1. Introduction
In intertidal systems, the type and role of interactions among sediment microorganisms, animals, plants, and abiotic factors are complex and not well understood [
1]. Such interactions are known to aid in nutrient provisioning and cycling, with the dynamics and interconnections being especially important in arid microtidal systems with limited nutrient influx [
2]. Mangroves, coastal ecosystems prevalent in tropical and subtropical regions worldwide, span approximately 150,000 square kilometers across 123 countries [
3]. Bacterial communities play important roles in marine ecosystems, contributing to nutrient cycling, degradation of organic matter, and maintenance of ecological balance [
4]. According to a review of the literature, the primary compartments of mangrove systems are the rhizosphere, root systems, pneumatophores, bulk soil, water, sediments, and biota [
5]. Understanding the distribution and composition of bacterial communities across diverse ecological niches is crucial for unraveling the complexities of microbial ecology and its implications for ecosystem health. Microorganisms in mangrove sediments and water, play an important role in nutrient cycling by facilitating the conversion and transportation of key elements [
6]. Their importance is particularly evident in areas submerged beneath the tidal waterline, where they exhibit the greatest variety and abundance, benefiting the entire mangrove ecosystem [
7]. Nevertheless, understanding of the intricate food webs and biogeochemical cycles in mangroves remains incomplete, primarily due to the limited information available on microbial species compositions and their ecology within these environments [
8]. A diverse microbial community perpetually converts decaying vegetation into sources of nutrients, including nitrogen, phosphorus, and others, which are subsequently assimilated by plants [
9]. In return, root exudates function as a nutrient source for microorganisms [
10]. Hence, the significance of investigating microorganisms inhabiting root zones lies in elucidating various processes occurring in natural environments and the potential to manipulate these microbial populations for the benefit of the plant [
11]. The emergence of metagenomics and next-generation sequencing technologies has allowed for a broader understanding of microbial diversity and functionality within mangrove ecosystems [
12]. Given the ongoing risk of mangrove deforestation, understanding the composition of microbial communities associated with sediments, water, and organisms within mangrove habitats is critical for successful restoration efforts and assessing the health of mangrove ecosystems [
13].
Microbial communities in mangrove habitats are influenced by several key factors. Salinity fluctuations due to tidal cycles play a significant role, as they create varying salt concentrations that shape microbial diversity [
14]. Nutrient availability, particularly nitrogen and phosphorus levels, impacts microbial composition and functions involved in nutrient cycling [
15]. Plant-microbe interactions are crucial, with mangrove plants releasing organic matter and root exudates that influence microbial communities around their roots and in the sediment [
15]. Tidal dynamics affect oxygen levels and nutrient availability, influencing microbial metabolism [
16]. Anthropogenic impacts such as pollution and plastic debris can disrupt microbial communities and their ecological roles [
17]. Lastly, climate change factors like rising temperatures and sea level pose additional challenges to mangrove microbiomes by altering habitat conditions [
17].
Investigating microorganisms within mangrove ecosystem sediment is essential for comprehending the distribution of bacterial communities, which play key roles in element cycling and fostering plant growth [
18]. Furthermore, exploring microorganisms in mangrove ecosystems is crucial as mangrove rhizospheres harbor unique microbial assemblages that impact nutrient and sediment fluxes to the open sea [
19]. These studies underscore the significance of understanding microbial dynamics in mangrove environments for elucidating their ecological functions and broader ecosystem processes. Previous studies indicate that the most dominant phylum associated with different substrates in mangroves is Proteobacteria [
20]. In particular, classes alpha- and beta-Proteobacteria are commonly found in seawater and different substrates including, rocks, seaweeds, marine organisms, and industrial applications [
21].
Mangroves accumulate many different types of pollution including plastics and microplastics. The proliferation of marine plastic debris has emerged as a major global issue affecting oceanic ecosystems [
22]. Plastics are colonized by different types of microorganisms, which form a unique community [
19,
21]. Such a microbial community is called a plastisphere [
24]. The initial study on microbial colonization of plastic waste revealed that diatoms and certain species of Gram-negative bacteria had colonized polystyrene spherules discovered in the Sargasso Sea [
25]. Members of the Bacteroidetes genus
Tunicatimonas, which were originally isolated from sea anemones and later discovered to be prevalent on plastic debris in marine environments, are thought to have adaptations that allow them to exploit the novel niches created by plastic [
26]. Zettler and colleagues [
17] utilized next-generation sequencing and scanning electron microscopy (SEM) to examine the microbial populations of plastic waste in the North Atlantic. They observed distinct differences between the bacterial communities on plastic debris and those present in the surrounding seawater. Meanwhile, a few plastic-degrading and hydrocarbon-degrading bacteria were found on the surface of plastic debris [
27]. Wu with colleagues found that specific microorganisms, such as plastic-degrading bacteria and pathogens, were more abundant in plastics compared to water and sediment in the Haihe Estuary [
28].
Gut microbiota refers to the microorganisms associated with the intestinal tract of animals, playing a vital role in physiological and biochemical reactions. Analyzing the gut microbiota within a mangrove environment offers a way to assess the extent of disturbance to mangrove ecosystems and evaluate the effects of anthropogenic pollutants [
29]. In addition, studying the gut microbiota within mangrove systems is crucial due to the direct influence of environmental conditions on their microbial composition, highlighting the significance of conserving and sustainably managing estuaries [
30] . This underscores the necessity of studying microbial communities in such ecosystems and implementing measures to preserve their ecological integrity. Studies have demonstrated that various environmental pollutants, including plastics, can impact the gut microbiota of different animals. Despite this significance, there is a scarcity of studies focusing on the gut microbiota of a gastropod mollusk
Terebralia palustris (Linnaeus, 1767). This giant mangrove snail is commonly found in Omani mangrove lagoons, inhabiting mud and feeding on mangrove leaves, propagules, and seeds [
31]. Given the importance of
T. palustris in Oman's mangrove ecosystems, investigating the microbes associated with this snail becomes crucial.
In Oman, mangroves consist of exclusively one species of
Avicennia marina (Forssk.). The Ministry of Environment and Climate Affairs (now Environment Authority) launched in 2002 a campaign to expand the mangrove area, resulting in approximately 23.6 hectares now covered. This study was conducted in Sawadi lagoon (177 ha) which has the highest pollution and another natural mangrove lagoon (Qurum, 60 ha) was selected due to the lowest pollution [
32]. This study aims to investigate the microbial communities inhabiting four distinct substrates within two mangrove lagoons located in Oman: Sawadi and Qurum. Specifically, our objectives are twofold: (1) Characterize the microbial communities present in sediment, surface water, plastic debris, and the gut of
T. palustris snails within these mangrove lagoons, and (2) Compare the composition and diversity of bacterial communities across the aforementioned substrates and between the two mangrove lagoons using MiSeq sequencing of the 16S rDNA gene. Achieving the objectives will fill several specific research gaps, such as the lack of comparative analysis of microbial communities across different substrates (sediment, water, plastic debris, and snail guts) within mangrove ecosystems, the limited understanding of microbial communities on plastic debris versus natural and biotic substrates, the insufficient high-resolution data on bacterial diversity in mangroves, the underexplored gut microbiomes of
T. palustris snails, and the spatial variability of microbial communities between different mangrove lagoons.
2. Materials and Methods
2.1. Locations and Site Characteristics
Sampling activities were conducted from July 15th to 20th, 2023, in two lagoons located in the Sea of Oman, Oman. These lagoons, Sawadi (23°45'41.99"N 57°47'29.64"E) and Qurum (N23°37'20.45"/E58°28'37.34") exhibit distinct mangrove vegetation characteristics (
Supplementary Table 1). Each lagoon was divided into three transects (T1, T2, and T3), representing the seaward fringe, inside the forest, and landward fringe, respectively. Detailed design schematics can be found in the supplementary materials (
Supplementary Table 1). During the study period, samples of sediment, water, snails, and plastics were collected from each Sawadi and Qurum lagoon transects. The sampling protocol followed methodologies outlined by [
33] with necessary adaptations. Notably, all samples were collected concurrently. Diverse physical attributes were assessed at the sampling sites. Specifically, water parameters such as dissolved oxygen levels, conductivity, salinity, pH, and temperature were measured using the calibration method of portable water quality meters (SevenGoTM SG3, Japan) (
Supplementary Table 2).
2.2. Sediments Collection
In each sampling site (Sawadi and Qurum), three samples from the upper layer (depth =0–5 cm) of sediments were collected in a quadrat 30 cm x 30 cm based on the previously described methodology [
34,
35,
36]. Only one sample was taken from each transect, representing each zone. Briefly, samples of surface sediment were collected using a metal spoon. About 400 grams of sediment per sample were carefully gathered and placed in separate sterile 500 mL glass containers. Samples were transported to the laboratory immediately on ice. Upon arrival at the laboratory, all samples were stored in a lab freezer at -80°C until further analysis.
2.3. Water Collection
In each sampling site (Sawadi and Qurum) three samples of water were collected. Only one sample was taken from each transect, representing each zone. Two liters of water samples were taken from a depth of 30 cm below the surface [
33]. The collected water samples underwent a two-step filtration process to eliminate potential contaminants. First, they were passed through quantitative stainless steel tower sieves with a pore size ranging from 60µm to 500µm. This step removed any impurities from the samples. Subsequently, the filtered water samples were subjected to a secondary filtration using 0.2µm sterile Millipore cellulose acetate membranes (Whatman, China). This additional filtration step ensured the removal of even finer particles. Then, the filters were cut into smaller pieces in preparation for the DNA extraction protocol [
37].
2.4. Plastics Collection and Characterization
Plastic samples prevalent in the lagoons were collected using sterile stainless forceps from the surface sediments within a 100 m2 quadrat in each transect (T1, T2, and T3). Various types of the most prevalent plastics, differing in size and color were collected from three quadrats at each lagoon. In the laboratory, the plastic samples underwent a triple rinse with distilled DNA-free water (Sigma, Germany) and were subsequently stored in 250 mL sterile screw-neck glass tubes and kept at -80°C until further analysis (see below).
The color, shape, and size of plastics were recorded during the sampling process (
see Supplementary Table 4). The types of polymers were identified using Attenuated Total Reflection Fourier Transformed Infrared Spectroscopy (ATR-FTIR) with the ATR-MIRacle
TM PIKE instrument (Agilent Technologies, USA). The detector's spectral range covered 400 to 4000 cm
-1, with a resolution of 8 cm
-1 for 16 scans. The spectra were processed using (MicroLab software) and compared with standard polymer spectra to facilitate analysis (
Supplementary Figure 1).
Figure 1.
Venn diagrams showing counts and percentages of common and unique OTUs in microbial communities across four substrates in Sawadi (A) and Qurum (B) lagoons.
Figure 1.
Venn diagrams showing counts and percentages of common and unique OTUs in microbial communities across four substrates in Sawadi (A) and Qurum (B) lagoons.
2.5. Snail Collection
Ten Terebralia palustris snails were randomly collected within 100 m2 from both Sawadi and Qurum lagoons. To maintain snail integrity for further examination, they were promptly chilled on ice. In the laboratory, snail shells were crushed utilizing a vice, followed by the dissection of their guts using a sterile scalpel. Each snail gut was then delicately placed into a sterile 250 ml glass container and preserved at -80°C for subsequent analysis.
2.6. Isolation of DNA
DNA from water, sediments, plastics, and snail gut samples were extracted using the Powersoil DNA extraction kit (Qiagen, Germany). For this procedure, 250 mg of sediment, 250 mg of cut filter, 250 mg of plastic, and 250 mg of snail gut were added to separate tubes. Before extraction, large pieces were cut into micro-sized fragments using sterilized scissors. DNA extraction was carried out according to the instructions provided in the manual. From each location, DNA from 3 samples of sediment, 3 samples of water, 3 samples of plastic, and 10 guts of snails was obtained. To ensure quality control, DNA-free water was utilized instead of the sample during DNA extraction to detect any potential contamination. Following extraction, the quality and quantity of the extracted DNA were evaluated using a NanoDrop™ Lite spectrophotometer (Thermo Fisher Scientific, USA). In the case of low quality and quantity of DNA, it was re-extracted from new samples collected earlier.
2.7. DNA sequencing and Identification of Bacteria
The DNA samples obtained from sediments, water, the gut of snails, and plastic underwent Illumina MiSeq paired-end sequencing (2 × 300 bp) at Molecular Research (MRDNA) in Texas, USA. Before sequencing, PCR was conducted with universal primers targeting the bacterial hypervariable regions V3–V4 of the 16S rRNA gene (515 F: 5′-GTGCCAGCMGCCGCGGTAA-3′ and 806 R: 5′-GGGACTACHVGGTWTCTAAT-3′), following specific PCR conditions. The subsequent Illumina MiSeq paired-end sequencing process involved several data processing steps. These steps included the removal of barcode and primer sequences, merging reads to generate Raw Tags using Vsearch v2.4.4, filtering out low-quality reads, and defining OTUs based on 97% sequence identity. Representative sequences for OTUs were annotated using the SILVA12.8 databases, with validation from RDPII and NCBI databases. The relative abundance in the percentage of each bacterial group in each sample was calculated.
2.8. Data Analysis and Statistical Methods
In this study, descriptive statistics were computed for OTUs to characterize their distribution in sediment samples from Sawadi and Qurum lagoons. Additionally, relative abundances at the phylum, class, and genus levels were analyzed across various substrates and microbial communities. For phyla and genus data with the abundance greater than 1% was analyzed, while for class level, there was no cut off. Normality tests, specifically the Shapiro-Wilk test, were conducted to assess the distribution of taxonomic data, followed by Kruskal-Wallis tests to detect significant differences in taxonomic composition. Subsequently, Dunn Post Hoc tests were employed for pairwise comparisons following significant findings in the Kruskal-Wallis tests, aimed at identifying specific pairs of substrates or microbial communities exhibiting significant differences in taxonomic composition. Through these analyses, the study aimed to elucidate the diversity and taxonomic structure of microbial communities in the lagoons and discern potential differences.
Data analysis includes the calculation of the percentage of relative abundances, mean, and standard deviation numbers in each bacterial group. Principle Component Analysis (PCA) was employed to analyze differences in bacterial communities across sampling sites and substrates. Shannon diversity indices, evenness index and Chao indices were calculated to estimate genus richness. Shared and unique OTUs among different substrates were plotted using Venn diagram (
https://cir.nii.ac.jp/all?q=http://bioinfogp.cnb.csic.es/tools/venny/index.html). The data were plotted using OriginPro software and PAST software.
5. Conclusions
This study aimed to characterize and compare the microbial communities present in sediment, surface water, plastic debris, and the gut of T. palustris snails within two mangrove lagoons in Oman: Sawadi and Qurum. Our analysis revealed that microbial communities in sediment, surface water, plastic debris, and snail guts exhibited similarities between the two lagoons, likely due to comparable environmental conditions such as temperature, salinity, total dissolved solids (TDS), and electrical conductivity. However, significant differences were noted in the snail gut microbiota, possibly due to differences in the natural versus man-made environments and varying pollution levels. In Qurum's natural mangroves, the stable and mature ecosystem supported diverse microbial communities, while the man-made mangroves in Sawadi showed different microbial colonization patterns, influenced by higher pollution levels, including microplastics. Proteobacteria were the most abundant phylum across all substrates in both lagoons, with Gammaproteobacteria being particularly dominant. Bacteroidetes, the second most abundant phylum, played significant roles in nutrient cycling. The genus Vibrio, potentially including pathogenic species, was prevalent across most substrates, indicating a potential health risk in these habitats. Each substrate harbored distinct microbial communities. For instance, water samples contained unique genera such as Sunxiuqinia and Pseudomonas. Plastic surfaces, despite being artificial, supported high microbial diversity, including bacteria capable of degrading plastics. Environmental conditions, substrate composition, and pollution levels were identified as major factors shaping microbial communities in the lagoons. The higher pollution levels in Sawadi supported microbial communities adapted to these conditions, whereas Qurum's lower pollution levels favored more balanced microbial ecosystems.
The identification of distinct microbial communities among different sampling sites and different subsstrata in mangrove habitats indicates that environmental factors are influencing microbial communities, as microbial populations are impacted by physical, chemical and biological properties of the environment. Due to climate change and increasing anthropogenic pressure the microbial communities associated with mangrove forests are expected to undergo significant shifts. Yet, without the knowledge of existing microbial communities, we cannot accurately assess the extent of these changes. As mangrove habitats in the world face increasing threats, integrating microbial ecology research into ecosystem management policies becomes imperative. Recognizing the role of microorganisms in enhancing ecosystem resilience against global changes underscores the urgency of incorporating microbiome data into mangrove conservation strategies.
Author Contributions
Conceptualization, M.T. and S.D.; methodology, M.T. and S.D.; software, M.T. ,S.D and M.B.; validation, S.D. and M.B; formal analysis, M.T.,S.D and M.B.; investigation, M.T.,S.D and M.B.;; resources, S.D.; data curation, M.T.,S.D and M.B .; writing—original draft preparation, M.T. and S.D.; writing—review and editing, M.T.,S.D and M.B.; visualization, M.T.,S.D and M.B.; supervision, S.D and M.B.; project administration, S.D.; funding acquisition, S.D..