resilient to stress. Alternatively, the symbionts' elevated productivity
might be the consequence of the host being particularly healthy. Under
this explanation, rapid growth of the healthy host creates new space,
lowering the symbionts' competition and allowing for codominance. The
latter explanation is supported by the fact that codominance is
associated with lower symbiont densities. Irrespective of the causation,
the presence of mixed symbiont communities could potentially be used as
an instant indicator of coral well-being, which would be a useful tool
for coral conservation and restoration.%
\end{abstract}%



\sloppy


Codominance of two symbiont genera within the same coral host is
associated with elevated symbiont productivity and lower host
susceptibility to thermal stress

Evelyn Abbott, Groves Dixon, Mikhail Matz

Department of Integrative Biology, University of Texas at Austin,
Austin, TX, USA

\textbf{Correspondence}

Evelyn Abbott, Department of Integrative Biology, University of Texas at
Austin, Austin, TX, USA

Email: evelyn.abbott@utexas.edu

Abstract

In recent years, as sea surface temperature increases, many coral
species that used to harbor symbionts of the genus
\emph{Cladocopium}have become colonized with the thermally tolerant
genus,\emph{Durusdinium.} Here, we asked how the symbionts of one genus
react to the presence of another symbiont genus within the same coral
host, and what effect this interaction has on the host. We used
previously published transcriptomic data from \emph{Acropora hyacinthus}
corals hosting \emph{Cladocopium} and/or \emph{Durusdinium} symbionts
and looked at gene expression in all three symbiotic partners depending
on the relative proportion of the two symbiont genera within the same
host. We find that both \emph{Cladocopium} and \emph{Durusdinium} change
their expression the most when their proportions within the host are
nearly equal (the state that we call ``codominance''): both genera
elevate expression of photosynthesis and ribosomal genes, suggesting
increase in photosynthesis and growth (i.e. higher productivity). At the
same time, the coral host also elevates production of ribosomes
suggesting faster cellular growth, and, when heated, shows less
pronounced stress response. These results can be explained in two
alternative ways. One explanation is that increased competition between
codominant symbionts switches them to the higher productivity mode,
which benefits the host, making it more resilient to stress.
Alternatively, the symbionts' elevated productivity might be not the
cause but the consequence of the host being particularly healthy. Under
this explanation, rapid growth of the healthy host creates new space,
lowering the symbionts' competition and thus promoting their growth,
which allows for codominance to happen where one genus would otherwise
outcompete another. The latter explanation is supported by the fact that
codominance is associated with lower symbiont densities, assessed as
relative proportions of symbiont reads in the data. Irrespective of the
causation direction, the presence of mixed symbiont communities could
potentially be used as an instant indicator of coral well-being, which
would be a useful tool for coral conservation and restoration.

Introduction

Reef building corals get up to 90\% of their energetic requirements for
growth and calcification through symbiosis with dinoflagellate algae of
the family Symbiodiniaceae (\emph{Falkowski et al. 1984}). Coral
bleaching is the breakdown of this symbiosis, and often occurs when
water temperatures exceed a certain threshold. This heat tolerance
threshold varies more depending on the genus of symbiont than on the
host genetics (\emph{Fuller et al., 2020}). These symbionts, formerly
delineated as clades A-I, have now been divided into six genera
(\emph{Lajeunesse et al.,} \emph{2018}). In the Great Barrier Reef, the
majority of scleractinian corals of the genus \emph{Acropora} have
historically engaged in symbiosis with symbionts of the genus
\emph{Cladocopium} . However, as ocean temperatures continue to rise and
bleaching events become more frequent, these corals are becoming
colonized by relatively opportunistic, thermotolerant symbionts of the
genus \emph{Durusdinium} .

Symbionts are known to have diverse effects on their coral hosts.
Although \emph{Durusdinium} symbionts confer bleaching resistance, it
comes at the cost of reduced growth (\emph{Pettay et al., 2015}). Other
physiological trade-offs have been observed, including reduced
fecundity, reduced carbon acquisition (\emph{Matthews et al., 2018}),
reduced calcification (\emph{Pettay et al., 2015}), and disease
susceptibility (\emph{Shore-Maggio et al., 2018}). Furthermore, it was
found that in the Caribbean coral \emph{Montastraea cavernosa,
Durusdinium} dominance is associated with differential expression of
stress-related genes in the host: having\emph{Durusdinium} appears to
stress the host (\emph{Cunning et al., 2020}).

Most corals only associate with a single symbiont type at a time, with
background levels of other symbionts present in host tissues
(\emph{Baker, 2003}). In the case of acroporid corals from the Great
Barrier Reef, hosts may harbor \emph{Cladocopium} symbionts with
background levels of\emph{Durusdiunium} , or the reverse, although some
colonies have been shown to have a more even mixture (\emph{Ulstrup et
al., 2003}). Whether these two symbiont genera interact in the host
tissues is presently unknown. Furthermore, as colonization of acroporid
corals by \emph{Durusdinium} becomes more common, it is unknown how
harboring two distinct symbiont genera at once impacts both the
symbionts and the host.

In this study, we analysed existing gene expression data from two
studies with a combined total of 181 \emph{Acropora hyacinthus} samples
(\emph{Rose et al.,} \emph{2015};\emph{Barshis et al.,} \emph{2013}).
These indo-pacific corals had entirely\emph{Cladocopium,} entirely
\emph{Durusdinium} , or a mixture of both symbionts. We asked how
symbionts respond to symbionts of a different genus within the same
host. Initially, we predicted that symbionts would have the most
distinct expression patterns depending on whether they are the majority
or the minority within the host. We also anticipated that the stress of
competition would cause the symbionts to become more virulent towards
the host, prioritizing their own proliferation by sequestering more
nutrients and translocating fewer photosynthates to the host
(\emph{Lesser et al., 2013};\emph{Baker et al., 2018};\emph{Morris et
al., 2019}). Therefore, we expected that corals hosting mixed symbiont
populations would be more susceptible to heat stress and might show
elevated expression of generalized stress response genes (\emph{Dixon et
al.,} \emph{2020}) even under non-stressful temperature. We were
surprised to find no support for any of these predictions.

Materials and Methods

\emph{Data sources}

We chose two studies (\emph{Rose et al.,} \emph{2015};\emph{Barshis et
al.,} \emph{2013}) for this analysis by searching for the genus,
\emph{Acropora,} in the NCBI SRA database, comprising 181 coral samples
sequenced with RNA-seq method. These studies were selected because they
involved similar heat stress experiments on \emph{Acropora hyacinthus}
corals. Furthermore, these corals were all isolated from back reef tide
pools in Ofu, American Samoa. The SRA metadata tables for each study are
shown in supplemental table S1.

\emph{Sequence data processing and symbiont genus determination}

Detailed descriptions of the data processing pipeline are on Github
(https://github.com/evelynabbott/codominant\_symbiosis.git). The Fastq
files from both studies were downloaded using the SRA toolkit. Adapter
trimming was done on paired-end mode using cutadapt, with a minimum
length of 20 bp and a PHRED quality cutoff set to 20. FASTQC (Andrews,
2010) was used to assess the quality of a subset of 10,000 reads before
and after trimming. Reads were then mapped to a combined reference
comprising \emph{Cladocopium} transcriptome\emph{,
Durusdinium}transcriptome (\emph{Ladner et al., 2012}), and
\emph{Acropora millepora} genome (\emph{Fuller et al., 2018}) using
bowtie2. The reads in the resulting sam files were then split into three
separate sam files, one for each organism. PCR duplicates were removed
after alignment using MarkDuplicates from the Picard Toolkit (Broad
Institute, 2019). Samtools (\emph{Li et al., 2009}) was used to sort and
convert from sam files to bam files. FeatureCounts (\emph{Liao, Smyth,
\& Shi, 2014}) was used to count reads mapping to annotated gene
boundaries.

\emph{Differential gene expression analysis}

We used DESeq2 to identify genes which were differentially expressed due
to symbiont codominance and heat treatment. This analysis was performed
on \emph{Cladocopium} symbionts, \emph{Durusdinium} symbionts, and the
coral host. Genes with a mean count less than three were excluded from
this analysis, leaving a total of 19,580 genes for the coral host,
15,332 for \emph{Cladocopium} , and exactly 15,000 for\emph{Durusdinium}
.

\emph{Weighted gene coexpression network analysis}

This analysis (WGCNA) (\emph{Langfelder \& Hovarth, 2008}) was used to
identify groups of co-regulated genes in both symbiont genera, to
explore major patterns of gene expression variation in an unsupervised
way. The input for this analysis were the matrices of normalized
variance stabilized counts obtained with R function DESeq2::vst(), from
which the variation due to study and to the logarithm of total read
count was removed using the R function limma::removeBatchEfect. For
\emph{Cladocopium} , we ran WGCNA with a soft threshold power of 10, a
minimum module size of 30, and a module merging threshold of 0.4. For
\emph{Durusdinium} , we ran WGCNA with a soft threshold power of 12, a
minimum module size of 30, and a module merging threshold of 0.4.

\emph{Functional enrichment tests}

We used a Gene Ontology (GO) enrichment analysis that utilizes the
Mann-Whitney \emph{U} (MWU) test (\emph{Wright et al., 2017}) to
identify significant functional differences among up and down-regulated
genes associated with the codominant state. We used -log10 transformed
\emph{p-} values output from DESeq2, multiplied by -1 when the gene was
down-regulated, as input for this analysis, following (\emph{Dixon et
al., 2015}). This test compares transformed p-value ranks among genes to
determine whether the ranks of genes in a GO category diverge
significantly from ranks of other genes. We also used a Eukaryotic
Orthologous Group (KOG) MWU test (package KOGMWU in R,\emph{Dixon et
al., 2015}) to broadly determine coral host gene expression response to
codominant symbionts. For this analysis, the data from this study was
compared to the generalized stress response (GSR) profile from
(\emph{Dixon et al., 2020}) that represents the response of
\emph{Acropora} sp. to any kind of high-intensity stress.

Results

\emph{WGCNA}

We were firstly interested in which factors impacted the gene expression
of \emph{Cladocopium} and \emph{Durusdinium} symbionts the most. To find
this out we identified groups of genes (``modules'') that were
co-regulated across samples using weighted gene co-expression network
analysis (WGCNA). These modules, which WGCNA identifies in an
unsupervised fashion without knowledge of the experimental design, are
then examined for correlation with known traits or experimental
treatments. In this way, it is possible to identify the largest and most
responsive groups of genes and then investigate what biological effects
they track. By examining the modules' behavior across samples (Fig. 1)
we observed that the greatest gene expression difference in the
symbionts was not between ``genus-background'' and ``genus-dominant''
states, as we initially expected. Instead, in both genera the most
distinct state was when the proportions of the two symbionts were near
equal within the host (Fig. 1), the state that we here term
``codominance.''

For \emph{Cladocopium,} WGCNA identified nine modules of co-regulated
genes. Two of these modules, containing 1233 and 131 genes respectively,
were significantly correlated with codominance (r = 0.43, p \textless{}
4e-09 \& r = 0.76, p \textless{} 2e-33). Additionally, the module
containing 131 genes was negatively correlated with the dominance
of\emph{Cladocopium} (r = -0.26, p \textless{} 5e-04).
For\emph{Durusdinium} , WGCNA identified 7 modules of co-regulated
genes. Two of these modules, containing 815 and 81 genes respectively,
were significantly correlated with codominance (r = 0.71, p \textless{}
9e-25 \& r = 0.3, p \textless{} 8e-05). One module, containing 5671
genes was negatively correlated with codominance (r = -0.28, p
\textless{} 2e-04). Notably, neither symbiont had modules significantly
associated with exposure to elevated temperature.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1} Correlation of WGCNA modules with symbiont
codominance. Samples are represented across the x axis, in order from
least to most \emph{Cladocopium.} The points in the top panel show the
log ratio of C:D counts for each sample. The heatmap rows represent
WGCNA modules, with \emph{Cladocopium} modules on the top
and\emph{Durusdinium} modules on the bottom; color representing the
module's eigengene expression (the left color scale). The numbers listed
to the left of the heatmaps represent the number of genes in the module.
The heatmaps on the right show Pearson correlations for each module with
codominance (how near is the C:D ratio to 50:50, ``codom'') and with the
C:D ratio itself. Top number is the correlation coefficient and bottom
number is p-value (only shown for significant correlations).

\emph{DESeq2 analysis}

We used DESeq2 modeling to measure the gene expression responses to
codominance in each genus. Codominance was coded as a quantitative
trait: log\textsubscript{10}(C:D ratio) multiplied by -1 when it was
\textgreater{}0. This measure reaches its maximum (zero) when symbionts
are equally represented and diminishes when their relative proportions
become unequal. For \emph{Cladocopium,} out of a total of 15,332 genes
assayed, 1,930 were upregulated (false discovery rate, FDR = 0.1) and 89
were downregulated (FDR = 0.1, Fig. S1A). For \emph{Durusdinium} , out
of a total of 15,000 genes, 2,629 were upregulated (FDR = 0.1) and 2,868
were downregulated (FDR = 0.1, Fig. S1B). For the coral host, out of a
total of 19,580 genes, 138 were upregulated (FDR = 0.1) and 83 were
downregulated (FDR = 0.1, Fig. S1C).

We also evaluated gene expression response to heat treatment, and
codominance:heat interaction (i.e., additional response to heat
treatment under codominance), for all three partners. Response to heat
was virtually absent in both symbiont genera: for \emph{Cladocopium,}out
of a total of 15,332 genes, 0 were upregulated and 1 was downregulated
(FDR = 0.1, Fig. S2A), and for \emph{Durusdinium} , out of a total of
15,000 genes, 1 was upregulated (FDR = 0.1) and 2 were downregulated
(FDR = 0.1, Fig. S2B). The coral host, however, did show a pronounced
response to heat treatment: out of a total of 19,580 genes, 1,399 were
upregulated (FDR = 0.1) and 610 were downregulated (FDR = 0.1, Fig.
S2C).

\emph{Gene Ontology Analysis}

To ascertain the functions of differentially expressed genes of
symbionts in the codominant state, we used a Gene Ontology (GO)
enrichment analysis that utilizes the Mann-Whitney \emph{U} test
(\emph{Wright et al., 2017}). For \emph{Cladocopium} symbionts, there
were 2,019 differentially expressed genes (DEGs), with an FDR cut-off of
10\%. At the GO level, the most notable signal pertained to ribosomes
and photosynthesis. There were nine cellular component GO terms that
were significantly (adjusted p \textless{} 0.001) enriched by
upregulated genes. Of these, six were related to ribosome, and three to
chloroplast (Fig. 2A).

We repeated the same analysis for \emph{Durusdinium} symbionts,
identifying 5,497 DEGs at the 10\% FDR level. Like \emph{Cladocopium} ,
the \emph{Durusdinium} GO analysis results in multiple terms related to
ribosomes and photosynthesis. There were ten cellular component terms
that were significantly (adjusted p \textless{} 0.001) enriched by
upregulated genes. Of these, seven were related to ribosomes and two to
chloroplasts (Fig. 2B).

Lastly, we did this analysis for the coral host, identifying 7,799 DEGs
at the 10\% FDR level. Like the symbionts, there were multiple GO terms
related to ribosomes. There were four cellular component terms that were
significantly (adjusted p \textless{} 0.001) enriched by upregulated
genes. Of these, three were related to ribosomes (Fig. 2C).
Additionally, there were 11 GO terms significantly (adjusted p
\textless{} 0.005) enriched for downregulated genes. Of these, six were
related to neurons.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2} Gene ontology terms (cellular component) significantly
enriched with up-regulated (red) or down-regulated (blue) genes based on
Mann-Whitney \emph{U} test for (A) \emph{Cladocopium} ,
(B)\emph{Durusdinium} , and (C) the coral host. Font indicates
the\emph{p} -value) adjusted for multiple testing over GO categories
(see legend under panel A). Dendrograms represent hierarchical
clustering of GO categories based on sharing of the genes among them.
The fraction shows the number of genes with unadjusted \emph{p}
\textless{}0.05 in the DESeq2 model (numerator) relative to the total
number of genes annotated with a given term (denominator).

\emph{Comparison of GO term delta-ranks between symbiont genera}

To compare the functional signals of\emph{Cladocopium} and
\emph{Durusdinium} symbionts in response to codominance, we used the
GO\_MWU analysis results which output the degree of up- or
down-regulation of GO terms as measured by the ``delta-rank'' -- the
difference between the median rank of the genes annotated with the term
and the median rank of all other genes. In GO\_MWU, a positive
delta-rank implies up-regulation of genes annotated with the GO term.
The comparison of delta ranks (rather than per-gene expression changes)
between experiments integrates the signal over meaningful functional
categories of genes and, importantly for the current study, circumvents
the problem of different reference transcriptomes used. At the GO
delta-rank level, responses of\emph{Cladocopium} and \emph{Durusdinium}
to codominance were clearly similar (Fig. 3), although the statistical
significance of this similarity cannot be formally ascertained because
GO terms are not independent (they may encompass overlapping sets of
genes). Most notably, ribosomal and photosynthesis categories were
similarly and significantly (p \textless{} 0.001) enriched for
upregulated genes in both genera. These GO categories include large
ribosomal subunit, small ribosomal subunit, ribonucleoprotein complex,
thylakoid part, photosystem, and plastid part (p \textless{} 0.001).

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\par\null

\textbf{Figure 3} Delta rank comparison of highly significant (p
\textless{} 0.001) \emph{Cladocopium} and \emph{Durusdinium} GO
categories. Higher delta ranks indicate upregulation and lower delta
ranks indicate downregulation.

We were concerned that the variance in the number of symbiont counts per
sample would skew the results of our functional analyses. This was
primarily due to the fact that read counts for each symbiont covaried
with the symbiont's proportion in the host. While this effect was
formally accounted for in our analyses by including the
log\textsubscript{10}(total count) as a covariate in DESeq2 models,
doubts remained as to whether this would not create additional
artifacts. One reassuring argument is that the main gene expression
response (to codominance) was not aligned with the minor-major axis
(i.e. with variation in total counts) but rather happened in the middle
of the total counts' scale. Still, to further test for possible residual
effects of total counts variation on our results, we resampled the
counts across samples so that each sample would have similar counts. We
reduced the counts to 30,000 per sample, 15,000 per sample, and 8,000
per sample, the latter being the lowest number of counts for a symbiont
type observed in a sample. We repeated the DESeq2 and GO\_MWU analyses
for each resampled dataset and compared the GO delta ranks of each.
Reassuringly, we observed similar results at the GO delta-ranks level
across all resampling trials, indicating that our functional results
were largely unaffected by differences in coverage across samples (Fig.
S3).

\emph{Symbiont codominance is associated with reduced coral stress}

We were next interested in how symbiont codominance is reflected in the
host functional profile. In addition to analyzing the effect of
codominance on its own, we were also interested in how symbionts'
codominance modifies the host response to heat stress (i.e.,
codominance:heat interaction). To better interpret the coral host
functional profiles, we used eukaryotic orthologous group (KOG) analysis
to identify broader functional categories of modulated genes and to
formally compare these results to the known profile of
\emph{Acropora}sp. response to various kinds of high-intensity stress
(generalized stress response, ``GSR'';\emph{Dixon et al.,2020}). This
analysis revealed that host gene expression response to symbiont
codominance had no significant correlation with the GSR (Fig 4B),
indicating that harboring codominant symbionts does not stress the host.
Instead, supporting the GO analysis results, the ``translation,
ribosomal structure, and biogenesis'' category was up-regulated (Fig.
4A), suggesting stimulation of cellular growth (\emph{Giordiano et al.,
2015};\emph{Elser et al.,} \emph{2003};\emph{Bosdriez et al.,
2015};\selectlanguage{ngerman}\emph{López-Maury et al.,} \emph{2008}). As expected, gene
expression of the heated corals strongly correlated with the GSR (r =
0.66, p = 0.00058, Fig. 4C), implying that the corals were stressed by
the treatment. However, delta-ranks for the heat:codominance interaction
term were negatively correlated with the GSR (r=-0.79, p=5.9e-06, fig.
4D), which means that hosting codominant symbionts mitigated the heat
stress response.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4} Symbiont codominance does not cause host stress and is
associated with less pronounced host stress under heat. (A) Heatmap of
delta-ranks across eukaryotic orthologous groups (KOGa), showing which
KOG terms are upregulated (red) or downregulated (blue) with respect to
heat:codominance interaction, codominance, generalized
\emph{Acropora}stress response (GSR), and response to heat in this
experiment (``heated''). (B-D) Correlation of KOG delta ranks between
generalized stress response (x-axis) and (B) response to codominance;
(C) response to heat; (D) heat:codominance interaction (i.e.,
codominance-specific modification of the response to heat).

\emph{Symbiont densities are the lowest under codominance}

To evaluate the relative density of symbionts across samples, we looked
at the variation of the ratio of symbiont to host reads. In another
coral, \emph{Orbicella faveolata} , this measure is a reliable proxy of
symbiont density (\emph{Manzelloet al., 2018)}. We find that the
proportion of symbiont reads is the lowest under codominance (Fig. 5).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5} Corals with codominant symbionts tend to have lower
symbiont density. X-axis is the rank of the sample from least to most
Cladocopium, as on the top panel of Figure 1. The codominance zone is
shaded. Y-axis is the logarithm of the ratio of the total number of
reads mapping to symbiont transcriptomes and the number of reads mapping
to the chromosome 1 of the host.

Discussion

\emph{Symbionts}

We initially expected that symbiont gene expression would primarily
depend on its own abundance within the host. Instead, in
both\emph{Cladocopium} and \emph{Durusdinium} , gene expression was
similar when the genus was either the overwhelming majority or minority,
but was highly distinct when the relative proportion of the two genera
were close to equal (codominant state, Fig 1). Functional analysis of
the codominant state revealed upregulation of translation and
photosynthesis machinery in both symbiont genera (Fig. 2, 3).
Association between high growth rate and high concentrations of
ribosomes has been demonstrated in a variety of organisms, including
multicellular plants, green algae (\emph{Giordiano et al., 2015}),
insects, crustaceans (\emph{Elser et al.,} \emph{2003}), bacteria
(\emph{Bosdriez et al., 2015}), and yeast (\selectlanguage{ngerman}\emph{López-Maury et al.,}
\emph{2008}). We therefore believe that the observed functional signal
indicates higher growth rate in both symbiont genera in the codominant
state.

\emph{Coral host}

Under heat stress, symbionts are expected to parasitize the coral host
by sequestering host resources and proliferating in host tissues without
giving photosynthates to the host (\emph{Lesser et al.,
2013};\emph{Baker et al., 2018};\emph{Morris et al., 2019}). Higher
competition between symbionts typically results in higher virulence
towards the host (\emph{Bremermann and Pickering, 1983};\emph{Chao et
al., 2000}). In the codominant state the symbionts might be expected to
compete more, and, as our data indicate, they also grow more,
potentially withholding resources from the host. All this could result
in host stress, but our data do not support this prediction. Functional
profiles of corals with codominant symbionts did not significantly
correlate with profiles from stressed corals (Fig. 4 A, B). Instead,
under codominance the corals upregulated their translational machinery
(Fig. 3C, Fig. 4A), which might be an indication of higher growth rate
(\emph{Elser et al.,} \emph{2003};\emph{López-Maury et al.,}
\emph{2008};\emph{Giordiano et al., 2015};\emph{Bosdriez et al., 2015}).
Down-regulation of neuronal components (Fig. 4A) is also notable, but
cannot be easily interpreted. More importantly, in corals with
codominant symbionts the response to elevated temperature treatment was
reduced (Fig. 4D), indicating higher stress resilience.

\emph{Causation direction}

Two alternative hypotheses can be put forward to explain these results,
differing in the direction of the causation. The first explanation is
that symbionts switch into a highly competitive physiological mode when
they are near 50:50 ratio in the host, increasing their productivity in
the effort to outgrow each other. This ``growth race'' benefits the host
because of higher symbiont productivity, improving the host's growth and
boosting its stress resilience. The second explanation starts with a
host that is very healthy: it is less susceptible to stress and
experiences a high growth rate. The host's growth promotes symbiont
growth to occupy the newly available space, while reduced competition
inside the new space allows for symbiont codominance where one genus
would otherwise outcompete the other. In support of this latter
hypothesis, corals with codominant symbionts had lower symbiont
densities than non-codominant corals (Fig. 5); this result would have
been the opposite if the codominance was associated with the higher
competition between symbionts, as postulated under the first
explanation. The second explanation also appears more parsimonious
because it does not assume an unknown mechanism of the two symbionts
sensing each other's abundances. In addition, the notable reduction in
neuronal investment in codominant corals (Fig. 2C) suggests that
codominance might in part be promoted by reduced host control over the
symbionts' proliferation, assuming host neurons are actually involved in
such control, which remains to be investigated in the future.

Conclusions

We have documented a strong gene expression response to the presence of
a mixed symbiont community in both the symbionts and the coral host.
Overall, the presence of a mixed symbiont community is associated with
higher physiological fitness of all symbiotic partners involved,
manifested as higher growth rate and productivity in symbionts and
higher cellular growth and stress resilience in the host. It appears
more likely that symbiont growth and productivity are elevated as a
consequence of higher host fitness, not the other way around, which is a
testable hypothesis for future research. Irrespective of the causation
direction, the presence of mixed symbiont communities could potentially
be used as an instant indicator of coral well-being, which would be a
useful tool for coral conservation and restoration.

References

Andrews, S. (2010). fastqc: A quality control tool for high throughput
se-quence data.

Baker, Andrew C. ''Flexibility and Specificity in Coral-Algal Symbiosis:
Diversity, Ecology, and Biogeography Of Symbiodinium.'' \emph{Annual
Review of Ecology, Evolution, and Systematics} 34.1 (2003):
661-89.\emph{https://doi.org/10.1146/annurev.ecolsys.34.011802.132417}

Baker, David M., Christopher J. Freeman, Jane C.y. Wong, Marilyn L.
Fogel, and Nancy Knowlton. ''Climate Change Promotes Parasitism in a
Coral Symbiosis.'' \emph{The ISME Journal} 12.3 (2018): 921-30.
https://\emph{doi} .org/10.1038/s41396-018-0046-8

Barshis, Daniel J., Jason T. Ladner, Thomas A. Oliver, François O.
Seneca, Nikki Traylor-Knowles, and Stephen R. Palumbi. ''Genomic Basis
for Coral Resilience to Climate Change.'' \emph{Proceedings of the
National Academy of Sciences} 110.4 (2013): 1387-392.
https://doi.org/10.1073/pnas.1210224110

Bremermann, Hans J., Pickering, John, A game-theoretical model of
parasite virulence, Journal of Theoretical Biology,Volume 100, Issue
3,1983, Pages 411-426, ISSN
0022-5193,\emph{https://doi.org/10.1016/0022-5193(83)90438-1}.

Bosdriesz, Evert, Douwe Molenaar, Bas Teusink, and Frank J. Bruggeman.
''How Fast\selectlanguage{english}-growing Bacteria Robustly Tune Their Ribosome Concentration
to Approximate Growth\selectlanguage{english}-rate Maximization.'' \emph{The FEBS Journal}
282.10 (2015): 2029-044. Print. https://doi.org/10.1111/febs.13258

Chao, Lin, et al. ``Kin Selection and Parasite Evolution: Higher and
Lower Virulence with Hard and Soft Selection.'' \emph{The Quarterly
Review of Biology} , vol. 75, no. 3, 2000, pp. 261--275.,
doi:10.1086/393499.

Cunning, Ross, and Andrew C. Baker. ''Thermotolerant Coral Symbionts
Modulate Heat Stress\selectlanguage{english}-responsive Genes in Their Hosts.'' \emph{Molecular
Ecology} 29.15 (2020): 2940-950. https://\emph{doi}
.org/10.1111/mec.15526

Dixon, G. B., S. W. Davies, G. V. Aglyamova, E. Meyer, L. K. Bay, and M.
V. Matz. ''Genomic Determinants of Coral Heat Tolerance across
Latitudes.'' \emph{Science} 348.6242 (2015): 1460-462.
https://\emph{doi} .org/10.1126/science.1261224

Dixon, Groves, Evelyn Abbott, and Mikhail Matz. ''Meta\selectlanguage{english}-analysis of the
Coral Environmental Stress Response: Acropora Corals Show Opposing
Responses Depending on Stress Intensity.'' \emph{Molecular Ecology}
29.15 (2020): 2855-870. https://\emph{doi} .org/10.1111/mec.15535

Elser, J. J., K. Acharya, M. Kyle, J. Cotner, W. Makino, T. Markow, T.
Watts, S. Hobbie, W. Fagan, J. Schade, J. Hood, and R. W. Sterner.
''Growth Rate-stoichiometry Couplings in Diverse Biota.'' \emph{Ecology
Letters} 6.10 (2003): 936-43.
https://doi.org/10.1046/j.1461-0248.2003.00518.x

Falkowski, Paul G., Zvy Dubinsky, Leonard Muscatine, James W. Porter,
Light and the Bioenergetics of a Symbiotic Coral, \emph{BioScience} ,
Volume 34, Issue 11, December 1984, Pages
705--709,\emph{https://doi.org/10.2307/1309663}

Fuller, Zachary L., Veronique J. L. Mocellin, Luke A. Morris, Neal
Cantin, Jihanne Shepherd, Luke Sarre, Julie Peng, Yi Liao, Joseph
Pickrell, Peter Andolfatto, Mikhail Matz, Line K. Bay, and Molly
Przeworski. ''Population Genetics of the Coral Acropora Millepora:
Toward Genomic Prediction of Bleaching.'' \emph{Science} . American
Association for the Advancement of Science, 17 July 2020.
https://\emph{doi} .org/10.1101/867754

Giordano, Mario, Matteo Palmucci, and John A. Raven. ''Growth Rate
Hypothesis and Efficiency of Protein Synthesis under Different Sulphate
Concentrations in Two Green Algae.'' \emph{Plant, Cell \&
Environment}38.11 (2015): 2313-317. https://doi.org/10.1111/pce.12551

Ladner, Jason T., Daniel J. Barshis, and Stephen R. Palumbi. ''Protein
Evolution in Two Co-occurring Types of Symbiodinium: An Exploration into
the Genetic Basis of Thermal Tolerance in Symbiodinium Clade
D.''\emph{BMC Evolutionary Biology} 12.1 (2012): 217.
https://doi.org/10.1186/1471-2148-12-217

Lajeunesse, Todd C., John Everett Parkinson, Paul W. Gabrielson, Hae Jin
Jeong, James Davis Reimer, Christian R. Voolstra, and Scott R. Santos.
''Systematic Revision of Symbiodiniaceae Highlights the Antiquity and
Diversity of Coral Endosymbionts.'' \emph{Current Biology} 28.16
(2018).\emph{https://doi.org/10.1016/j.cub.2018.07.008}

Langfelder, P., and S. Horvath. ''WGCNA Package FAQ. Retrieved from
https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/faq.html.''
2017.

Lesser, M. P., M. Stat, and R. D. Gates. ''The Endosymbiotic
Dinoflagellates (Symbiodinium Sp.) of Corals Are Parasites and
Mutualists.'' \emph{Coral Reefs} 32.3 (2013): 603-11.
https://doi.org/10.1155/2011/185890

Li, H., B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G.
Marth, G. Abecasis, and R. Durbin. ''The Sequence Alignment/Map Format
and SAMtools.'' \emph{Bioinformatics} 25.16 (2009): 2078-079.
https://\emph{doi} .org/10.1093/\emph{bioinformatics} /btp352

Liao, Y., G. K. Smyth, and W. Shi. ''FeatureCounts: An Efficient General
Purpose Program for Assigning Sequence Reads to Genomic
Features.''\emph{Bioinformatics} 30.7 (2013): 923-30. Print.
https://doi.org/10.1093/bioinformatics/btt656

Lopez-Maury, Luis, Samuel Marguerat, and Jurg Bahler. ''Tuning Gene
Expression to Changing Environments: From Rapid Responses to
Evolutionary Adaptation.'' \emph{Nature Reviews Genetics} 9.8 (2008):
583-93. https://doi.org/10.1038/nrg2398

Manzello, Derek P., Mikhail V. Matz, Ian C. Enochs, , Lauren Valentino,
Renee D. Carlton, Xaymara Serrano Kolodziej., Erika K. Towel., Mike
Jankulak. ``Role of host genetics and heat\selectlanguage{english}-tolerant algal symbionts in
sustaining populations of the endangered coral \emph{Orbicella
faveolata} in the Florida Keys with ocean warming.'' \emph{Global Change
Biology} . 25.8 (2019): 1016-1031. https://doi.org/10.1111/gcb.14545

Matthews, Jennifer L., Clinton A. Oakley, Adrian Lutz, Katie E. Hillyer,
Ute Roessner, Arthur R. Grossman, Virginia M. Weis, and Simon K. Davy.
''Partner Switching and Metabolic Flux in a Model
Cnidarian--dinoflagellate Symbiosis.'' \emph{Proceedings of the Royal
Society B: Biological Sciences} 285.1892 (2018): https://\emph{doi}
.org/10.1098/rspb.2018.2336

Morris, Luke A., Christian R. Voolstra, Kate M. Quigley, David G.
Bourne, and Line K. Bay. ''Nutrient Availability and Metabolism Affect
the Stability of Coral--Symbiodiniaceae Symbioses.'' \emph{Trends in
Microbiology} 27.8 (2019): 678-89. https://\emph{doi}
.org/10.1016/j.tim.2019.03.004

Pettay, D. Tye, Drew C. Wham, Robin T. Smith, Roberto Iglesias-Prieto,
and Todd C. Lajeunesse. ''Microbial Invasion of the Caribbean by an
Indo-Pacific Coral Zooxanthella.'' \emph{Proceedings of the National
Academy of Sciences} 112.24 (2015): 7513-518.
https://doi.org/10.1073/pnas.1502283112

Rose, Noah H., Francois O. Seneca, and Stephen R. Palumbi. ''Gene
Networks in the Wild: Identifying Transcriptional Modules That Mediate
Coral Resistance to Experimental Heat Stress.'' \emph{Genome Biology and
Evolution} 8.1 (2015): 243-52. https://doi.org/10.1093/gbe/evv258

Shore-Maggio, Amanda, Sean M. Callahan, and Greta S. Aeby. ''Trade-offs
in Disease and Bleaching Susceptibility among Two Color Morphs of the
Hawaiian Reef Coral, Montipora Capitata.'' \emph{Coral Reefs} 37.2
(2018): 507-17. https://\emph{doi} .org/10.1007/s00338-018-1675-0

Ulstrup, K. E., and M. J. H. Van Oppen. ''Geographic and Habitat
Partitioning of Genetically Distinct

Zooxanthellae ( Symbiodinium ) in Acropora Corals on the Great Barrier
Reef.'' \emph{Molecular Ecology} 12.12 (2003): 3477-484.
https://\emph{doi} .org/10.1046/j.1365-294X.2003.01988.x

Wright, Rachel M., Adrienne M. S. Correa, Lucinda A. Quigley, Lory Z.
Santiago-Vazquez, Kathryn E. F. Shamberger, and Sarah W. Davies. ''Gene
Expression of Endangered Coral (Orbicella Spp.) in Flower Garden Banks
National Marine Sanctuary After Hurricane Harvey.'' \emph{Frontiers in
Marine Science} 6 (2019).
Print.\emph{https://doi.org/10.3389/fmars.2019.00672}

Wright, R. M., Kenkel, C. D., Dunn, C. E., Shilling, E. N., Bay, L. K.,
\&Matz, M. V. (2017). Intraspecific differences in molecular stress
responses and coral pathobiome contribute to mortality under bacterial
challenge in Acropora millepora.Scientific Reports,7,
2609.https://doi.org/10.1038/s41598-017-02685-1

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