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Journal of Tropical Ecology
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Research Article
Cite this article: Lu H, Asem A, Li W, Che W, and
Wang P-Z. Influence of temperature changes on
symbiotic Symbiodiniaceae and bacterial
communities’structure: an experimental study
on soft coral Sarcophyton trocheliophorum
(Anthozoa: Alcyoniidae). Journal of Tropical
Ecology https://doi.org/10.1017/
S0266467421000109
Received: 11 November 2020
Revised: 8 April 2021
Accepted: 10 May 2021
Keywords:
Sarcophyton trocheliophorum; symbiotic
bacteria; Symbiodiniaceae; diversity;
temperature difference
Author for correspondence:
Weidong Li and Pei-Zheng Wang,
Emails: 542148880@qq.com;
condywpz@126.com
†Equally contribution as first author.
© The Author(s) 2021. Published by Cambridge
University Press. This is an Open Access article,
distributed under the terms of the Creative
Commons Attribution licence (http://
creativecommons.org/licenses/by/4.0), which
permits unrestricted re-use, distribution and
reproduction, provided the original article is
properly cited.
Influence of temperature changes on symbiotic
Symbiodiniaceae and bacterial communities’
structure: an experimental study on soft coral
Sarcophyton trocheliophorum (Anthozoa:
Alcyoniidae)
Hao Lu1
,
†, Alireza Asem1
,
†, Weidong Li2, Wenxue Che3and Pei-Zheng Wang3
1College of Fisheries and Life Science, Hainan Tropical Ocean University, Sanya, China; 2College of Ecology and
Environment, Hainan University, Haikou, China and 3College of Ecology and Environment, Hainan Tropical
Ocean University, Sanya, China
Abstract
It is well concluded that microbial composition and diversity of coral species can be affected
under temperature alterations. However, the interaction of environmental accumulation of cor-
als and temperature stress on symbiotic Symbiodiniaceae and bacterial communities are rarely
studied. In this study, two groups of soft coral Sarcophyton trocheliophorum were cultured
under constant (26 °C) and inconstant (22 °C to 26 °C) temperature conditions for 30 days
as control treatments. After that, water was cooled rapidly to decrease to 20 °C in 24 h. The
results of diversity analysis showed that symbiotic Symbiodiniaceae and bacterial communities
had a significant difference between the two accumulated groups. The principal coordinate
analyses confirmed that symbiotic Symbiodiniaceae and bacterial communities of both control
treatments were clustered into two groups. Our results evidenced that rapid cooling stress could
not change symbiotic Symbiodiniaceae and bacterial communities’composition. On the other
hand, cooling stress could alter only bacterial communities in constant group. In conclusion,
our study represents a clear relationship between environmental accumulation and the impact
of short-term cooling stress in which microbial composition structure can be affected by early
adaptation conditions.
Introduction
Coral bleaching has become a research hotspot for marine science since 1960s. This phenome-
non was initially discovered as a consequence of large-scale loss of Symbiodiniaceae in corals
under environmental disturbances (Yonge and Nicholls 1931). Goreau (1964) reported that
shallow-water corals were whitened and had died in Jamaica due to the abundant inflow of
freshwater and further proposed the term ‘coral bleaching’. Nowadays, there are different opin-
ions on the causes of coral bleaching, such as temperature rising (Aronson et al. 2000, Hoegh-
Guldberg 1999), photoinhibition (Bhagooli & Hlidaka 2004), and chemical pollutants (Gervino
et al. 2003, Philip et al. 2004). Afterwards influence of low temperature and bacterial infection
were considered. The large-scale deaths of corals have been reported in Leizhou Peninsula dur-
ing Holocene due to extensive cooling (Yu et al. 2004). In an experimental study, Kushmaro
et al. (1996) documented that infected Oculina patagouica by Vibrio AK-1 bacteria could exhibit
bleaching. Further studies showed Vibrio shilonii AK-1 releases quartile sensing signal mole-
cules in the process of coral infection (Li et al. 2016). Additionally, Meyer et al. (2016) confirmed
that quartile sensing signal molecules could be involved in the infection process of coral leukosis.
Regarding current studies, there are several causes for coral bleaching. However, a consensus
has been achieved that coral bleaching is mainly caused by losing in vivo pigments of symbiotic
Symbiodiniaceae. Symbiodiniaceae lives in the vacuole of the entoderm cells of the host and
provides more than 95% of the products of photosynthesis (e.g., amino acids, sugar, carbohy-
drate, and small molecular peptide) for hosts (Loh et al. 2001,Luet al. 2021a,b). Photosynthetic
products can supply energy and essential compounds for corals; instead, Symbiodiniaceae can
get elemental nutrients (e.g., amine and phosphate) from the metabolic products by corals
(Saxby 2000). Weglry et al. (2007) found that symbiotic microorganisms (e.g., bacteria, fungi,
and archaea) play key roles in coral metabolism, such as energy supply, transformation of sub-
stances, and disease immunity. Additionally, Anthozoans can provide shelter and raw materials.
The probiotics have an indispensable biological role for corals. During coral bleaching, the
nitrogen-fixing bacteria in the mucus of corals can replace with Symbiodiniaceae and provide
nutrients for coral. For example, the symbiotic Cyanobacteria can synthesize nutrients through
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the bleaching stage in Oculinary patagonica (Teplitski & Ritchie
2009). Moreover, probiotics can also facilitate the ecological balance
of flora in the host or in surrounding environments (Merrifield et al.
2010). The symbiotic microorganisms (Symbiodiniaceae and bac-
teria) of corals are groups of complicated dynamic combinations.
Regional disparity (McKew et al. 2012), eutrophication (Thurber
et al. 2009), and diseases (Rosenberg et al. 2007) can change the sym-
biotic microflora of corals. Terraneo et al. (2019) used the Internal
Transcribed Spacer (ITS) sequence of Symbiodiniaceae to study on
Porites corals in the Red Sea. It was calculated that the communities’
structure of Symbiodiniaceae has a relationship with latitude.
Environmental condition can be an important factor to restrict their
distribution. Pootakham et al. (2019) also found that coral symbiotic
bacteria are sensitive to temperature, and temperature alterations
cause a change in the structure of the bacterial community.
In Similan Archipelago (Thailand), large-amplitude internal
waves bring daily average temperature differences of 5–7 °C in sea-
water. Wall et al. (2015) reported that such temperature differences
induce the strong adaptation of corals. Studies on the dynamic
changes in the holobiont of corals can provide a new approach
to better understand coral’s biology and their microbial commun-
ities’relationships with environmental changes. We hypothesize
that accumulation condition can cause non-identical responses
in coral host to determine symbiotic Symbiodiniaceae and bacterial
composition under different environmental stress. The aim of this
study was to point out the effect of rapid cooling of water temper-
ature on symbiotic Symbiodiniaceae and bacterial communities’
structure of cultured Sarcophyton trocheliophorum under constant
(26 °C) and variable (22 °C to 26 °C) temperature conditions.
Materials and methods
Sampling
Following Yu et al. (2020), a specimen of S. trocheliophorum was
collected (in December 2020) from a fringing reef at a depth of 6 m
(salinity: 34 ppt, temperature: 27 °C, water temperature: 25 °C)
around the Xiaozhou Island (18°12'30.43"N; 109°23'27.62"E) in
South China Sea (Figure S1). Taxonomic status of specimen has
been confirmed using 28S and mtMutS markers sequences
(Benayahu et al. 2018, Quattrini et al. 2019) and morphology of
sclerites (Benayahu et al. 2018). The 17 branches of the specimen
were split and cultured in a glacial aquarium (ca. 100 L) filled with
natural seawater (salinity: 33 ±1 ppt; temperature: 26±1 °C). The
aquarium was illuminated with white and blue cool LCD fluores-
cent bulbs (Philips T5HO Activiva Active 54 W) at a light intensity
of 518 μmol photons m−2s−1in a 12 h/12 h light–dark cycle for 4
months to recover full colony and acclimatise to laboratory condi-
tion following Tang et al. (2018).
Temperature acclimation and simulation of cooling event
Twelve well-grown full colonies have been chosen and divided into
two groups (constant and inconstant temperatures) in which each
group including control and rapid cooling treatments (each treat-
ment consists of three replicates). Temperature of constant group
(Cg) was set as acclimation condition (26 °C) following Tang et al.
(2018). To simulate the effect of temperature changes, its range was
set from 22 °C to 26 °C for inconstant group (Ig), which was auto-
matically coordinated every 12 h. Both groups (including control
and rapid cooling treatments) were acclimated to 30 days simulta-
neously. At the end of 30 days, water temperature was swiftly
decreased to 20 °C in rapid cooling treatments. This condition
was maintained for 24 h (control treatments continued in the
previous temperature condition).
DNA extraction, PCR amplification, and Illumina MiSeq
sequencing
Whole DNA from each individual was extracted using the Column
Marine Organism DNA Kit (Guangzhou DONGSHENG, China).
DNA was stored in Tris-EDTA buffer solution and kept at −20°C
for further studies.
PCR amplification of the ITS2 sequence (approximately 320 bp)
for Illumina MiSeq platform was performed using primers ITS intfor2
and ITS2 reverse (Coleman et al. 2010, LaJeunesse & Trench 2000).
The primer sequences were as follows: Miseq-ITSintfor2 (50-GA
ATTGCAGAACTCCGTG-30) and Miseq-ITS2-reverse (5 0-GG
GATCCATATGCTTAAGTTCAGCGGGT-30).
The bacterial variable regions 3 and 4 of the 16S rRNA gene were
amplified using the primer pair: 341F (5 0-CCTACGGGNG
GCWGCAG-30) and 805R (5 0-GACTACHVGGGTATCTAA
TCC-30)(Lianget al. 2017).
Amplification was performed according to the following proto-
col. First, PCRs were run with 10 μM primer, 1 μL2×Taq master
Mix (Sangon Biotech Co., Ltd., Shanghai, China), and 15 μLof20
ng DNA. DNase-free water was added to obtain a total volume of
30 μL. The mixture was exposed to the following condition: dena-
turation at 94 °C for 3 min; five cycles of denaturation at 94 °C for
30 s, annealing at 45 °C for 20 s, and extension at 65 °C for 30 s; 20
cycles of denaturation at 94 °C for 20 s, annealing at 55 °C for 20 s,
and extension at 72 °C for 30 s; and a final extension at 72 °C for 5
min. A second 30 μL of reaction mixture containing 20 ng DNA, 15
μL2×Taq master Mix (Sangon Biotech Co., Ltd., Shanghai, China),
1μL of each Bar-PCR primer (10 uM), and DNase-free water was
prepared to make a total volume of 30 μL and was used for PCR
under the following condition: denaturation at 95 °C for 3 min, five
cycles of denaturation at 94 °C for 20 s, annealing at 55 °C for 20 s
and extension at 72 °C for 30 s, and a final extension at 72 °C for 5
min. Pooled samples were cleaned with Agencourt AMPure XP
magnetic bead system (Beckman Coulter, Brea, CA, USA). The
samples were then quantified by Qubit3.0 DNA (Life
Technologies, CA, USA) and pooled in equimolar ratios. A
PE2×300 library was constructed according to the standard oper-
ating procedures of the platform. Finally, sequencing was con-
ducted on the IlluminaMiseqPE300 platform (Majorbio).
Analysis of sequence data
The Miseq data contains the barcode sequence, the primers, and
linker sequences that are added at the time of sequencing. First,
cutadapt was used to remove the primer sequence. According to
PE overlap between the overlap, PEAR pairs of reads were then
used to merge the sequence. The merge sequence overlap area
was allowed a maximum mismatch ratio of 0.1. According to
the barcode tag sequence used to identify and distinguish the sam-
ple to get the sample data, the Prinseq was used to remove the sam-
ple in the sample tail mass of 20 or less base. The port was set at 10
bp when the average quality value in the window was less than 20,
starting from the window to the back end of the base. The cut con-
tained the N part of the sequence and removed the short sequence
in the data according to the length threshold of 200 bp. Low-com-
plex sequence filtering was conducted, and the sample valid data
were finally obtained. Usearch and uchime were used to remove
chimaeric with non-specific amplification sequences to get filtered
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reads. All sample sequences were clustered according to the dis-
tance between the sequences. Finally, the sequences were divided
into different operational taxonomic units (OTU) using a 97% sim-
ilarity cut-off.
Nucleotide sequence accession numbers
Raw reads of Symbiodiniaceae (accession numbers: SRP279038)
and bacteria (accession numbers: SRP279036) were submitted to
the NCBI SRA.
MiSeq ITS2 sequence analysis
A comparison database corresponding to the Symbiodiniaceae
subgroup ITS was downloaded from GeoSymbio (http://sites.
google.com/site/geosymbio/downloads), and the ITS2 database
was uploaded onto the website of CD-HIT Suite. CD-HIT was
set at 100%, and other parameters were set to default.
Repetitions were deleted, and annotations were combined. The
remaining results were used to construct a non-redundancy ITS
database. The best alignment results of OTU sequences were
screened, and the results were filtered. The default satisfied a sim-
ilarity >90%, and a sequence of coverage >90% was used for sub-
sequent classification (Arif et al. 2014, Ziegler et al. 2017). The
diversity of single sample was gained from the alpha diversity index
based on sample clustering results with Mothur software. OTU
abundance and diversity were reflected by Chao 1 and Simpson
indices, respectively. To measure the change in the diversity of
Symbiodiniaceae from one condition to another, the principal
coordinate analysis (PCoA) at the OTU levels (OTU68, OTU49,
OTU44, and other identified taxa) has been analyzed.
Bacterial microbiome analysis
Non-repetitive sequences of 16S were extracted from optimal
sequences for OTU clustering (excluding single sequence) accord-
ing to 97% similarity. Chimaeras in the clustering process were
eliminated to obtain the representative sequence of OTU. A taxo-
nomic analysis of OTU representative sequences of 97% similar
level was conducted using the RDP classifier Bayesian algorithm
to acquire the specific classification information of each OTU.
Community composition of different samples was analyzed on dif-
ferent classification levels (Inc. domain, kingdom, phylum, class,
order, family, genus, and species). The diversity of a single sample
was gained from the alpha diversity index analysis of sample clus-
tering results with Mothur software. Coverage, abundance, and
diversity of microflora were reflected by coverage, Chao 1, and
Simpson indices, respectively. The PCoA has been performed to
consider the beta diversity analysis at the genus and OTU levels.
Results
Diversity of Symbiodiniaceae
Based on OTU classification, an abundance of the symbiotic
Symbiodiniaceae is summarized in Table 1 and Figure 1. OTUs
were identified in three major levels, including OTU68, OTU49,
and OTU44. The OTU68 presented the highest abundance in all
treatments. The highest and lowest values of OTU68 were recorded
in Cg (control: 98.8%, cooling: 96.9%) and Ig (control: 62.07% and
cooling 63.52%), respectively. In contrast, the highest and lowest
values of OTU49 and OTU44 were revealed in Ig and Cg treat-
ments consecutively.
Based on OTU levels, PCoA shows that the first and second
coordinates held 99.89% and 0.09% of the variance, respectively.
PCoA documented that Cg and Ig were completely divided into
two clusters following first coordinate, while there was no indica-
tive differentiation between treatments within each group
(Figure 2).
Chao and Shannon indices represent significant differences
among treatments (Table 2;Figure 3). Overall, the highest values
of both Chao and Shannon indices were observed in Cg. Although
Shannon index could not show a difference between control (0.979
±0.012) and rapid cooling (0.930 ±0.050) treatments in Cg, the
highest value of Chao index was obtained in rapid cooling treat-
ment of Cg (17.3 ±0.577). There was no significant difference
between control and rapid cooling treatments in Ig (p>0.05).
Table 1. Percentage of Symbiodiniaceae OTUs abundance (Cg: constant group,
Ig: inconstant group).
OTU
Treatment
Cg (control) Cg (cooling) Ig (control) Ig (cooling)
OTU68 98.8 96.9 62.07 63.52
OTU49 0.51 1.38 35.22 33.42
OTU44 0.12 0.06 2.44 2.81
Others 0.57 1.66 0.27 0.25
Figure 1. The OTU-based Symbiodiniaceae genera profiles (Cg: constant group, Ig:
inconstant group).
Figure 2. Relationships between Symbiodiniaceae diversity and groups/treatments
using principal coordinate analysis (PCoA) based on the OTU level.
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Diversity of bacteria
Four groups of sample databases were obtained from high-
throughput sequencing. All samples were screened, and repeated
results were eliminated. Table 3 represents the bacterial com-
munities’structure in different taxonomic levels. Overall, the
highest and lowest bacterial contribution were observed in both
control and rapid cooling of Cg, respectively. The symbiotic bac-
terial structure was composed of seven most dominant phyla,
including Tenericutes, Protebacteria, Bacteroidetes, Firmicutes,
Actinobacteria, Spirochaetae, and Cyanobacteria (Table 4).
Percentage of bacterial communities of phyla is shown in
Figure 4. Our finding demonstrated that generally there was
no significant difference in phyla composition between control
and rapid cooling in Ig, while in Cg, Tenericutes (36.3%) and
Protebacteria (53.21%) were dominant phyla in control and rapid
cooling treatments, respectively. The highest percentage of
cyanobacteria (phototrophic bacteria) was presented in control
treatment of Cg samples. Increasing the percentage of
Bacteroidetes after rapid cooling in Cg was considerable
(7.72% vs. 38.06%). Similar result was recorded in genus level
inwhichbothtreatmentsofIgmostly revealed parallel compo-
sition. In the other part, genera composition showed dissimilarity
within Cg treatments (Figure 5). Control and rapid cooling treat-
ments contained the highest percentage of Spiroplasma (36.24 vs.
0.14%) and Marinifilum (24.15 vs.0.00%), respectively.
Additionally, the high value of Enterococcus (11.47 vs. 0.00%)
was distinguished in the control treatment (Table S1). Vibrio
which was known as a pathogen, was recorded in coral treat-
ments, except in the control treatment of Cg although.
In genus level, PCoA represents that the first and second coor-
dinates consist of 40.37% and 22.33% of variation and totally the
two coordinates involve with 62.7% of variety (Figure 6). Our
results showed that four treatments were grouped into three sep-
arated clusters consisting of Cg control, Cg rapid cooling, and
another containing both treatments of Ig together. In OTUs level,
the first and second PCoA coordinates contribute 32.93% and
22.81% of the variance, respectively (overall, 55.74% of total differ-
ence). Same as genus level, Cg control and Cg rapid cooling treat-
ments were divided into two clusters, and Ig control and Cg rapid
cooling treatments were placed in a single one (Figure 7).
Chao and Simpson indices evidenced that there was no signifi-
cant difference in abundance communities composition of bacteria
between the control and rapid cooling treatments within each
group, as well as between both control treatments (Table 5).
The highest and lowest values of Chao index were observed in both
rapid cooling treatments in Cg (506.5 ±73.41) and Ig (328.4 ±
33.39), respectively. Meanwhile, Simpson index presented contrary
results, which the highest and lowest values belonged to cooling
treatments in Ig (0.32 ±0.09) and Cg (0.09 ±0.02), respectively
(Figure 8).
Discussion
This is the first experimental study to understand the effect of dif-
ferent conditions of thermal adaptation on the communities’struc-
ture of symbiotic Symbiodiniaceae and bacteria of coral in
association with rapid cooling stress.
Diversity changes of Symbiodiniaceae
Diversity of symbiotic Symbiodiniaceae in host was analyzed with
ITS2 marker. This method has been widely accepted and used by
many researchers to compare the traditional Symbiodiniaceae clas-
sification method (Arif et al. 2014, Quigley et al. 2014, Thomas
et al. 2014, Ziegler et al. 2017).
With regard to our results, Symbiodiniaceae communities were
identified with OTU68, OTU49, and OTU44, out of which OTU68
had the highest abundance in all treatments. According to taxo-
nomical relationship, Symbiodiniaceae has been classified into
nine genera which formally named A-I clades (Chen et al.
2019). Four clades of Symbiodiniaceae, including clade A, B, C,
and D have been reported as common symbiotic relationships with
corals (Pochon et al. 2004, Ziegler et al. 2017). In our study, OTU68
belongs to clade C (Cladocopium), whereas OTU49 and OTU44 fit
in clade G (Gerakladium) (see Pochon & Gates 2010) (Figure S2).
Clade G has been recorded in stony corals with low abundance
from South Chain Sea for the first time by Chen et al. (2019). It
is the first time that we could report the existence of clade G in soft
coral with high abundance from South Chain Sea. Zhou and
Huang (2011) proved the dominant species of Symbiodiniaceae
consisted of Clade C in stony corals surrounding the Hainan
Island (South China Sea). Cooper et al. (2011) also reported that
Clade C showed high distribution of Symbiodiniaceae in Acropora
millepora from the Great Barrier Reef (Australia). While different
latitudes represented variable communities’composition of
Symbiodiniaceae in corals, the most abundance of OTUs were
involved in clade C (Chen et al. 2019). Our study also confirmed
that clade C was the dominant community.
Previous studies have documented a significant relationship
between temperature extremes and dominance of clade D1
(Oliver & Palumbi 2009, Oliver & Palumbi 2011). Lajeunesse
Table 2. Mean values (±SD) of Chao index and Shannon index for
Symbiodiniaceae communities under different treatments. (Cg: constant
group, Ig: inconstant group).
Treatment Chao index Simpson index
Cg (Control) 13.1b
(±1.644)
0.979cd
(±0.012)
Cg(cooling) 17.3abc
(±0.577)
0.930ab
(±0.050)
Ig (Control) 11.0c
(±0.000)
0.544bd
(±0.049)
Ig(cooling) 11.2a
(±0.288)
0.542ac
(±0.048)
Same letter in each column shows significant difference (p<0.05).
Figure 3. Mean values (±SD) of Chao index and Shannon index for Symbiodiniaceae
communities under different treatments. (Cg: constant group, Ig: inconstant group).
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et al. (2010) concluded that local environmental conditions have
most likely impacted the relative dominance of coral symbionts.
For example, high temperature and high turbidity may cause
increasing frequency of Symbiodinium trenchi (clade D1) in the
Andaman Sea (northeastern Indian Ocean). They found that with
increasing the rate of turbidity among studied localities, abundance
and frequency of S. trenchi have increased. It was suggested that
water transparency and sediment quality (especially nutrient
levels) could affect on the distribution of D1 in coral hosts
(Cooper et al. 2011). Overall it seems communities’structure of
Symbiodiniaceae can be determined by environmental conditions
(Chen et al. 2019).
Our findings evidence that inconstant thermal conditions can
significantly increase the abundance of clade G. Though clade G
has been identified as the lowest abundance in stony corals
(Chen et al. 2019, LaJeunesse et al. 2018), high percentage of this
clade in Ig was considerable. Generally there is a lack of informa-
tion about the relationship between environmental factors and dis-
tribution of clade G (Chen et al. 2019). Ziegler et al. (2017) showed
that the members of this clade have more potential to adapt with
high temperature and salinity. In this study, although OTU68
(clade C) was reported as dominant Symbiodiniaceae in both
groups, inconstant thermal conditions (22 ºC–26 ºC) has distinctly
increased the abundance of OTU49, which belongs to clade G
(35.22%–33.42% vs.0.5%–1.38%). Additionally, increasing of
OTU44 (clade G) abundance was considerable (0.12%–0.01% vs.
2.44%–2.81%). Our results contradict previous observations in
the Arabian Sea by Ziegler et al. (2017). It can be conservatively
concluded that clade G might exhibit adaptive potential in rela-
tionship with temperature alterations and high/low temperature
stress. Additionally, we document that clade C is sensitive to
long-term temperature alterations while it cannot be affected by
rapid cooling stress.
According to low values of Simpson index, the most important
effect of inconstant culture condition (22 ºC–26 ºC) was the
increased diversity of Symbiodiniaceae (Table 5). This showed that
temperature changes provide more opportunities for large number
of symbiotics to adapt with host corals. Meanwhile low values of
Table 3. Number of bacteria associated with different groups in different taxonomic levels (Cg: constant group, Ig: inconstant group).
Treatment Phylum Class Order Family Genus Species OTU
Cg (control) 30 59 136 244 488 696 1034
Cg (cooling) 17 36 89 173 341 451 646
Ig (control) 22 45 105 205 380 499 719
Ig (cooling) 22 40 93 192 352 463 636
Table 4. Percentage of bacterial abundance on phylum level (Cg: constant group, Ig: inconstant group).
phylum
Treatment
Cg (control) Cg (cooling) Ig (control) Ig (cooling)
Tenericutes 36.3 0.14 54.76 55.86
Protebacteria 15.24 53.21 25.68 27.59
Bacteroidetes 7.72 38.06 6.18 3.63
Firmicutes 23.53 7.07 5.43 4.99
Actinobacteria 3.82 0.45 3.87 4.65
Spirochaetae 2.81 0.04 2.02 1.93
Cyanobacteria 6.03 0.06 0.4 0.41
Others 4.55 0.97 1.66 0.94
Figure 4. The OTU-based bacteria phyla profiles (Cg:
constant group, Ig: inconstant group).
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Chao index in this group suggested that symbiotics could not reach
too high abundance than constant culture conditions. This finding
can be attributed to the effect of temperature changes and/or
culture duration (30 days in this experiment). An extended culture
duration is suggested to get further information.
PCoA indicated that both groups (constant and inconstant)
completely represented different patterns so that, they were
divided into two separated clusters, while there was no significant
differentiation between structure and abundance of OTUs after
cooling within each group. This observation suggested that symbi-
otic Symbiodiniaceae could change under different long-term con-
dition but short-term rapid cooling could not change the structure
of communities. In addition, long-term adaptation could play an
important role to maintain diversity and abundance after a sudden
decrease in water temperature.
Diversity changes of bacteria
Coral bacterial communities can perform an important practical
function in the hosts, such as antibacterial activities (Kelman
et al. 1998, Ritchie 2006), nutrient metabolism (Naumann et al.
2009, Wild et al. 2004), and nitrogen fixation (Grover et al.
2014, Lawler et al. 2016). They also can be associated with coral
diseases (Egan and Gardiner 2016, Mouchka et al. 2010). It seems
beneficial bacterial communities may support coral’s adaptive
potential for rapid changes (Yu et al. 2020, Ziegler et al. 2017).
Symbiotic bacteria in corals perform a key duty in the nutrition
Figure 5. The OTU-based bacteria genera profiles (Cg: constant group, Ig: inconstant group).
Figure 6. Relationships between bacterial diversity and groups/treatments using
principal coordinate analysis (PCoA) based on the genus level.
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resource (Lesser et al. 2004), energy supplying (Mao-Jones et al.
2010), and healthy growth of coral ecosystems (Mahmoud &
Kalendar 2016). Temperature alterations represented a significant
relationship with bacterial composition (Hutchins & Fu 2017). It
was evidenced that change and/or replacement of bacterial com-
munities in corals can be a positive response to adapt with temper-
ature stress (Glasl et al. 2016, Reshef et al. 2006).
Environmental factors can modify relationships between sym-
biotic bacterial community and its coral hosts. Neulinger et al.
(2008) showed that there was no indicative dissimilarity between
the bacterial communities of deep-sea stony coral Lophelia from
Gulf of Mexico and Norway. In contrast, McKew et al. (2012) doc-
umented that bacterial compositions of Porites and Acropora from
two distinct geographical localities in Caribbean Sea (Mexico) and
Indo-Pacific (Indonesia) were significantly different. In addition,
samples of soft coral Scleronephthya gracillimum from different
geographical localities showed distinguished differentiation in bac-
terial communities (Seonock et al. 2017). It is obvious that
differences in environmental factors can change the communities
of bacteria at different geographical areas. We suggest that
differences in colouration of corals in different habitats can be
attributed to communities of bacteria with different types and
abundance of pigments.
Many studies aim to understand whether diseases are spread in
corals by invasive pathogens or by increased symbiotic bacteria
(Duvallet et al. 2017, Olesen & Alm 2016). Measuring bacterial
diversity and abundance alone cannot supply sufficient informa-
tion to make a decision for this question (Maher et al. 2019). To
better understand the relationship between bacterial communities
and coral disease, the first step is to investigate the role of environ-
mental factors on abundance and diversity of symbiotic bacteria.
Generally, increasing seawater temperatures have been linked with
alterations in the bacterial composition which can cause infections
and disease in corals (Seonock et al. 2017) but there is a lack of
information about low-temperature stress.
Previous studies have been documented that Proteobacteria
is typically dominated phylum in deepsea, tropical, and cold
water stony corals (Kellogg et al. 2009, Robertson et al. 2016).
Additionally, in some samples, Spirochaetes (van de Water
et al. 2016) and Tenericutes (Holm & Heidelberg 2016)were
the most abundant phyla. In this study, sequencing of a partial
of the 16S rRNA marker provided us a dataset to identify
differences in bacterial communities between different thermal
culture conditions. As observed, rapid cooling could change the
bacterial composition and diversity in Cg. According to our
results, Tenericutes and Firmicutes have been replaced with
Proteobacteria and Bacteroidetes by cooling stress, while there
was non-significant change in bacterial community’s structure
after cooling in Ig, statistically. Furthermore, bacterial families,
including Rhodobacteraceae, Vibrionaceae, Flavobacteriaceae,
Burkholderiaceae, and Campylobacteraceae were formerly
reported in high abundance in diseased corals (Daniels et al.
2015,Weileret al. 2018). Within this group, pathogenicity of
Rhodobacteraceae is considerable (Roder et al. 2014, Sunagaw
et al. 2009). In our data, three families of Rhodobacteraceae,
Vibrionaceae, and Flavobacteriaceae were reported.
Interestingly abundance and diversity of these three families
increased after rapid cooling in constant temperature condi-
tions, meanwhile their increase was not noticeable in Ig.
In this study, rapid cooling treatments completely represented
different consequences in different groups. While rapid cooling
could change the bacterial composition in Cg, inconstant condi-
tion maintained bacterial abundance against cooling stress.
Same observations were recorded using PCoA in genus and
OTU levels. Both treatments of Cg were strongly divided into
two clusters, and treatments of Ig were placed in single one.
This evidenced that long-term temperature changes can provide
suitable adaptation situations for bacterial communities to prevent
the effect of short-term changes. Weiler et al. (2018) proved the
bacterial compositions of seawater were dissimilar with commun-
ities of host corals. We cautiously suggest that environmental
Table 5. Mean values (±SD) of Chao index and Shannon index for bacterial
communities under different treatments. (Cg: constant group, Ig: inconstant
group).
Treatment Chao index Simpson index
Cg (control) 489.1
(±221.58)
0.28
(±0.334)
Cg (cooling) 506.5a
(±73.41)
0.09a
(±0.027)
Ig (control) 435.3
(±109.35)
0.25
(±0.203)
Ig (cooling) 328.4a
(±33.39)
0.32a
(±0.097)
Same letter in each column shows significant difference (p<0.05).
Figure 8. Mean values (±SD) of Chao index and Shannon index for bacterial com-
munities under different treatments. (Cg: constant group, Ig: inconstant group).
Figure 7. Relationships between bacterial diversity and groups/treatments using
principal coordinate analysis (PCoA) based on the OTUs level.
Journal of Tropical Ecology 7
https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0266467421000109
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alterations may cause primary symbiotic communities structure;
and in this condition, bacteria in surrounding seawater cannot play
an important role in new communities’composition.
Conclusion
In this study, we noted the soft coral S. trocheliophorum symbionts
association during long-term temperature adaptation and its
response to rapid cooling changes. Because examined individuals
have been originated from single specimen, consequently the
results can be only referred to host response to temperature
changes. Our results show that microbial communities’composi-
tion is directly related to water temperature conditions.
Symbiodiniaceae composition was strongly adapted with long-
term temperature acclimation of hosts while there was no signifi-
cant difference in their diversity and abundance after rapid cooling.
On the other hand, temperature compatibility has different effects
on the bacterial communities. Our findings prove that bacterial
composition of S. trocheliophorum that cultured under constant
temperature conditions can be significantly altered with rapid
cooling stress while long-term acclimation under inconstant tem-
perature conditions increased coral adaptation ability to sustain its
microbial communities’structure. Overall, it can be hypothesised
that long-term adjustment following inconstant thermal state in
nature provides adaptive conditions which may protect
Symbiodiniaceae and bacterial communities of corals against rapid
temperature decreasing during seasonal typhoons and internal
waves. Although rapid cooling stress has been suggested as a
key factor in increasing the incidence of disease in corals via
increasing abundance and diversity of pathogenic bacteria, long-
term acclimation under temperature range can greatly reduce
the risk of infection after rapid cooling stress rather than constant
thermal conditions.
In conclusion, temperature changes in the experimental states
can provide better symbiotic adaptation between microbial com-
munities and corals. This adaptation can play a protective role
for Symbiodiniaceae and bacterial compositions against cold stress
and can protect corals from disease. Additional experimental stud-
ies on different thermal conditions are needed to get more infor-
mation about the relationship between thermal adaptations and
environmental stress on coral microbial communities’structure.
Acknowledgments. We thank Prof. Benayahu for his assistance in species
identification.
Financial support. This work was supported by Sanya Science and Technology
Industry Information Bureau under Grant 2019YD06 and Hainan Province
Science and Technology Department Key Research and Development
Program (ZDYF2019154).
Supplementary material. To view supplementary material for this article,
please visit https://doi.org/10.1017/S0266467421000109
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