Biodiversity Data Journal :
Research Article
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Corresponding author: Badrul Munir Md-Zain (abgbadd1966@yahoo.com)
Academic editor: Anna Sandionigi
Received: 02 Jun 2021 | Accepted: 09 Feb 2022 | Published: 22 Mar 2022
© 2022 Nur Syafika Mohd-Yusof, Muhammad Abu Bakar Abdul-Latiff, Abd Rahman Mohd-Ridwan, Aqilah Sakinah Badrulisham, Nursyuhada Othman, Salmah Yaakop, Shukor Md-Nor, Badrul Munir Md-Zain
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Mohd-Yusof NS, Abdul-Latiff MAB, Mohd-Ridwan AR, Badrulisham AS, Othman N, Yaakop S, Md-Nor S, Md-Zain BM (2022) First report on metabarcoding analysis of gut microbiome in Island Flying Fox (Pteropus hypomelanus) in island populations of Malaysia. Biodiversity Data Journal 10: e69631. https://doi.org/10.3897/BDJ.10.e69631
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Flying fox (Pteropus hypomelanus) belongs to the frugivorous bats, which play a crucial role in maintaining proper functioning of an ecosystem and conservation of the environment. Bats are well-known carriers of pathogenic viruses, such as BatCov RaTG13 from the coronavirus family that share 90.55% with SARS-CoV-2, the pathogen causing recent global pandemic coronavirus disease 19 (COVID-19). However, bats’ possible role as a carrier of pathogenic bacteria is less explored. Here, using metabarcoding analysis through high-throughput sequencing, we explored the gut microbiome composition of different island populations on the east and west coasts of Peninsula Malaysia. The 16S rRNA gene in samples from Redang Island, Langkawi Island, Pangkor Island and Tinggi Island was amplified. Bacterial community composition and structure were analysed with α and β diversity metrics. A total of 25,658 operational taxonomic units at 97% similarity were assigned to eight phyla, 44 families, 61 genera and 94 species of microbes. The Proteobacteria was the dominant phylum in all populations. Meanwhile, the genera Enterobacter, Pseudomonas and Klebsiella, isolated in this study, were previously found in the rectum of other fruit bats. Our analyses suggest that Redang Island and Langkawi Island have high bacteria diversity. Thus, we found geographic locality is a strong predictor of microbial community composition and observed a positive correlation between ecological features and bacterial richness.
Flying Fox, Pteropus hypomelanus, gut microbiome, high-throughput sequencing, metabarcoding
Bats are capable of flying high and covering long distances during seasonal migrations. Bats have extraordinary adaptation and are able to inhabit a huge number of diverse ecological niches (
Early microbiome studies on wildlife focused on primates which represent only 5% of the diversity of extant mammals (
Previous studies found that Henipaviruses were the most common zoonotic pathogens in natural reservoir hosts, species of Pteropus (
Fruits are the primary diet of bats and influence the abundance of different types of bacteria in their intestinal tract due to the nutritionally-rich environment, whose bacterial composition provides information about the dietary habits and feeding behaviour of bats (
Conventional methods, such as microbial cultivation is considered inefficient, time consuming and inadequate (
As information on the distribution and diversity of microbes found in pteropodids from the Indomalaya Region is limited (
In Peninsular Malaysia, we sampled P. hypomelanus at four sites, including Dangli Island (Langkawi), Pantai Teluk Nipah in Pangkor Island (Perak), Mat Kepit in Redang Island (Terengganu) and Tanjung Balang in Tinggi Island (Johor) (Fig.
Dangli Island
Dangli Island is a small island to the north of Langkawi Island. The uninhabited Island is visible from the beach at Tanjung Rhu. It is within a small group of islets that include Gasing Island and Pasir Island. Pteropus hypomelanus can be found roosting in the trees on the two rocky outcrops on Dangli Island in the north and Lalang Island to the south of Langkawi Archipelago. This Island is classified as the most environmentally diverse amongst all sites. Its inland is mountainous and covered with mixed dipterocarp forest.
Pangkor Island
Pangkor Island is an island located in the Strait of Malacca on the west coast of Peninsular Malaysia between 04°13.0’N latitude and 100°33.0’E longitude. It is one of the most famous islands in Malaysia, 3.5 km from Peninsular Malaysia with a land area of 18 km2. This Island is classified as coastal hill forest with high conservation. The highest point is Bukit Pangkor at 371 m a.s.l. It has a population of approximately 25,000 and the major industries of the Island are tourism and fishing.
Redang Island
Redang Island is an island in Kuala Nerus District, Terengganu, Malaysia. It is one of the largest islands off the east coast of Peninsular Malaysia, which lies about 45 km from the coast of Terengganu State. Pulau Redang measures about 7 km long and 6 km wide. Its highest peak is Bukit Besar at 359 m a.s.l. It has an equatorial climate with high temperatures throughout the year, ranging from 22°C in the early morning to 34°C at noon. This Island is an important conservation site for sea turtles.
Tinggi Island
Tinggi Island is located 37 km southeast of Mersing, on the east coast of Johor with a land area of 15 km2. It rises 600 m a.s.l. It takes approximately 45 minutes to reach Tinggi Island by boat from the mainland. The inland is mostly covered by secondary lowland Dipterocarp rainforest. It has fresh water, fruits, rattan and timber. A sheltered harbour with coral reefs abounds with prolific marine life. It has a long coastline with white sandy beaches and caves. This Island has the highest residential population amongst the east coast Johor Islands, with the latest tally estimated at only 448 people, from three villages including Kampung Tanjung Balang, Kampung Pasir Panjang and Kampung Sebirah Besar.
Bacterial genomic DNA extraction was carried out using innuPREP Stool DNA Kit (Analytik Jena, Germany). The purity and concentration of DNA were confirmed by both spectrophotometric and fluorometric methods using Implen Nanophotometer and Qubit 4.0 HS Assay Kit (Life Technologies), respectively. Two rounds of polymerase chain reaction (PCR) were performed. The first PCR is amplification of the targeted locus of 16S rRNA gene. The second PCR is for indexing of purified PCR products. 16S rRNA gene was amplified by PCR using primers targeting the V3 and V4 regions. The following are the universal bacterial primer pair F515 (5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGCCAGCMGCCGCGGTAA-3’) and R806 (5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGGACTACHVGGGTWTCTAAT-3’) with Illumina adapter overhang sequences (underlined) (
The purified amplicons containing the full-length Illumina adapters and unique barcodes were quantified using quantitative PCR (qPCR). This reaction was conducted using KAPA SYBR FAST qPCR Master Mix (KAPA Biosystems, USA). A total volume of 20 µl PCR mixture was prepared that contains 10 µl KAPA SYBR FAST qPCR Master Mix, 2 µl primer premix, 4 µl indexed-amplicon and 4 µl RNase-free distilled water. The PCR reaction was performed on a Eco48 Real Time PCR system (PCRmax) under the following conditions: 95°C for 5 min, followed by 25 cycles of 95°C for 40 sec, 60℃ for 2 min, 72°C for 1 min, with a final extension step at 72°C for 7 min. Normalisation is crucial for the success of sequencing, which equalises the concentration of DNA libraries for multiplexing in order to obtain similar number of reads from each sample. Based on the qPCR and Qubit quantification data, the amplicons were normalised and pooled into a single library for NGS. The multiplexed library consists of 300 µl pooled amplicons (1.3 pM) and 200 µl PhiX Control kit (1.3 pM). The sequencing length is 2 x 151 cycles using a MiniSeq High Throughput Reagent Kit on an Illumina Miniseq platform (Illumina Inc, USA). Sequencing was conducted at the Evolutionary and Conservation Genetics Laboratory of Department of Technology and Natural Resources, Universiti Tun Hussein Onn Malaysia.
All next-generation sequence data were deposited into National Center of Biotechnology Information (NCBI), under Sequence Read Archive (SRA) accession numbers; SRR16796807, SRR16798027, SRR14798122, SRR16805065, SRR16805071, SRR16805076, SRR16805547 and SRR16805567. Quality filtering and demultiplexing of generated sequences were performed using CLC Genomic Workbench software (CLC) (Qiagen, USA). An initial assessment of quality scores of the sequencing data was conducted on FASTQ files. Aligned sequences were then clustered into operational taxonomic unit (OTUs) defined by 97% similarity and OTUs were aligned using MUSCLE tool in CLC. Rarefaction curves were then plotted with the OTUs observed with a given sequencing depth using CLC. OTUs were given taxonomic assignment using SILVA v.138 database and these trees were used for the calculation of alpha diversity indices (Chao1, Shannon, Simpson and Evenness) in all samples from each island population as described in AST 3 software (
Sample collection
A total of eight samples were collected and used in this metabarcoding analysis (Table
# |
Sample code |
Locality |
Source of isolation |
1 |
DA |
Dangli Island, Langkawi |
Intestine swabs |
2 |
DB |
Dangli Island, Langkawi |
Intestine swabs |
3 |
PB |
Pangkor Island, Perak |
Intestine swabs |
4 |
PC |
Pangkor Island, Perak |
Intestine swabs |
5 |
RA |
Redang Island, Terengganu |
Intestine swabs |
6 |
RB |
Redang Island, Terengganu |
Intestine swabs |
7 |
TA |
Tinggi Island, Johor |
Intestine swabs |
8 |
TB |
Tinggi Island, Johor |
Intestine swabs |
A total of 80,472 sequences (<300 base pairs) in bacterial 16S rRNA gene OTUs were identified, ranging from 11,783 to 28,081 sequences from eight samples of each population (Table
Numbers of effective 16S rRNA gene sequences, numbers of observed OTUs, alpha diversity indices (Chao1, Shannon and Simpson) and Evenness for the bacterial community in four island populations.
Population |
Sequences |
OTUs* |
Chao1 |
Evenness (e) |
Shannon (H) |
Simpson (1-D) |
|
Langkawi Island |
28081 |
4413 |
1.14E+04 |
0.735 |
8.694 |
0.9997 |
|
Pangkor Island |
15362 |
811 |
7372 |
0.761 |
8.438 |
0.9996 |
|
Redang Island |
11783 |
6070 |
1.23E+04 |
0.687 |
8.916 |
0.9997 |
|
Tinggi Island |
25246 |
10849 |
6234 |
0.751 |
8.106 |
0.9995 |
|
Overall |
80472 |
25658 |
The OTUs were successfully aligned to eight phyla, 44 families, 61 genera and 94 species. The relative abundance of various microbial taxa differed significantly amongst populations. The Proteobacteria was the dominant phylum and was found across the populations (Langkawi Island, 76.15%; Pangkor Island, 80.42%; Redang Island, 52.09%; and Tinggi Island, 76.27%) (Table
Relative abundance of microbiome communities at the phylum level in different populations.
# |
Phylum |
Langkawi Island (%) |
Pangkor Island (%) |
Redang Island (%) |
Tinggi Island (%) |
1 |
Proteobacteria |
76.15 |
80.42 |
52.09 |
76.27 |
2 |
Actinobacteria |
7.53 |
0.70 |
21.62 |
0.32 |
3 |
{Unknown Phylum} Bacteria |
8.37 |
4.20 |
9.09 |
9.49 |
4 |
Firmicutes |
4.60 |
9.79 |
5.28 |
13.92 |
5 |
{Unknown}-2 |
0.00 |
2.10 |
6.88 |
0.00 |
6 |
Bacteroidetes |
3.35 |
0.00 |
4.42 |
0.00 |
7 |
{Unknown}-1 |
0.00 |
0.70 |
0.61 |
0.00 |
8 |
Fusobacteria |
0.00 |
2.10 |
0.00 |
0.00 |
Relative abundance of microbiome communities at the family level in different populations.
# |
Family |
Langkawi Island (%) |
Pangkor Island (%) |
Redang Island (%) |
Tinggi Island (%) |
1 |
Enterobacteriaceae |
13.89 |
82.68 |
4.65 |
75.75 |
2 |
Bradyrhizobiaceae |
39.35 |
3.94 |
23.70 |
0.66 |
3 |
{Unknown Phylum} Bacteria |
9.26 |
4.72 |
10.44 |
9.97 |
4 |
Micrococcaceae |
0.00 |
0.00 |
15.51 |
0.33 |
5 |
Roseobacteraceae |
0.83 |
0.00 |
11.14 |
0.00 |
6 |
{Unknown}-2 |
0.00 |
2.36 |
7.90 |
0.00 |
7 |
Pseudomonadaceae |
11.11 |
0.00 |
4.23 |
0.00 |
8 |
Streptococcaceae |
3.24 |
0.79 |
0.56 |
12.62 |
9 |
Kytococcaceae |
0.00 |
0.00 |
6.63 |
0.00 |
10 |
Idiomarinaceae |
3.24 |
0.00 |
3.81 |
0.00 |
11 |
Clostridiaceae |
0.93 |
1.57 |
3.67 |
0.66 |
12 |
Methylobacteriaceae |
3.24 |
0.00 |
2.40 |
0.00 |
13 |
Halomonadaceae |
0.00 |
0.00 |
3.39 |
0.00 |
14 |
Moraxellaceae |
0.00 |
3.15 |
1.97 |
0.00 |
15 |
Nocardiaceae |
7.41 |
0.79 |
0.00 |
0.00 |
Heatmap with a dendrogram at the genus level using a gradient heatmap (over 1% of the microbiome). The 30 most predominant genera were used in hierarchical clustering to evaluate the relationships amongst four populations of P. hypomelanus using weighted pair clustering, based on Bray-Curtis measurements. The lighter colour indicates higher abundance.
Based on the Venn diagram in Fig.
A three-dimensional plot of weighted UniFrac, based principal coordinate analysis (PCoA). The plot was created using the pairwise weighted UniFrac distances which account for microbial species richness and evenness where (PC1 is variability at 74%, PC2 is variability at 18% and PC3 is variability at 8%). Different shape indicates the different locality.
Principal coordinate analysis (PCoA), based on UniFrac, revealed that clustering of samples was according to the grouping of the 16S rRNA dendrogram (Fig.
The correlation coefficient values (Pearson r) and p-values (bold) of bacterial community (genera) amongst island populations.
Langkawi Island |
Pangkor Island |
Redang Island |
Tinggi Island |
|
Langkawi Island |
0.89703 |
1.54E-14 |
0.83656 |
|
Pangkor Island |
0.016919 |
0.90198 |
8.77E-13 |
|
Redang Island |
0.79706 |
-0.016102 |
0.71778 |
|
Tinggi Island |
-0.026967 |
0.76307 |
-0.047228 |
The Island Flying Fox is of particular interest to researchers because bats are a group of volant mammals that have unique evolutionary adaptation to habitats. Recently, high-throughput sequencing technology has become available and provided an efficient tool for analysing the relationships between microorganisms that are thought to influence their species diversity and functions (
In this study, we acquired data from bacteria in eight phyla, 44 families and 61 genera. This highlights the advantages of using high-throughput sequencing compared to culture-based approaches in studying bacterial communities (
Moreover, two families of gut bacteria (Enterobacteriaceae and Bradyrhizobiaceae) were most abundant in the group of Proteobacteria. These bacterial families are facultative anaerobes and function in glucose fermentation (
The general composition of gut microbiota in bats is strikingly different from that of other mammalian gut microbiomes, which are generally dominated by Firmicutes. Interestingly, the relatively high abundance of Proteobacteria in the chiropteran gut is similar to that found in the avian gut (
From 61 genera isolated from the intestinal content of Flying Fox, some of the genera contain non-pathogenic species and a common presence of potentially pathogenic microbes, including Pseudomonas, Escherichia, Streptococcus and Clostridium. Previous studies have reported a similar bacteria genus associated with bats, although some genera were not isolated from this study (
The results of our metabarcoding analysis showed both variation in diversity and species composition of bacterial communities in P. hypomelanus amongst different island populations. Overall, the population from Redang Island has a relatively high diversity index (H') of gut microbiome compared to other populations. Meanwhile, the population from Tinggi Island has the lowest diversity index (H') of gut microbiome. Low bacterial diversity is associated with poor physical fitness, while high diversity indicates good health (
Langkawi Island, located in Kedah, has a land area of 328 km2, while Redang Island in Terengganu is 42 km2, Pangkor Island in Perak is 18 km2 and Tinggi Island in Johor is 15 km2. In this study, we tested the hypothesis that the Flying Fox, occupying islands with different habitat quality and environment, may develop different gut microbiome. Langkawi and Redang Islands have a larger island size compared to Pangkor Island and Tinggi Island. Animals occupying large areas of habitats consumed more diverse diets and consequently sustain high gut microbiome richness and diversity (
Residential populations around the islands indirectly affect the abundance and diversity of gut microbiome of P. hypomelanus. Sampling areas in Langkawi Island and Redang Island were better protected from interference by humans compared to those in Pangkor Island and Tinggi Island. Besides, Tinggi Island comprises three villages, namely Kampung Tanjung Balang, Kampung Pasir Panjang and Kampung Sebirah Besar, with a large number of residents. Habitats with high population density and scarce food sources due to human disturbance may affect the diet of P. hypomelanus on the Island. As a result, their diets deviate from the typical dietary habits, which can be associated with shifts in microbiome composition. In general, animals in disturbed habitats consume different types of food from animals in less disturbed areas (
The gut microbiomes in the populations of Langkawi Island and Redang Island were found to be closely related, supported by the shared number of OTUs displayed by the Venn diagram. Besides, one of the PCoA axes correlate which shows island populations (Redang and Langkawi) clustering together and supported with low percentage of variability, as there were no significant differences in bacterial diversity of the gut microbiota. As suggested in previous studies on flying vertebrates (bats and birds), convergent adaptations driven by flight may influence digestive physiology, such as increasing paracellular absorption and accelerating the transit time of food through the gut (
Taken together, these factors have shaped the structure of the community, which revealed bacterial communities between island populations at larger spatial scales in Peninsular Malaysia. Our results revealed important mechanisms that are critical for improving our knowledge of host-microbe interactions in Island Flying Fox populations. This information will serve as a basis for conservation efforts and better assessment of the impact of human activity on animal health and zoonotic disease managements. However, future research is needed to identify specific plant taxa in the diet of P. hypomelanus at finer geographic scales to help promote the healthy gut microbiome in P. hypomelanus in Peninsular Malaysia.
In conclusion, we have outlined the diversity and distribution of bacteria isolated from the gut of Island Flying Fox across four populations in Peninsular Malaysia. Given that collection localities were separated by geographical distance and differ in island size, an unexpected observation from this study was that environment of island populations apparently influences the gut microbiome, suggesting the microbiota observed in bats is not driven by host evolution, but rather by ecological features.
The authors are deeply indebted to Department of Wildlife and National Parks Peninsular Malaysia for providing research permit: JPHL and TN(IP):100-6/1/14(39). The authors acknowledge Universiti Kebangsaan Malaysia and Universiti Tun Hussein Onn Malaysia, for providing necessary funding, facilities and assistance. We appreciated Dr Juliana Senawi and UKM students for their contribution during field genetic samplings. This research was funded by Grants AP-2015-004, GUP-2019-037, GUP-2011-183, ST-2017-007, FRGS/1/2018/WAB13/UTHM/03/2 and MTUN-UTHM-K121 by Universiti Kebangsaan Malaysia and Ministry of Education Malaysia.
AP-2015-004, GUP-2019-037, GUP-2011-183, ST-2017-007, FRGS/1/2018/WAB13/UTHM/03/2 and MTUN-UTHM-K121
Universiti Kebangsaan Malaysia and Universiti Tun Hussein Onn Malaysia.
Research methods, reported in this manuscript, adhered to the legal requirements of Malaysia and were approved by Department of Wildlife and National Parks (PERHILITAN), Peninsular Malaysia, KM10 Jalan Cheras, Kuala Lumpur, Malaysia under research permit JPHLandTN(IP):100-6/1/14(39).
N.S.M.Y., M.A.B.A.L., A.R.M.R. and B.M.M.Z. designed the project. N.S.M.Y. was involved in field sample collection. N.S.M.Y., M.A.B.A.L., A.R.M.R. and A.S.B performed the laboratory work. N.S.M.Y., M.A.B.A.L., A.R.M.R. and N.O. wrote the manuscript and analysed and interpreted the data. S.Y., S.M.N., M.A.B.A.L. and B.M.M.Z. edited the manuscript. All authors read and approved the last version of the manuscript.
The authors declare no conflict of interest.