VIETNAM NATIONAL UNIVERSITY OF AGRICULTURE

FACULTY OF BIOTECHNOLOGY
----------  ----------

GRADUATION THESIS
TITLE:
“COMPARATIVE ANALYSIS OF MICROBIAL
COMMUNITIES ASSOCIATED WITH ACROPORA
FORMOSA AND SEDIMENT IN PHU QUOC ISLAND.”

Hanoi - 2022


VIETNAM NATIONAL UNIVERSITY OF AGRICULTURE

FACULTY OF BIOTECHNOLOGY
----------  ----------

GRADUATION THESIS
TITLE:
“COMPARATIVE ANALYSIS OF MICROBIAL

COMMUNITIES ASSOCIATED WITH ACROPORA
FORMOSA AND SEDIMENT IN PHU QUOC ISLAND.”

Student name

: NGUYEN PHAM DAN TRUONG

Class

: K63CNSHE

Student’s code

: 637372

Supervisor

: NGUYEN HUY DUONG, MSc.
NGUYEN VAN GIANG, Assoc. Prof.

Department

: MICROBIAL TECHNOLOGY

Hanoi - 2022


COMMITMENT
I hereby declare that the data and results stated in the thesis are honest and have
never been published by anyone in other studies.
In the references section, the graduations with references to papers and action
information are mentioned.
I am completely responsible for the data of this thesis.
Hanoi, January 9th, 2023
Sincerely

Nguyen Pham Dan Truong


i


ACKNOWLEDGEMENTS
Above all else, I would like to express my heartfelt gratitude to MSc. Nguyen Huy
Duong, an officer of Bioinformatics Department at the Institute of Biotechnology of the
Vietnam Academy of Science and Technology, who is my thesis advisor and has also
provided me with invaluable guidance, input, and support throughout the thesis work.
Following that, I'd want to offer my grateful to PhD. Bui Van Ngoc with researchers
at the Bioinformatics Department at the Institute of Biotechnology of the Vietnam
Academy of Science and Technology, have assisted, provided technical support and
imparted valuable knowledge as well as research experience. The knowledge and skills
gained would be beneficial in the future it had been a warm and fruitful experience.
It would not have been possible to complete this project without the enthusiastically
guidelines, cordial supporting of Assoc. Prof. Nguyen Van Giang, Head of Department of
Microbiology Technology at the Vietnam National University of Agriculture, who created
opportunities for me to study and work directly at the Bioinformatics Department.
Without the enthusiastic facilitation of the Board of Directors at Vietnam National
University of Agriculture and the teachers of Biotechnology falcuty, I would not have been
able to acquire not only the professional foundation necessary to complete this report, but
also the wealth of experience that has helped me take my first confident steps along my
chosen career path.
I would have to thank all the seniors in the lab, who also helped me during the
preparation of this thesis. To wrap up, I'd want to express my gratitude to my family and
all who have journeyed with me, encouraged me, and shared in my experiences.
I sincerely thank you!

ii



Hanoi, Janury 9th, 2023
Sincerely

Nguyen Pham Dan Truong

iii


Table of Contents
COMMITMENT ........................................................................................................ i
ACKNOWLEDGEMENTS ...................................................................................... ii
LIST OF TABLES ................................................................................................... vi
LIST OF FIGURES ................................................................................................ vii
LIST OF ABBREVIATIONS ................................................................................ viii
ABSTRACT ............................................................................................................. ix
CHAPTER 1. INTRODUCTION ..............................................................................1
1.1 State of problem ................................................................................................1
1.2 Purpose ..............................................................................................................3
1.3 Research contents .............................................................................................3
CHAPTER 2. LITERATURE REVIEW ...................................................................4
2.1 Coral reefs .........................................................................................................4
2.1.1 Coral and coral reef ....................................................................................4
2.1.2 Functional importance of coral reefs ..........................................................5
2.1.3 The current situation of coral reefs .............................................................5
2.2 The coral microbiome .......................................................................................6
2.2.1 The coral holobiont: a multi-partite symbiotic organism ...........................6
2.2.2 Microbiota of healthy corals .......................................................................7
2.3 Microbial identification methods in coral reefs ................................................8
2.3.1 Culture-based methods ...............................................................................8
2.3.2 Methods for unculturable microbes ......... Error! Bookmark not defined.

2.4 Bioinformatics analysis of metagenomics ........................................................9
2.4.1 Methods in metagenomics ........................................................................11
2.5 Current situation of domestic and international research ...............................13
2.5.1 International research................................................................................13
2.5.2 Domestic research .....................................................................................14
CHAPTER 3. MATERIALS AND METHODS .....................................................16
3.1 Materials .........................................................................................................16
iv


3.2 Methods...........................................................................................................17
3.2.1 Total DNA extraction for 16S rRNA survey............................................17
3.2.2 Next-generation sequencing .....................................................................17
3.2.3 Bioinformatics approach...........................................................................18
CHAPTER 4. RESULTS .........................................................................................20
4.1 Enhancing data reliability ...............................................................................20
4.1.1 Raw read quality profiles ..........................................................................20
4.1.2 Obtaining cleaned and chimera-free sequences .......................................23
4.2 Data exploration ..............................................................................................25
4.2.1 Archaeal data ............................................................................................25
4.2.2 Bacterial data ............................................................................................32
CHAPTER 5. CONCLUSIONS AND RECOMMENDATIONS ...........................41
5.1 Conclusions .....................................................................................................41
5.2 Recommendations ...........................................................................................41
CHAPTER 6. REFERENCES .................................................................................42
SUPPLEMENTARY MATERIALS .......................................................................49

v



LIST OF TABLES
Table 2. Overview of modern sequencing technologies ................................................... 11
Table 3. Sample name, sample abbreviation and sample collection location ................... 16
Table 4.1. Abundance of archaeal phyla in the Acropora formosa mucus and the sediment
(Abundance > 0.5%) .......................................................................................................... 27
Table 4.2. Abundance of archaeal genera in the Acropora formosa mucus and in the
sediment (Abundance > 0.5%) .......................................................................................... 28
Table 4.3. Statistical summary for alpha diversity indices for archaeal communities ...... 31
Table 4.4. Abundance of bacterial phyla in the Acropora formosa mucus and in the
sediment (Abundance > 0.5%) .......................................................................................... 34
Table 4.5. Abundance of top 10 bacterial genera in the Acropora formosa mucus and in
the sediment (Abundance > 0.5%) .................................................................................... 36
Table 4.6. Statistical summary for alpha diversity indices for bacterial communities ..... 37

vi


LIST OF FIGURES
Figure 2. Acropora formosa coral. ...................................................................................... 4
Figure 4.1. Forward read’s quality score of the archaeal data when sequencing. ………20
Figure 4.2. Reverse read’s quality score of the archaeal data when sequencing. …….....21
Figure 4.3. Forward read’s quality score of the bacterial data when sequencing………..22
Figure 4.4. Reverse read’s quality score of the bacterial data when sequencing. ……….23
Figure 4.5. Quantity of reads that were kept after filtering step in the archaeal data…....24
Figure 4.6. Quantity of reads that were kept after filtering step in the bacterial data.. ..... 25
Figure 4.7. Composition of microbiota at phylum level…… ……………………………26
Figure 4.8. Composition of microbiota at genus level. ..................................................... 28
Figure 4.9. Alpha diversity of archaeal biomes. …………………………………………30
Figure 4.10. Beta diversity of the archaeal community.. .................................................. 32
Figure 4.11. Composition of microbiota at phylum level. ................................................ 33

Figure 4.12. Composition of microbiota at genus level. ................................................... 35
Figure 4.13. Alpha diversity of bacterial community. ...................................................... 38
Figure 4.14. Beta diversity of the bacterial community.. .................................................. 40
Supplementary Figure 1.
Supplementary Figure 2.
Supplementary Figure 3.
Supplementary Figure 4.
Supplementary Figure 5.
Supplementary Figure 6.

Composition of microbiota at Class level. ............................... 53
Composition of microbiota at Order level. .............................. 54
Composition of microbiota at Family level. ............................ 55
Composition of microbiota at Class level. ............................... 56
Composition of microbiota at Order level. .............................. 57
Composition of microbiota at Family level. ............................ 58

vii


LIST OF ABBREVIATIONS

Abbreviation

Full word

AF

Acropora formosa


ANOSIM

Analysis of similarities

ARISA

Automated

Ribosomal

Intergenic

Spacer

Analysis

ASV

Amplicon sequence variant

DGGE

Denaturing Gradient Gel Electrophoresis

DNA

Deoxyribonucleic Acid

NGS


Next-Generation Sequencing

OTU

Operational taxonomic unit

PCoA

Principal coordinates analysis

PCR

Polymerase Chain Reaction

QC

Quality score

rRNA

Ribosomal ribonucleic acid

SE

Sediment

SST

Sea surface temperatures


T-RFLP

Terminal

Restriction

Polymorphism

viii

Fragment

Length


ABSTRACT
Coral reefs are among the most productive, complex and highly diverse ecosystems
on the planet. Corals include a diverse range of microorganisms in their mucus, skeleton,
and healthy tissue. These organisms, which include microalgae, bacteria, and archaea,
assist corals in a variety of ways, including photosynthesis, nutrition intake, and infection
resistance. Little is known about the similarities and differences in microbial diversity and
composition across prokaryotic kingdoms and coral reef biotopes that are geographically
near one another. In this study, we compared archaea and bacteria communities in two
distinct biotopes: the coral Acropora formosa and sediment in Phu Quoc Island using 16S
rRNA metagenomics. Comparative analysis in composition at phylum level showed that
Nanoarchaeota dominated the archaeal biomes in the coral mucus and the sediment, and
there were significant differences in composition between them (p-value = 0.03 < 0.05). In
bacterial data. Proteobacteria dominated in both the coral mucus and the sediment at the
phylum level and there were significant differences in composition between them (p-value
= 0.01 < 0.05). Overall, the alpha diversity in the bacterial data is higher than in the archaeal

data. In bacterial data, the composition diversity in the coral mucus and in the sediment is
significant different through 4 indices Observed (p-value = 0.009), Chao1 (p-value =
0.009), Shannon (p-value = 0.009), Simpson (p-value = 0.009). The archaeal data showed
tthe composition diversity in the coral mucus and in the sediment with significant
differences through 4 indices Observed (p-value = 0.009), Chao1 (p-value = 0.009),
Shannon (p-value = 0.009), Simpson (p-value = 0.009). The beta diversity in both archaeal
data and bacterial data showed significant differences of the coral mucus community and
the sediment community (p-value = 0.006 in archaeal data and p-value = 0.009 in bacterial
data). Biotope proved to be the main identifiable factor affecting composition. However,
within the framework of this study, it stops at the level of genus classification of bacteria
in the composition. Other molecular marker genes must be used in conjunction with
functional genes for species or subspecies classification, as well as technologies such as
long read sequencing or whole genome sequencing.

ix


CHAPTER 1. INTRODUCTION
1.1 State of problem
Coral reefs are one of the most diverse ecosystems on the planet, contributing
significant economic, social, and ecological value. In recent years, due to the change of the
environment and the impact of humans such as overexploitation, vandalism, coral mining,
tourism, etc., many coral reefs in the world have experienced the bleaching phenomenon,
of which some coastal reefs in Vietnam are no exception. As a result, research and coral
protection are critical for marine biodiversity, which plays an important political, social,
and economic role and is a top priority for the country.
The coral microbiome is diverse and makes up the largest component of the
organisms that live on corals and reefs; it is estimated that there are more than 100 million
bacteria per square centimeter of a healthy coral. There are approximately a billion bacteria
and 10 billion viruses per liter of seawater in coral reef areas. Corals have a lot of organisms

in their mucus, skeleton, and healthy tissue. These organisms, such as microalgae, bacteria,
and archaea, help corals in many ways, such as photosynthesis, getting nutrients, and
fighting off infections. Microbial biomes that live on corals have both beneficial and
harmful effects on corals, and between them there is an extremely complex relationship.
For example, in the coral Acropora tenuis, the bacterial genus Pseudoalteromonas can
synthesize antibiotics that inhibit opportunistic microorganisms such as Vibrio
coralliilyticus. Archaea also play key roles in processes such as the geochemical cycling
of carbon, nitrogen, and sulfur. This cycling activity, particularly the nitrogen cycle, is
critical for oligotrophic coral reefs in order to breakdown organic matter and maintain high
levels of primary production. Nitrogen is crucial for organisms and ecosystems because it
is an essential component of proteins, nucleic acids, and cell wall elements, and it inhibits
marine environment primary productivity. Therefore, the microbial identification will help
us learn more about the variety and interactions of all the microbial biomes in the coral
mucus layer.

1


Microorganisms are typically identified and evaluated by scientists by growing
them in the appropriate environment and then determining their identity based on
biochemical and physiological characteristics, combined with sample observation on
electron microscopy, confocal microscopy, and fluorescence microscopy to assess the total
number of microorganisms in the environment, as well as partially identify microorganisms
based on known microbial morphology. However, the number of cultured microorganisms
on the disk exhibited an anomaly when it was less than the total number of microbial
microorganisms under the microscope. Therefore, the culture method can only identify a
small part of the microorganisms capable of growing well in the culture medium, so it is
not possible to give an overview of the microbial biome in corals. Methods for separating
genetic units such as: Denaturing Gradient Gel Electrophoresis (DGGE), Terminal
Restriction Fragment Length Polymorphism (T-RFLP) and Automated Ribosomal

Intergenic Spacer Analysis (ARISA) used before sequencing using the Sanger method.
Although the DGGE, T-RFLP, and ARISA methods combined with Sanger sequencing
produce good results, it is possible to completely evaluate environmental microorganisms.
But these methods are complex and time-consuming.
In recent years, metagenomics has emerged as a new trend commonly used in
microbial ecology, especially in research involving in-depth coverage of microbial biomes.
This approach supports the analysis of microbial strains that cannot be cultured in the
laboratory because it focuses on microbial genetic analysis through markers in highly
conservative gene regions so that they can be easily classified. Moreover, the
metagenomics method is increasingly developed with the next-generation sequencing
method, Next-Generation Sequencing (NGS), and also integrates a number of
bioinformatics tools and programming languages to save research time, visualize research
data, and have high accuracy.
Therefore, 16S rRNA metagenomics analysis is an effective method for evaluating
microbial diversity and composition in Acropora formosa mucus and sediment. Stemming
from the above reasons, the implementation of the study “Comparative analysis of

2


microbial communities associated in Acropora formosa mucus and sediment in Phu Quoc
Island.” is extremely important and urgent.

1.2 Purpose
Determination of diversity and identification of archaeal and bacterial communities
residing in Acropora formosa mucus and sediment using metagenomics technology.
1.3 Research contents
 Analyzing and processing data, data analysis, and visualization of data obtained by
metagenomics approach and R programming language.
 Analysis of diversity and identification of microorganisms residing in coral mucus

and sediment from the phylum to genus level.

3


CHAPTER 2. LITERATURE REVIEW
2.1 Coral reefs
2.1.1 Coral and coral reef
Corals are marine organisms of the phylum Cnidaria, class Anthozoa which comes
from the Greek words άνθος (ánthos; "flower") and ζώα (zóa; "animals"), hence ανθόζωα
(anthozoa) = "flower animals", a reference to the floral appearance of their perennial polyp
stage. Coral reefs are colonies of stone-like, hard-calcified structures formed by corals.
Corals are polyps in their individual forms, connected by living tissue. Each polyp has a
cup-like shape and a ring of tentacles around a central opening. At the end of each tentacle
is a stinging cell that helps the polyp defend itself and catch zooplankton to feed on. Coral
polyps are made up of two layers of cells that are covered by a mucus layer and a massive
calcified skeleton. Most corals are stony - or reef-building corals - meaning they stick to
stone or other structures and slowly form a calcified structure, usually at a rate of a few
centimeters per year (Anderson et al., 2017).

Figure 2. Acropora formosa coral. (Monti, 2015) This species is a member of the
Acroporidae family

4


Reef-building corals can be found in tropical waters. They are considered to be the
most highly diverse ecosystem on the planet, containing around 25% of all macroscopic
life in the ocean (Plaisance et al., 2011). Because of their diversity, they are vital to the
survival of many species around them, including thousands of species of fish, algae,

sponges, crustaceans, and others.
2.1.2 Functional importance of coral reefs
Tropical coral reef ecosystems are referred to as the ocean's rainforests since they
cover only a small portion of the bottom surface area but are estimated to support more
than 25% of all marine species (Connell, 1978). In addition to providing habitat and shelter,
reefs are important for nutrient cycling and carbon and nitrogen fixation (which provide
crucial nutrients to the marine food chain). Bacteria on coral reefs play an important role
in reef nutrient cycling, which supports highly productive reef-based fisheries as well as
coastal protection and tourism. Reefs also give paleontological time scale records of
climatic events, as well as more modern records of major storms and human impacts
recorded by changes in coral growth patterns. These records are extremely valuable for
predicting coral reef resilience in the future. The importance of coral reefs to the economy
cannot be overstated. They are frequently valued in the billions or even the trillions of
dollars by the tourism and fishing industries(Costanza & Limburg, n.d.).
2.1.3 The current situation of coral reefs
Although, coral reefs are extremely sensitive. Multiple natural and manmade
stressors, including but not limited to predation, physical disturbance, competition,
pollution, nutrient enrichment, overfishing, and climate change, have contributed to the
declining coral reefs degradation (Hoegh-Guldberg et al., 2007; Hughes et al., 2003;
Zaneveld et al., 2016). Ocean acidification and, in particular, rising ocean temperatures
lead to their rapid degradation. Sea surface temperatures (SST) that surpass the thermal
threshold of coral cause the symbiotic association between the coral host and its
endosymbiotic Symbiodinium partners to break down. Elevated SST’s also causes changes

5


in the populations of bacteria that are associated with corals. These bacteria are known to
play a role in the health of the coral holobiont.(D. Bourne et al., 2008). Prolonged periods
of higher-than-normal SST's can cause widespread coral death, with devastating

consequences for the numerous fish and other marine species that rely on corals for habitat
and food. Along with warming, Ocean acidification is progressing due to CO2 released into
the atmosphere by human activities, which is changing the carbonate chemistry of surface
waters. Ocean acidification is regarded as a major danger to coral reef ecosystems because
it limits the supply of carbonate ions required by reef-building corals to produce their
skeletons(Mollica et al., 2018).
In recent years, coral disease has been identified as one of the major dangers to the
coral reef ecosystem (Pollock et al., 2011). These stressors and their interactions have
resulted in the global decline of overall coral reef health as well as ecosystems (Brandl et
al., 2020). Bleaching is the most common cause of coral degradation. Coral bleaching
commonly occurs in a cloudless sky and the sun is hot and emits a lot of radiation, causing
the sea temperature to increase over average. Coral bleaching is becoming more common
as temperatures rise for an extended period of time, and it is spreading across coral reefs
(Brown, 1997). Corals eject their symbiotic partner during a bleaching event, resulting in
pigmentation loss, increased vulnerability to disease, and, if the bleached state persists,
coral death (Figure 2) (Hughes, Kerry, et al., 2017).
Without our dramatic reductions in CO2 emissions, the majority of coral reefs are
unlikely to survive much longer, and entire ecosystems may collapse. Meanwhile,
researchers can do everything they can to assist corals become more resistant to climate
change, but any solution will only be temporary (Hughes, Barnes, et al., 2017).
2.2 The coral microbiome
2.2.1 The coral holobiont: a multi-partite symbiotic organism
Corals are coevolved symbiotic communities of polyps, unicellular algae, and
microorganisms. This complex symbiotic assembly was termed a "holobiont" (Rohwer et

6


al., 2002). The use of this term to describe corals broadens the original definition, which
was intended to describe eukaryotic organisms, which were themselves the result of

reticulate evolution resulting from a merger (rather than hybridization) of organisms of
different lineages, with each holobiont partner maintaining their own genomes (Mindell,
1992).
2.2.2 Microbiota of healthy corals
Corals are made up of two layers of cells, the epidermis and gastrodermis, which
are joined by a massive, porous calcium carbonate skeleton. These structures also interact
with various forms of microbial life, and the coral holobiont has microbial representatives
from all three kingdoms — Bacteria, Archaea, and Eukaryota — as well as a variety of
viruses.
2.2.2.1 Symbiodinium
Karl Brandt observed in 1883 that stony corals were connected with intracellular
microscopic algae that were later identified as dinoflagellates (Baker, n.d.). These algae
were first cultured in the 1950s, yielding the new genus Symbiodinium.
Symbiodinium helps their hosts get most of the energy they need by giving the coral
carbon that has been fixed by photosynthesis (Falkowski et al., 1984). Another effect of
algal photosynthesis in this system is the generation of enormous amounts of molecular
oxygen, which allows for efficient respiration by the coral and associated prokaryotic
microorganisms. A single coral species can harbor many types of Symbiodinium, with
distinct taxa present at different depths (LaJeunesse et al., 2003).
2.2.2.2 Bacteria
Corals provide three habitats for bacteria: the surface mucus layer, coral tissue
(including the gastrodermal cavity) and the calcium carbonate skeleton, each of which has
its own bacterial population (D. G. Bourne & Munn, 2005; Koren & Rosenberg, 2006). At
first, research on coral microbiology focused on the mucus layer of the coral structure,

7


using traditional methods of culturing. These studies found that this layer is home to diverse
and abundant beneficial bacteria (Ducklow & work(s):, 1979; Shashar et al., 1994), such

as bacteria that fix nitrogen (Lesser et al., 2004; Shashar et al., 1994; Williams et al., 1987)
and bacteria that break down chitin (Ducklow & work(s):, 1979).
Coral skeletons are porous structures that are host to a wide range of bacteria. This
endolithic colony is thought to meet 50% of the coral's overall nitrogen needs (Pernice et
al., 2020). Organic chemicals (generated by photosynthesis) are supplied to coral tissue by
cyanobacteria in the skeleton of Oculina patagonica (Fine & Loya, 2002). These bacteria
may be critical for coral survival when it loses its endosymbiotic algae (Schlichter et al.,
1995), a disease referred to as coral bleaching.
2.2.2.3 Archaea
Using culture-independent approaches, the presence of diverse and abundant
Archaea communities in hard corals has been demonstrated (Kellogg, 2004). Direct cell
counts with Archaea-specific probes indicate that many corals have more than 107 archaeal
cells per cm2 of coral surface. Recent research, however, reveals that Archaea do not form
particular associations with corals. Little is known about the biological function of Archaea
in the coral holobiont at this time.
2.3 Microbial identification methods in coral reefs
Knowing which microbes live in coral reefs is important for figuring out how the
strains of the host and coral reef microbiota work together.
2.3.1 Culture-based methods
Following Robert Koch's invention of plating techniques for microbial culturing in
1881, microbiology remained fully culture dependent throughout a century. Microbe
cultivation under verified laboratory conditions remains hard, laborious, and timeconsuming for a variety of reasons. Microorganisms that are low in abundance and grow
slowly may be outcompeted by species that are abundant and grow rapidly. Others may

8


fail to grow on standard media due to unfavorable conditions such as pH, redox state,
temperature, or lack of nutrients. A study shows that less than 20% of the environmental
bacteria can be grown under controlled conditions (Ward et al., 1990). This method is

labor-intensive, time-consuming, and often insufficient for distinguishing the strains
phenotypically. These limitations are quite crucial in fields where rapid and accurate
identification is important, such as medical diagnosis, food quality control, pharmacology,
and even criminal investigations (Buszewski et al., 2017; Fan et al., 2016).
2.3.2 Culture-independent methods
Because of the limits of culture-based identification studies, there has been a lot of
interest in alternative methodologies known as culture-independent methods or molecular
methods. Molecular fingerprinting is a method of generating patterns of bands from DNA,
either directly from a sample or through PCR amplification of specific locations
appropriate for studying bacterial composition (Forbes et al., 1991; Garibyan & Avashia,
2013). . The widely used fingerprinting methods are denaturing gradient gel
electrophoresis, temperature gradient gel electrophoresis, and terminal restriction fragment
length polymorphism. These methods rely on the separation of DNA fragments based on
their chemical or physical properties into a pattern, using gel electrophoresis. However, the
absence of taxonomic mapping of communities and underestimation of communities due
to band overlapping are seen as major limitations of these approaches (Costa & Weese,
2019).
2.4 Bioinformatics analysis of metagenomics
Metagenomics analysis is based on the function and sequence of microbial genomes
in an environmental sample's community (Riesenfeld et al., 2004). Metagenomics is an
approach to studying microorganisms that grow in ecosystems without requiring culture to
learn about their physiology and genetics. Metagenomics has evolved into a potent
technique for researching microbial communities in any environment without the

9


requirement for laboratory culture, allowing researchers to better understand community
structure and physiological value in the ecosystem.
Advantages of metagenomics technique:

 The microorganisms present in the environment can be rapidly identified
through genome extraction from the environment and 16S rRNA sequencing
to identify microorganisms,
 The proportion of genomes collected directly from environmental samples is
significantly higher than the proportion obtained through traditional
microbial isolation and culture, which includes both cultured and uncultured
microbial genomes. From there, the microbial community can be evaluated
thoroughly,
 In addition, as compared to traditional methods, the metagenomics technique
allows researchers to use bioinformatics tools and large databases to save
time and minimize the size of experiments (Vakhlu et al., 2008).
Applications of metagenomics technique:
Metagenomics is a growing field in microbial ecology that allows us to learn about
the genomes of most microorganisms (including unculturable microorganisms) in any
given environment, while we only know approximately 1% of isolated and cultured
microorganisms. This method has enhanced our understanding of the world of uncultivated
microorganisms and helped in the discovery of new genes. Currently, metagenomics
techniques are often used to study the microbial community in special environments such
as gastric juice, coral mucus, hot water, and so on, in order to better understand the
relationship between microorganisms and the environment, as well as the microorganism's
association with the host. Metagenomics, on the other hand, provides an infinite resource
for creating novel genes, finding enzymes and biocatalysts, and natural products from
uncultivated microorganisms, all of which can have a significant effect on applications in
industries and biotechnologies.

10


2.4.1 Methods in metagenomics
2.4.1.1 Sequencing

High-throughput DNA and RNA sequencing have taken the lion's share of the
methods used in almost all fields of biological research in recent years (Park & Kim, 2016).
The application of whole-genome or transcriptome sequencing technologies has absolutely
transformed how we approach designing modern experiments, especially in microbial
ecology, where many organisms that could not be cultured in laboratory settings have now
been identified and their genome sequenced. In that revolution, one should not overlook
metabarcoding, which has long been used to characterize the taxonomic distribution and
differences across microbial communities and to compare microbial ecosystems under
different conditions.
2.4.1.2 Sequencing platform
There are two types of sequencing techniques: short-read sequencing and long-read
sequencing. Table 2.1 provides an overview of the current platforms.
Table 2. Overview of modern sequencing technologies
Platform
Illumina MiSeq
Illunina NovaSeq
Pacbio Sequel
Oxford Nanopore MinION
Oxford Nanopore GridION
Oxford Nanopore PromethION

Read length
2*150-300
2*50-250
30kb
up to mb
up to mb
up to mb

Throughput

15Gbp
up to 3Tbp
20Gbp
15Gbp
250Gbp
up to 10Tbp

The Illumina platform is currently the most popular for metagenomics, due to the
high throughput required for recovering genomes of medium and low abundance species,
but the Oxford Nanopore MinION's availability and inexpensive cost may make it a
contender for field sequencing in the near future.
2.4.1.3 Analysis and process 16S rRNA metagenomics data

11


Following Illumina sequencing, sequence data are often in FASTQ format, which
includes both nucleotide sequences and their quality values in a single file, with each
nucleotide in the sequence corresponding to its quality score. Normally, Illumina
sequencing data is cut at the 3' end, but the removed segment does not have a specific
length. Furthermore, the noise at the 5' end and the presence of the adapter must be checked
and removed from the sequence (Bragg & Tyson, 2014). Currently, popular tools for
evaluating quality scores, including FastQC, FASTX toolkit, and others, are frequently
used to verify the initial raw quality of NGS data (Trivedi et al., 2014), before removing
low-quality sequences with the TrimGalore or Cutadapt toolkits, if the sequence contains
an adapter segment (Bragg & Tyson, 2014). For most short-read sequencing methods, since
sequence quality degrades towards the end of the sequence, to enhance sequence reliability,
sequence pairs are overlapped together. Using tools like MOTHUR, QIIME, and DADA2
or standalone tools like Usearch and FLASH to do this (Hugerth & Andersson, 2017).
Before data processing, chimera analysis and detection will be performed to remove all

sequence segments that are not part of the original biological sequence. Several algorithms
and tools are proposed to identify and remove these chimeras, such as UCHIME, Perseus,
and Decipher. All of these tools use sequence frequency information to detect chimeras
(Kim et al., 2013). Depending on the processing algorithm, the sequences will then be
grouped into operational taxonomic unit (OTU) clusters, or amplicon sequence variant
(ASVs) to map with the reference gene dataset in the database, such as the RDP database
maintained by the University of Michigan's Center for Molecular Ecology, or SILVA,
maintained by the Microbial Genomics and Bioinformatics group of the Institute of Marine
Microbiology Max Planck (Hugerth & Andersson, 2017). After assigning classifications
to the OTUs/ASVs, the composition of microorganisms is represented by graphs for
analysis. Besides, from OTU/ASV data, the diversity of microbial composition in each
sample (alpha diversity) was also evaluated through indicators such as OTU abundance,
abundance (Chao1), and diversity (Shannon). Accordingly, the difference in composition
between two different sites or two different sample conditions (beta diversity) was also

12


evaluated to give an overview of the microbial diversity in the communities (Hugerth &
Andersson, 2017).
2.5 Current situation of domestic and international research
2.5.1 International research
Acropora was discovered and classified quite early on. Therefore, Acropora corals,
such as Acropora sp., have been studied widely in laboratories around the world to evaluate
the effect of CO2 pressure and temperature on the boron isotopic composition of corals
(Reynaud et al., 2004) or or the effects of light and temperature on the ratio of Sr/Ca and
Mg/Ca in corals (Reynaud et al., 2007). Studies on the correlation between temperature
and the occurrence of bleaching phenomenon of Acropora sp. (Muller et al., 2008),
together with environmental agents leading to bleaching of Acropora species
(Hoogenboom et al., 2017), and the metabolism of symbionts during heat stress and

bleaching in coral Acropora aspera have also been studied in recent years (Hillyer et al.,
2017).
Also, Kushmaro et al. (2009) found that the spread of Vibrio shiloi was one of the
reasons why O. patagonica was bleaching. Because when isolated V.shiloi only appeared
in bleached corals but not in healthy corals. The invasion mechanism of V. shiloi in P.
patagonica was also extensively studied afterwards, and it was found that this bacterium
can penetrate the coral mucus layer, attach to the β-galactoside receptor on the coral
surface, and penetrate the epidermis. From there, V.shiloi will multiply and secrete toxins
that kill algae and affect corals. However, V. shiloi cannot infect, reproduce or survive in
corals during the winter period. Another species of Vibrio coralliilyticus has also been
isolated from bleached Pocillopora damicornis corals at Zanzibar Reef. McGrath and
Smith then isolated culturable bacteria and found that the genus Vibrio appeared in 20% of
healthy corals and increased to 40% when the corals were bleached. They can be increased
by more than 60% in cultured microorganisms once they have reached the peak of the
bleaching process (Rosenberg et al., 2009).

13


M. Lins-de-Barros et al. (2009) yielded 354 distinct microbial OTUs of microbe
communities associated with the reef-building corals Siderastrea stellata and Mussismilia
hispida. Crenarchaeota dominated archaeal communities, while Proteobacteria was the
most abundant bacterial phylum, dominated by alpha-Proteobacteria. Polónia et al. (2013)
analyzed the composition of the Archaea in different biotopes in the Kepulauan Seribu
Reef and found that Crenarchaeota dominated the archaeal community of both sponge
species and sediment, while Euryarchaeota dominated the seawater community. The
number of operational taxonomic units (OTUs) was highest in sediment and
seawater biotopes and substantially lower in both sponge hosts.
Although the microorganisms in the biomes and in the environment are quite diverse
and complex, However, due to the limitations of the culture method, only 0.01–0.01% of

microorganisms have been isolated from the environment. In recent decades, the
development of a metagenomics method that can extract microbial DNA directly from the
environment has given a better overview of microbial biomes in the environment
(Handelsman, 2007). The analysis and identification of microorganisms based on the 16s
rRNA gene. With the development of technology, the use of Sanger sequencing is moving
to next-generation sequencing platforms with better equipment from different companies
(Roche 454, Illumina, Ion Torrent PGM) with more economy and faster sequencing
capabilities. is a powerful tool for evaluating microbial phylogeny in the metagenomics
approach (Pootakham et al., 2017). Ramu et al. (2020) used NGS to metagenomics analysis
of 16S rRNA genomes of microorganisms on the surfaces of different corals to assess the
diversity of microorganisms and look for those that predominate in different corals
(Meenatchi et al., 2020).
2.5.2 Domestic research
Many domestic scientists have long been interested in Vietnam's sea corals. Nguyen
Huy Yet et al. (1986, 1989, 1992, 1995, 1996, 1999, 2001), Lang Van Ke et al. (1989),
Nguyen Van Quan et al. (2002, 2005), and Nguyen Dang Ngai (2005) have all published
studies. Furthermore, Nguyen Ngoc Lam (2002) and Ho Van Thieu (2009) of the Nha

14