Next Article in Journal
Early Life Factors Influencing Children Gut Microbiota at 3.5 Years from Two French Birth Cohorts
Next Article in Special Issue
Effect of Heavy-Metal-Resistant PGPR Inoculants on Growth, Rhizosphere Microbiome and Remediation Potential of Miscanthus × giganteus in Zinc-Contaminated Soil
Previous Article in Journal
Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE)
Previous Article in Special Issue
Apple Root Microbiome as Indicator of Plant Adaptation to Apple Replant Diseased Soils
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Microorganisms
Volume 11
Issue 6
10.3390/microorganisms11061389
microorganisms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Degradation on Microbial Communities of an Amazonian Mangrove

by
Gleyciane Machado da Costa
1,2,
Sávio Souza Costa
1,2,
Rafael Azevedo Baraúna
1,2,
Bruno Pureza Castilho
1,
Izabel Cruz Pinheiro
1,
Artur Silva
1,2,
Ana Paula Schaan
3,
Ândrea Ribeiro-dos-Santos
3 and
Diego Assis das Graças
1,2,*
1
Laboratory of Biological Engineering, Guamá Science and Technology Park, Belém 66075-750, Brazil
2
Laboratory of Genomics and Bioinformatics, Center of Genomics and Systems Biology, Institute of Biological Sciences, Federal University of Pará, Belém 66075-110, Brazil
3
Laboratory of Medical and Human Genetics, Institute of Biological Sciences, Federal University of Pará, Belém 66075-110, Brazil
*
Author to whom correspondence should be addressed.
Microorganisms 2023, 11(6), 1389; https://doi.org/10.3390/microorganisms11061389
Submission received: 10 April 2023 / Revised: 4 May 2023 / Accepted: 5 May 2023 / Published: 25 May 2023
(This article belongs to the Special Issue Soil Microbial Diversity and Its Ecological Functions)
Browse Figures
Review Reports Versions Notes

Abstract

:
Mangroves provide a unique ecological environment for complex microbial communities, which play important roles in biogeochemical cycles, such as those for carbon, sulfur, and nitrogen. Microbial diversity analyses of these ecosystems help us understand the changes caused by external influences. Amazonian mangroves occupy an area of 9000 km2, corresponding to 70% of the mangroves in Brazil, on which studies of microbial biodiversity are extremely scarce. The present study aimed to determine changes in microbial community structure along the PA-458 highway, which fragmented a mangrove zone. Mangrove samples were collected from three zones, (i) degraded, (ii) in the process of recovery, and (iii) preserved. Total DNA was extracted and submitted for 16S rDNA amplification and sequencing on an MiSeq platform. Subsequently, reads were processed for quality control and biodiversity analyses. The most abundant phyla were Proteobacteria, Firmicutes, and Bacteroidetes in all three mangrove locations, but in significantly different proportions. We observed a considerable reduction in diversity in the degraded zone. Important genera involved in sulfur, carbon, and nitrogen metabolism were absent or dramatically reduced in this zone. Our results show that human impact in the mangrove areas, caused by the construction of the PA-458 highway, has resulted in a loss of biodiversity.

1. Introduction

Mangroves are one of the most dynamic and productive ecosystems and have great ecological importance. Located along tropical and subtropical regions, they constitute more than half of the terrestrial coastline forming a transitional environment between sea and land [1]. Mangroves are subjected to periodic tidal flooding, which results in variable salinity, redox potential, and anaerobic/aerobic conditions [2,3]. These characteristics make mangroves capable of harboring highly diverse microbial communities, which in turn are responsible for many essential features of biogeochemical cycles [4,5], thus microbial communities play a central role in maintaining the health and equilibrium of the mangrove environment.
The nitrogen cycle in mangroves is mediated by diverse groups of microorganisms and involves the transformation of nitrogen in various forms through key processes, such as nitrogen fixation, nitrification, denitrification, and ammonification [4]. Microbial communities in mangrove soils play a critical role in the phosphorus (P) cycle by mediating key processes involved in P cycling, such as (re)mineralization, immobilization, and adsorption, which influence P availability and cycling in mangrove ecosystems [5]. Microorganisms also mediate many sulfur transformation reactions, such as sulfide oxidation, sulfate reduction, and sulfur disproportionation [6]. The productivity of mangroves fuels ecosystem services based on plant products and makes up the foundation of the ecosystem food web.
Brazil has the second largest area of mangroves in the world [7]. It was reported that the mangroves in Brazil possess 8.5% of the world’s carbon stocks found in these ecosystems, most of which is in the upper meter layer of soil, making this biome crucial for maintaining the climate [8]. Amazonian mangroves occupy an area of more than 10,000 km2 and account for 80% of the country’s mangroves. Microbes play a major role in the carbon cycle, but studies focused on microbial diversity in the Amazonian region are extremely scarce, despite reports stating these areas are at risk due to the consequences of human activities [7,9,10].
The main bacterial phylum found in mangrove samples is Proteobacteria, which is considered part of the core microbiome, but other groups are also frequently found such as Planctomycetes, Acidobacteria, Bacteroidetes, and Chloroflexi [11]. Previous research in Brazil has aimed to understand and characterize the role of microbial diversity in mangrove areas [12,13,14,15]. In São Paulo state, evidence shows that Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes are more abundant in areas impacted by humans and oil spills [16]. In this same location, it was also reported that mangrove zones are richer in taxonomic and functional diversity [15].
Nóbrega et al. [9] reported a high abundance of Proteobacteria and Actinobacteria in water samples from an Amazonia mangrove area, with functional profiles related to carbon, nitrogen, sulfur, and methane cycles. In the same region, Tavares et al. [10] showed a high abundance of Proteobacteria, and that the microbiomes associated with Rhizophora mangle root soils are similar to those from the Brazilian southeast, in spite of their geographical distance.
The PA-458 highway was constructed to connect Bragança city to the coastal and touristic beach area of Ajuruteua, leading to the destruction of Amazonian mangrove areas along its path [17]. This impact affected not only aquatic systems that depend on the exchange of nutrients [18] but also animal nutrition and the riverine subsistence economy [19,20]. There are zones within this mangrove area that are considered to be under ecological and environmental recovery due to recent measures aimed at preservation, such as community environmental awareness programs, research, reforestation with native plants, and others.
Studies assessing the environmental impacts on the microbiome of mangroves are important to aid in the preservation and restoration of these valuable ecosystems. In this study, we characterize and compare changes in the microbial community structures in mangrove sediments impacted by the construction of the PA-458 highway, in the Brazilian Amazon, by analyzing preserved and under-recovery areas through amplicon sequencing.

2. Materials and Methods

2.1. Sample Collection and Site Description

The Bragança Region is located on the Amazonian Atlantic coast, and its mangrove peninsula encompasses the estuaries of the Caeté and Tapera-Açu rivers and is considered the second largest continuous mangrove ecosystem in the world. Soil compaction for the construction of the highway interrupted the flow of water and nutrients through the mangrove in several areas, in addition to streams, thus impacting the landscape, vegetation, and fauna. The area experiences a semidiurnal macrotidal pattern, with tides ranging from four to six meters [19]. The water salinity varies from zero to as high as 100 parts per thousand (ppt) throughout the annual cycle. Mangrove samples were collected in triplicate at six points along the PA-458 highway (Figure 1). The collection points were separated on the East and West sides of the highway, making a total of 18 samples obtained in August 2018, during the dry season. No rain occurred during sampling.
All three collection points on the east side of the highway (P2, P4, and P6), and P5 were considered preserved, due to constant water flow and wood density where Rhizophora mangle L., Avicennia germinans (L.) L., and Laguncularia racemosa (L.) C. F. Gaertn predominated. On the west side, sample P1 was classified as degraded, due to the absence of vegetation and no water flow. Point P3 was considered as under-recovery because the area is under the influence of a stream and vegetation is undergrowth.
At each point (from P1 to P6), three replicates of 30 g of subsurface sediment (~20 cm depth) were collected using a sterile soil core sampler. Vegetation was removed and soil was immediately transferred to a 50 mL tube. Samples were chilled on ice until arrival at the laboratory and then stored at −80 °C until further procedures. Due to DNA degradation during transportation, five replicates were removed for further analysis.
Another three sediment sample replicates were collected from each point (P1to P6), to give a total of 18 samples. Replicates from each point were prepared for physicochemical analysis, which was carried out at the Brazilian Agricultural Research Corporation (EMBRAPA). For the determination of: P, K, and Na content, extraction was performed with Mehlich 1 solution (12.5 mM H2SO4 + 50 mM HCl); Ca, Mg, and Al, extraction with 1 M KCL solution; H and AI (potential acidity), extraction with calcium acetate pH 7 solution; organic matter (OM), potassium dichromate; and total nitrogen, sulfuric/Kjeldahl digestion.

2.2. DNA Extraction and Sequencing of 16S rRNA Genes

Total DNA was extracted from 500 mg mangrove samples using the Powersoil DNA Isolation Kit (MO BIO, Carlsbad, CA, USA) according to the manufacturer’s protocol. Eluted DNA was quantified with fluorometry on a Qubit 4.0 (Thermo Scientific, Waltham, MA, USA) and subsequently stored at −20 °C. Library preparation was carried out according to the Illumina Metagenomic Sequencing Library Prep protocol with established primers and Illumina Nextera adapters targeting the V3–V4 region of the 16S rDNA, as follows: Bakt_341F (CCTACGGGNGGCWGCAG) e Bakt_805R (GACTACHVGGGTATCTAATCC), using the following cycle: 95 °C for 4 min, followed by 25 cycles at 94 °C for 1 min, 60 °C for 1 min, and 72 °C for 2 min. The PCR reaction final volume was 25 µL, containing 2.5 μL of DNA (5 ng/μL), 5 μL of each primer (1 μM), and 12.5 μL of 2x KAPA HiFi HotStart ReadyMix. Purification and size selection of PCR products were performed using a Pronex® Size-Selective Purification System (Promega, Madison, WI, USA). Libraries were subsequently quantified with TapeStation (Agilent, Santa Clara, CA, USA) using High Sensitivity D1000 screen prior to sequencing on the Illumina MiSeq platform, using Reagent Kit v2 (500 cycles, 2 × 250 bp) on an Illumina MiSeq sequencer (Illumina, San Diego, CA, USA).

2.3. Data Analysis

Read quality was evaluated using FASTQC v0.12.1 [21], low-quality reads smaller than 200 bp were filtered out, and chimeras were removed using USEARCH [22]. After quality control analyses, one replicate yielded less than 5000 raw reads with low-quality sequences and was removed from further analysis. Reads were grouped into Operational Taxonomic Units (OTU) with 97% similarity and taxonomy was assigned to each OTU (excluding singletons) by performing BLAST searches in the SILVA v.132 database [23]. Alpha and beta diversity analyses were performed in R v.3.5.343 using Phyloseq [24], Vegan [25], and LEfSe [26] packages.
Statistical differences between alpha diversity results were tested using T-Test. To perform beta diversity analyses, sample counts were normalized based on their relative abundances, and PERMANOVA was used to examine the Bray–Curtis Distances. Heatmap and sample clustering analysis were performed using the Wilcoxon Rank Sum test, and the taxonomic differences between microbial communities were obtained using LDA Effect Size (LEfSe) with a p-value 0.1 using the Kruskal Wallis test.

3. Results

The data presented in Table 1 correspond to the results of the physicochemical analyses of mangrove sediment samples. Samples were acid to neutral (pH range 5.1–6.4). We observed a difference in the amount of carbon, OM, phosphorus, potassium, and cation-exchange capacity (CEC) when comparing degraded mangrove sediment to the preserved areas (except for P6), but without in-depth statistical analysis.
We obtained 999,997 high-quality reads (per sample minimum = 43,328, maximum = 131,784, mean = 83,333, median = 84,411, standard deviation: 25,795). We observed 14,155 different OTUs throughout all samples and considered that sequencing efforts were sufficient due to rarefaction curves reaching a plateau of around 25,000–30,000 sequences in library size (Figure S1, Supplementary Materials). It is important to note that the number of samples taken from each zone was unbalanced, which can affect the strength of the inference.
Alpha diversity results (Table 2) revealed that samples from degraded mangroves showed a dramatically lower species richness (~2.5× less OTUs) when compared to others, with a mean Shannon index of 5.55 (mean of 1759 OTUs), while preserved samples showed a mean Shannon index of 7.00 (mean of 4496 OTUs), and samples from the recovery area reached a Shannon index of 7.12 (mean of 4653 OTUs). The Simpson index shows a high degree of diversity and evenness in all samples.
Alpha diversity results revealed significant differences (p < 0.05) in microbial diversity between the environment impacted by the road construction (degraded) and both the preserved and the recovery samples, demonstrated by lower Chao1, Shannon, and Simpson diversity indexes (Figure 2).
The most abundant phyla were Proteobacteria, Firmicutes, and Bacteroidetes in all three mangrove sites, however, in notably different proportions (Figure 3A). Alphaproteobacteria were assigned mostly to orders Rhizobiales, Rhodospirillales, and Rhodobacterales. Deltaproteobacteria were assigned mostly to orders Desulfobacterales, Syntrophobacterales, and Myxococcales, while Gammaproteobacteria were classified mostly in Legionellales, Chromatiales, and Methylococcales. Alpha, Delta, and Gammaproteobacteria represented more than 90% of the reads assigned in Proteobacteria phylum, but Beta, Epsilon, and Zetaproteobacteria were also observed, as well as Oligoflexia class.
Proteobacteria represented 38–55% of relative abundance in preserved and recovery areas, but in the degraded mangrove was reduced to 12–15%. On the other hand, Firmicutes phylum was observed in significantly higher abundance (30–35%) in the degraded area when compared to other points, as well as Bacteroidetes (25–29%), mainly represented by Prevotellaceae, Lachnospiraceae, and Ruminococcaceae families. Furthermore, Choloroflexi, Acidobacteria, Actinobacteria, Verrucomicrobia, and Planctomycetes were found in all areas (less than 10% of relative abundance), and were more abundant in preserved and under-recovery areas than in the degraded zone (Figure 3A).
Considering the differentially abundant taxa (LDA analysis), Firmicutes, Bacteroidetes, Elusimicrobia, Lenthisphaerae, Tenericutes, and Acetothermia were significantly more abundant in the degraded zone (Figure 3B), while Acidobacteria, Actinobacteria, Planctomycetes, Latescibacteria, and Nitrospirae were higher in the recovery area. The preserved zone presented a significantly higher abundance of Proteobacteria, Chloroflexi, Ignavibacteriae, and Deferribacteres.
Beta-diversity analyses (PCoA and dissimilarity) showed that samples collected in the degraded zone form a distinct group when compared to the preserved and in-recovery areas (Figure 4B), with axis 1 explaining 78.6% of the variability. In the Heatmap plot (Figure 4A), we observed that Thermodesulfobacteria, Acetothermia, Tenericutes, Bacteroidetes, Lentisphaerae, Elusimicrobia, and Firmicutes are more abundant in the degraded zone, while the other taxa are in higher proportion in preserved and recovery areas.

4. Discussion

Mangrove ecosystems face global threats from multiple factors, such as coastal development, pollution, and increasing sea levels. This study shows a dramatic loss of microbial phylogenetic diversity in zones affected by the construction of a 40 km long highway when compared to preserved or areas under recovery. The preserved and recovery zones have a higher concentration of carbon and OM, receiving nutrients from the riverine entrance and tide, as well as having a higher microbial diversity. The abundant vegetation and fauna contribute to a richer environment, with more niches and microbes being important players in this scenario.
Among the species most found in Brazilian mangroves, 53–60% belong to the phylum Proteobacteria [27], which corresponds to about half of the bacterial genomes recorded at the National Center for Biotechnology Information (NCBI), corroborating the results of this study [28,29,30]. Represented mostly by the classes of Deltaproteobacteria and Gammaproteobacteria, Proteobacteria are part of the core microbiome of mangroves worldwide [31,32,33]. Proteobacteria are found in freshwater and marine environments in all latitudes, where they are responsible for many roles, including the degradation of OM [9,16].
In a study carried out on three mangrove areas in the state of São Paulo (contaminated by oil, under anthropogenic effect, and preserved), more than 45% of all microbial diversity was represented by Proteobacteria in all three areas [16]. The same study showed a percentage below 15% for Firmicutes, and even lower abundances for Bacteroidetes in mangrove areas under the effect of anthropogenic action, despite the former being reported as the second most abundant phylum after Proteobacteria, followed by Actinobacteria and Bacteroidetes. In our observations, the Firmicutes phylum was detected in all mangrove environments, but in higher abundances in the degraded zone. A higher abundance of the phyla Firmicutes and Bacteroidetes was also found in mangroves contaminated by sewage on the island of Hainan in China [34]. In contaminated mangroves along the Red Sea Coast in Saudi Arabia, Bacteroidetes showed a relative abundance of >1% compared to the pristine zones (<1%) [35].
In our study, Firmicutes and Bacteroidetes are significantly more abundant in impacted mangroves when compared to pristine zones (preserved and recovery), and are mainly represented by Prevotellaceae, Lachnospiraceae, and Ruminococcaceae families, whose members are typically found in gut and rumen microbiomes. One explanation for this could be the intense populational flow and human activity throughout the highway extension. It is worth mentioning that the mangrove areas impacted in the studies discussed here had a small amount of vegetation in their environments. A study of the vertical distributions of rhizosphere bacteria from three mangrove species in the Beilun Estuary located in southern China revealed that plant species and depth played a role in the formation of microbial communities [29].
The phylum Acidobacteria represents a group of soil bacteria, whose members are widely and evenly distributed throughout almost all ecosystems [36], mainly in acidic soils. These bacteria may have an important contribution to the mangrove ecosystem, as they are phylogenetically diverse and may play many roles in various biogeochemical cycles, such as those of nitrogen, carbon, and sulfur, due to their metabolic versatility [37]. In the present study, many Acidobacteria subgroups (1, 2, 3, 6, 16, 22, and 23) were found in higher abundance in the under-recovery zone, but in lower proportion in the highly impacted mangrove, which is expected for an area with biodiversity loss [38,39]. These subgroups were found in Brazilian mangrove sediments associated with Rhizophora mangle [10] and in Restinga soils from the Brazilian southeast region [15].
Verrucomicrobia phylum represented less than 2% of the reads in all zones, but in degraded samples was nearly absent. This phylum is frequently found in low frequency in Brazilian mangroves [10,16,27,40], as well as worldwide [29]. Their role in mangrove sediments is poorly understood, but in the soil, they regulate methane emissions [41] and participate in nitrogen transformations [42], which reinforces the hypothesis that the rare microbiome plays a crucial role in mangrove cycles.
The Archaea domain was not considered abundant (<2%) as reported in other studies [43], but we observed that the degraded zone had a lower abundance of archaea than preserved areas. Euryarchaeota were represented mainly by Halobacteria and Methanogenic archaea, while Crenarchaeota were all represented by the Thermoproteales and Desulfurococcales. It is known that Crenarchaeota is also the major player in the nitrogen cycle in acidic soils (pH < 5.5) [44], which is the pH range of samples in this study. These groups are important in the carbon and sulfur cycle, which is probably affected in the degraded zone. We also observed ammonia-oxidizing archaea (AOA) at preserved and recovery zones, assigned to the Thaumarchaeota phylum, but in low frequency (<0.1%).
Ignavibacteriae were found in low abundance (less than 3%) in preserved and recovery zones, while nearly absent in degraded samples. It is a relatively recently described phylum, which is known to be Gram-negative, anaerobic, or microaerophilic [45]. They are generally considered to be slow-growing and are often found in environments such as freshwater sediments, subsurface environments, and gastrointestinal tracts of animals. Ignavibacteria were found to be present in low abundances (<1.5%) in mangrove samples from Panama, however, were observed in higher proportions in samples from more preserved and unpolluted areas [46]. These findings are similar to our results, and suggest Ignavibacteria are probably involved in some process only possible in a preserved environment.
The phylum Latescibacteria, previously known as WS3, can be found in various environments such as terrestrial, aquatic, marine, and mangrove habitats [47,48]. They are typically Gram-negative, anaerobic, and often found in low abundance, but their ecological roles and physiological characteristics are not yet fully understood. In mangrove sediments of Goa (India), Latescibacteria were found in higher proportions in environmentally rich niche samples [28].
At the family level, we observed differential distribution patterns in the degraded and preserved or in recovery mangrove regions, including the loss of facultative or strictly anaerobes Anaerolineaceae, Desulfobacteraceae, Desulfobubaceae, Sytrophaceae, and Planctomycetaceae in the impacted area, which is frequently found in aquatic (marine or freshwater) environments. Desulfobacteraceae, Desulfobubaceae, and Sytrophaceae are strictly anaerobic bacteria that reduce sulfate to obtain energy, and some members are also able to reduce nitrate. Recently, some researchers proposed to cluster these families into a phylum named Desulfobaterota [49,50]. The Anaerolineaceae family are anaerobic bacteria found in the upper zones of mangrove sediments that play a role in nitrate reduction to ammonium [51]. In preserved and recovery zones, we observed a high abundance of Thioalkalispiraceae, which are chemolithoautotrophic bacteria able to oxidize sulfur compounds and that have been obtained from soda lakes, hypersaline lakes, or marine environments, with specific NaCl concentration requirements for growth [52]. Bacteria assigned to Planctomycetaceae are facultative aerobes typically found in aquatic and wetland zones involved in the nitrogen and carbon cycle [16,53]. Here, we consider that the absence of these bacterial groups is due to mangrove degradation, affecting nitrogen, sulfur, and carbon cycles.
Actions to recover the Bragança mangrove have been carried out in recent decades and apparently had positive results on the resilience of the microbial community in the mangrove sediment. The beta diversity analysis showed that the recovering mangrove areas share similar taxonomic diversity to preserved collection sites, with no significant difference between the groups. In addition, we also observed several differentially abundant phyla, but no statistical significance was revealed in our study.
We observed 47 different phyla across all samples, only six of which displayed abundances greater than 5%. More than 30 phyla were considered rare or of low abundance, indicating the environment is capable of harboring a wide range of diversity that is potentially crucial for ecological balance [54]. Wang et al. (2022) [54] reported that in mangrove samples, the influence of abiotic variables on the structure of rare taxa is limited, explaining only a small portion of the observed variation. This suggests that there may be other unknown and more complex factors shaping the composition of rare taxa, and more studies focused on these groups are needed.
The significance of this study is to show the extent of the impact caused by road construction (and potentially other anthropogenic activities) on mangrove ecosystems, which also influence microbial diversity and possibly the function of mangrove ecosystems. Our findings indicate that degraded mangrove sediments have significantly lower bacterial diversity, with a decrease in taxa responsible for sulfur, nitrogen, and carbon cycles compared to preserved and recovering mangroves. Furthermore, we showed an increase of typical human gut microbial taxa in the degraded zone, which may indicate human contamination in mangrove sediments. Studies using a whole metagenomic sequencing approach with dense and longitudinal sampling may allow for further insights into the long term impact of human activity on mangroves as well as the pace at which these ecosystems are able to recover and restore microbial communities.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microorganisms11061389/s1, Figure S1: Rarefaction curve.

Author Contributions

G.M.d.C. and D.A.d.G.: analyzed, interpreted the data, and wrote the manuscript. S.S.C., R.A.B. and A.S.: contributed to the bioinformatics analyses. B.P.C. and I.C.P.: collected the samples. A.P.S. and Â.R.-d.-S.: contributed to the sequencing analysis. D.A.d.G.: conceived the study. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Fundação Amazônia de Amparo a Estudos e Pesquisas (FAPESPA).

Data Availability Statement

Data are available at SRA under the IDs PRJNA934321 and PRJNA934349.

Acknowledgments

We are grateful to PROPESP/PAPQ/UFPA for the support.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Sahoo, K.; Dhal, N.K. Potential Microbial Diversity in Mangrove Ecosystems:A Review. Indian J. Mar. Sci. 2009, 38, 249–256. [Google Scholar]
  2. Holguin, G.; Vazquez, P.; Bashan, Y. The Role of Sediment Microorganisms in the Productivity, Conservation, and Rehabilitation of Mangrove Ecosystems: An Overview. Biol. Fertil. Soils 2001, 33, 265–278. [Google Scholar] [CrossRef]
  3. Ferreira, T.O.; Otero, X.L.; de Souza Junior, V.S.; Vidal-Torrado, P.; Macías, F.; Firme, L.P. Spatial Patterns of Soil Attributes and Components in a Mangrove System in Southeast Brazil (São Paulo). J. Soils Sediments 2010, 10, 995–1006. [Google Scholar] [CrossRef]
  4. Lu, X.; Taylor, A.E.; Myrold, D.D.; Neufeld, J.D. Expanding Perspectives of Soil Nitrification to Include Ammonia-Oxidizing Archaea and Comammox Bacteria. Soil. Sci. Soc. Am. J. 2020, 84, 287–302. [Google Scholar] [CrossRef]
  5. Tian, J.; Ge, F.; Zhang, D.; Deng, S.; Liu, X. Roles of Phosphate Solubilizing Microorganisms from Managing Soil Phosphorus Deficiency to Mediating Biogeochemical P Cycle. Biology 2021, 10, 158. [Google Scholar] [CrossRef] [PubMed]
  6. Klotz, M.G.; Bryant, D.A.; Hanson, T.E. The Microbial Sulfur Cycle. Front. Microbiol. 2011, 2, 241. [Google Scholar] [CrossRef]
  7. Ottoni, F.P.; Hughes, R.M.; Katz, A.M.; Rangel-Pereira, F.d.S.; de Bragança, P.H.N.; Fernandes, R.; Palmeira-Nunes, A.R.O.; Nunes, J.L.S.; Dos Santos, R.R.; Piorski, N.M.; et al. Brazilian Mangroves at Risk. Biota Neotrop. 2021, 21, e20201172. [Google Scholar] [CrossRef]
  8. Rovai, A.S.; Twilley, R.R.; Worthington, T.A.; Riul, P. Brazilian Mangroves: Blue Carbon Hotspots of National and Global Relevance to Natural Climate Solutions. Front. For. Glob. Chang. 2022, 4, 217. [Google Scholar] [CrossRef]
  9. Nóbrega, M.S.; Silva, B.S.; Tschoeke, D.A.; Appolinario, L.R.; Calegario, G.; Venas, T.M.; Macedo, L.; Asp, N.; Cherene, B.; Marques, J.S.J.; et al. Mangrove Microbiome Reveals Importance of Sulfur Metabolism in Tropical Coastal Waters. Sci. Total Environ. 2022, 813, 151889. [Google Scholar] [CrossRef]
  10. Tavares, T.C.L.; Bezerra, W.M.; Normando, L.R.O.; Rosado, A.S.; Melo, V.M.M. Brazilian Semi-Arid Mangroves-Associated Microbiome as Pools of Richness and Complexity in a Changing World. Front. Microbiol. 2021, 12, 2485. [Google Scholar] [CrossRef]
  11. Palit, K.; Rath, S.; Chatterjee, S.; Das, S. Microbial Diversity and Ecological Interactions of Microorganisms in the Mangrove Ecosystem: Threats, Vulnerability, and Adaptations. Environ. Sci. Pollut. Res. 2022, 29, 32467–32512. [Google Scholar] [CrossRef]
  12. Mendes, L.W.; Tsai, S.M. Variations of Bacterial Community Structure and Composition in Mangrove Sediment at Different Depths in Southeastern Brazil. Diversity 2014, 6, 827–843. [Google Scholar] [CrossRef]
  13. Huergo, L.F.; Rissi, D.V.; Elias, A.S.; Gonçalves, M.V.; Gernet, M.V.; Barreto, F.; Dahmer, G.W.; Reis, R.A.; Pedrosa, F.O.; Souza, E.M.; et al. Influence of Ancient Anthropogenic Activities on the Mangrove Soil Microbiome. Sci. Total Environ. 2018, 645, 1–9. [Google Scholar] [CrossRef] [PubMed]
  14. do Carmo Linhares, D.; Saia, F.T.; Duarte, R.T.D.; Nakayama, C.R.; de Melo, I.S.; Pellizari, V.H. Methanotrophic Community Detected by DNA-SIP at Bertioga’s Mangrove Area, Southeast Brazil. Microb. Ecol. 2021, 81, 954–964. [Google Scholar] [CrossRef]
  15. Mendes, L.W.; Tsai, S.M. Distinct Taxonomic and Functional Composition of Soil Microbiomes along the Gradient Forest-Restinga-Mangrove in Southeastern Brazil. Antonie Van Leeuwenhoek 2018, 111, 101–114. [Google Scholar] [CrossRef]
  16. Andreote, F.D.; Jiménez, D.J.; Chaves, D.; Dias, A.C.F.; Luvizotto, D.M.; Dini-Andreote, F.; Fasanella, C.C.; Lopez, M.V.; Baena, S.; Taketani, R.G.; et al. The Microbiome of Brazilian Mangrove Sediments as Revealed by Metagenomics. PLoS ONE 2012, 7, e38600. [Google Scholar] [CrossRef] [PubMed]
  17. Cohen, M.C.L.; Lara, R.J. Temporal Changes of Mangrove Vegetation Boundaries in Amazonia: Application of GIS and Remote Sensing Techniques. Wetl. Ecol. Manag. 2003, 11, 223–231. [Google Scholar] [CrossRef]
  18. Fernandes, S.O.; Kirchman, D.L.; Michotey, V.D.; Bonin, P.C.; Lokabharathi, P.A. Bacterial Diversity in Relatively Pristine and Anthropogenically-Influenced Mangrove Ecosystems (Goa, India). Braz. J. Microbiol. 2014, 45, 1161–1171. [Google Scholar] [CrossRef]
  19. Cardenas, S.M.M.; Cohen, M.C.L.; Ruiz, D.P.C.; Souza, A.V.; Gomez-Neita, J.S.; Pessenda, L.C.R.; Culligan, N. Death and Regeneration of an Amazonian Mangrove Forest by Anthropic and Natural Forces. Remote Sens. 2022, 14, 6197. [Google Scholar] [CrossRef]
  20. Oliveira, M.V.C.; Henrique, M.C. In the Middle of the Road, There Was a Swamp: The Social and Environmental Impacts of the Bragança-Ajuruteua Highway, Pará, Brazil. Hist. Cienc. Saude Manguinhos 2018, 25, 497–514. [Google Scholar] [CrossRef]
  21. Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data. 2010. Available online: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/2019 (accessed on 9 April 2023).
  22. Edgar, R.C. SEARCH_16S: A New Algorithm for Identifying 16S Ribosomal RNA Genes in Contigs and Chromosomes. bioRxiv 2017, 124131. [Google Scholar] [CrossRef]
  23. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA Ribosomal RNA Gene Database Project: Improved Data Processing and Web-Based Tools. Nucleic Acids Res. 2013, 41, D590–D596. [Google Scholar] [CrossRef]
  24. McMurdie, P.J.; Holmes, S. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 2013, 8, e61217. [Google Scholar] [CrossRef] [PubMed]
  25. Oksanen, J.; Legendre, P.; O’Hara, B.; Stevens, M.H.H.; Oksanen, M.J.; Suggests, M. Vegan: Community Ecology Package. R Package Version 2.5-7. Community Ecol. Package 2020, 10, 31. [Google Scholar]
  26. Khleborodova, A. Lefser: R Implementation of the LEfSE Method for Microbiome Biomarker Discovery. R Package Version 1.8.0. Available online: https://github.com/waldronlab/lefser.2022 (accessed on 9 April 2023).
  27. Nogueira, V.L.R.; Rocha, L.L.; Colares, G.B.; Angelim, A.L.; Normando, L.R.O.; Cantão, M.E.; Agnez-Lima, L.F.; Andreote, F.D.; Melo, V.M.M. Microbiomes and Potential Metabolic Pathways of Pristine and Anthropized Brazilian Mangroves. Reg. Stud. Mar. Sci. 2015, 2, 56–64. [Google Scholar] [CrossRef]
  28. Haldar, S.; Nazareth, S.W. Taxonomic Diversity of Bacteria from Mangrove Sediments of Goa: Metagenomic and Functional Analysis. 3 Biotech 2018, 8, 436. [Google Scholar] [CrossRef]
  29. Wu, P.; Xiong, X.; Xu, Z.; Lu, C.; Cheng, H.; Lyu, X.; Zhang, J.; He, W.; Deng, W.; Lyu, Y.; et al. Bacterial Communities in the Rhizospheres of Three Mangrove Tree Species from Beilun Estuary, China. PLoS ONE 2016, 11, e0164082. [Google Scholar] [CrossRef] [PubMed]
  30. Gong, B.; Cao, H.; Peng, C.; Perčulija, V.; Tong, G.; Fang, H.; Wei, X.; Ouyang, S. High-Throughput Sequencing and Analysis of Microbial Communities in the Mangrove Swamps along the Coast of Beibu Gulf in Guangxi, China. Sci. Rep. 2019, 9, 1–10. [Google Scholar] [CrossRef]
  31. Sadaiappan, B.; Prasannakumar, C.; Subramanian, K.; Subramanian, M. Metagenomic Data of Vertical Distribution and Abundance of Bacterial Diversity in the Hypersaline Sediments of Mad Boon-Mangrove Ecosystem, Bay of Bengal. Data Brief. 2019, 22, 716–721. [Google Scholar] [CrossRef]
  32. Luis, P.; Saint-Genis, G.; Vallon, L.; Bourgeois, C.; Bruto, M.; Marchand, C.; Record, E.; Hugoni, M. Contrasted Ecological Niches Shape Fungal and Prokaryotic Community Structure in Mangroves Sediments. Environ. Microbiol. 2019, 21, 1407–1424. [Google Scholar] [CrossRef]
  33. Cotta, S.R.; Cadete, L.L.; van Elsas, J.D.; Andreote, F.D.; Dias, A.C.F. Exploring Bacterial Functionality in Mangrove Sediments and Its Capability to Overcome Anthropogenic Activity. Mar. Pollut. Bull. 2019, 141, 586–594. [Google Scholar] [CrossRef]
  34. Li, Y.; Zheng, L.; Zhang, Y.; Liu, H.; Jing, H. Comparative Metagenomics Study Reveals Pollution Induced Changes of Microbial Genes in Mangrove Sediments. Sci. Rep. 2019, 9, 1–11. [Google Scholar] [CrossRef]
  35. Ullah, R.; Yasir, M.; Khan, I.; Bibi, F.; Sohrab, S.S.; Al-Ansari, A.; Al-Abbasi, F.; Al-Sofyani, A.A.; Daur, I.; Lee, S.W.; et al. Comparative Bacterial Community Analysis in Relatively Pristine and Anthropogenically Influenced Mangrove Ecosystems on the Red Sea. Can. J. Microbiol. 2017, 63, 649–660. [Google Scholar] [CrossRef] [PubMed]
  36. Mushinski, R.M.; Zhou, Y.; Gentry, T.J.; Boutton, T.W. Bacterial Metataxonomic Profile and Putative Functional Behavior Associated with C and N Cycle Processes Remain Altered for Decades after Forest Harvest. Soil. Biol. Biochem. 2018, 119, 184–193. [Google Scholar] [CrossRef]
  37. Naether, A.; Foesel, B.U.; Naegele, V.; Wüst, P.K.; Weinert, J.; Bonkowski, M.; Alt, F.; Oelmann, Y.; Polle, A.; Lohaus, G.; et al. Environmental Factors Affect Acidobacterial Communities below the Subgroup Level in Grassland and Forest Soils. Appl. Environ. Microbiol. 2012, 78, 7398–7406. [Google Scholar] [CrossRef]
  38. Crits-Christoph, A.; Diamond, S.; Butterfield, C.N.; Thomas, B.C.; Banfield, J.F. Novel Soil Bacteria Possess Diverse Genes for Secondary Metabolite Biosynthesis. Nature 2018, 558, 440–444. [Google Scholar] [CrossRef]
  39. Kielak, A.M.; Castellane, T.C.L.; Campanharo, J.C.; Colnago, L.A.; Costa, O.Y.A.; Da Silva, M.L.C.; Van Veen, J.A.; Lemos, E.G.M.; Kuramae, E.E. Characterization of Novel Acidobacteria Exopolysaccharides with Potential Industrial and Ecological Applications. Sci. Rep. 2017, 7, 1–11. [Google Scholar] [CrossRef] [PubMed]
  40. Taketani, R.G.; Moitinho, M.A.; Mauchline, T.H.; Melo, I.S. Co-Occurrence Patterns of Litter Decomposing Communities in Mangroves Indicate a Robust Community Resistant to Disturbances. PeerJ 2018, 2018. [Google Scholar] [CrossRef]
  41. Dunfield, P.F.; Yuryev, A.; Senin, P.; Smirnova, A.V.; Stott, M.B.; Hou, S.; Ly, B.; Saw, J.H.; Zhou, Z.; Ren, Y.; et al. Methane Oxidation by an Extremely Acidophilic Bacterium of the Phylum Verrucomicrobia. Nature 2007, 450, 879–882. [Google Scholar] [CrossRef]
  42. Mohammadi, S.S.; Pol, A.; van Alen, T.; Jetten, M.S.M.; den Camp, H.J.M.O. Ammonia Oxidation and Nitrite Reduction in the Verrucomicrobial Methanotroph Methylacidiphilum Fumariolicum SolV. Front. Microbiol. 2017, 8, 1901. [Google Scholar] [CrossRef]
  43. Dias, A.C.F.; Dini-Andreote, F.; Taketani, R.G.; Tsai, S.M.; Azevedo, J.L.; de Melo, I.S.; Andreote, F.D. Archaeal Communities in the Sediments of Three Contrasting Mangroves. J. Soils Sediments 2011, 11, 1466–1476. [Google Scholar] [CrossRef]
  44. Prosser, J.I.; Nicol, G.W. Archaeal and Bacterial Ammonia-Oxidisers in Soil: The Quest for Niche Specialisation and Differentiation. Trends Microbiol. 2012, 20, 523–531. [Google Scholar] [CrossRef]
  45. Iino, T. Ignavibacteriae. In Bergey’s Manual of Systematics of Archaea and Bacteria; Wiley: New York, NY, USA, 2018; p. 1. [Google Scholar] [CrossRef]
  46. Quintero, I.J.; Castillo, A.M.; Mejía, L.C. Diversity and Taxonomy of Soil Bacterial Communities in Urban and Rural Mangrove Forests of the Panama Bay. Microorganisms 2022, 10, 2191. [Google Scholar] [CrossRef] [PubMed]
  47. Farag, I.F.; Youssef, N.H.; Elshahed, M.S. Global Distribution Patterns and Pangenomic Diversity of the Candidate Phylum “Latescibacteria” (WS3). Appl. Environ. Microbiol. 2017, 83, e00521-17. [Google Scholar] [CrossRef] [PubMed]
  48. Youssef, N.H.; Farag, I.F.; Rinke, C.; Hallam, S.J.; Woyke, T.; Elshahed, M.S. In Silico Analysis of the Metabolic Potential and Niche Specialization of Candidate Phylum “Latescibacteria” (WS3). PLoS ONE 2015, 10, e0127499. [Google Scholar] [CrossRef] [PubMed]
  49. Murphy, C.L.; Biggerstaff, J.; Eichhorn, A.; Ewing, E.; Shahan, R.; Soriano, D.; Stewart, S.; VanMol, K.; Walker, R.; Walters, P.; et al. Genomic Characterization of Three Novel Desulfobacterota Classes Expand the Metabolic and Phylogenetic Diversity of the Phylum. Environ. Microbiol. 2021, 23, 4326–4343. [Google Scholar] [CrossRef] [PubMed]
  50. Waite, D.W.; Chuvochina, M.; Pelikan, C.; Parks, D.H.; Yilmaz, P.; Wagner, M.; Loy, A.; Naganuma, T.; Nakai, R.; Whitman, W.B.; et al. Proposal to Reclassify the Proteobacterial Classes Deltaproteobacteria and Oligoflexia, and the Phylum Thermodesulfobacteria into Four Phyla Reflecting Major Functional Capabilities. Int. J. Syst. Evol. Microbiol. 2020, 70, 5972–6016. [Google Scholar] [CrossRef]
  51. Zhang, Y.; Gui, H.; Zhang, S.; Li, C. Diversity and Potential Function of Prokaryotic and Eukaryotic Communities from Different Mangrove Sediments. Sustainability 2022, 14, 3333. [Google Scholar] [CrossRef]
  52. Mori, K.; Suzuki, K.I. The Family Thioalkalispiraceae. Prokaryotes Gammaproteobacteria 2014, 9783642389221, 653–658. [Google Scholar] [CrossRef]
  53. Wiegand, S.; Jogler, M.; Jogler, C. On the Maverick Planctomycetes. FEMS Microbiol. Rev. 2018, 42, 739–760. [Google Scholar] [CrossRef]
  54. Wang, H.; Qi, Z.; Zheng, P.; Jiang, C.; Diao, X. Abundant and Rare Microbiota Assembly and Driving Factors between Mangrove and Intertidal Mudflats. Appl. Soil. Ecol. 2022, 174, 104438. [Google Scholar] [CrossRef]
Microorganisms 11 01389 g001 550
Figure 1. Location of each sampling point along highway PA-458 in relation to Brazil (red line) and the Brazilian Amazon territory (blue line). The (A) zone shows the degraded area on the left side of the road (P1), as the right side is preserved (P2). The (B) zone shows the area under recovery on the left side of the road (P3), as the right side is preserved (P4). The (C) zone shows two preserved areas on both sides of the road (P5 and P6).
Figure 1. Location of each sampling point along highway PA-458 in relation to Brazil (red line) and the Brazilian Amazon territory (blue line). The (A) zone shows the degraded area on the left side of the road (P1), as the right side is preserved (P2). The (B) zone shows the area under recovery on the left side of the road (P3), as the right side is preserved (P4). The (C) zone shows two preserved areas on both sides of the road (P5 and P6).
Microorganisms 11 01389 g001
Microorganisms 11 01389 g002 550
Figure 2. (A) Shannon alpha diversity index, (B) Chao1 alpha diversity index, and (C) Observed OTUs of all mangrove areas.
Figure 2. (A) Shannon alpha diversity index, (B) Chao1 alpha diversity index, and (C) Observed OTUs of all mangrove areas.
Microorganisms 11 01389 g002
Microorganisms 11 01389 g003 550
Figure 3. (A) Relative abundance at phylum level in mangrove environments. (B) Differentially abundant phyla according to mangrove preservation category.
Figure 3. (A) Relative abundance at phylum level in mangrove environments. (B) Differentially abundant phyla according to mangrove preservation category.
Microorganisms 11 01389 g003
Microorganisms 11 01389 g004 550
Figure 4. (A) Heatmap showing phylum abundances. (B) Principal Coordinate Analysis (PCoA) of Bray–Curtis distances between different collection points in the Amazonian Mangrove. Green dotted area shows the cluster of preserved and recovery samples.
Figure 4. (A) Heatmap showing phylum abundances. (B) Principal Coordinate Analysis (PCoA) of Bray–Curtis distances between different collection points in the Amazonian Mangrove. Green dotted area shows the cluster of preserved and recovery samples.
Microorganisms 11 01389 g004
Table
Table 1. Physicochemical parameters table. Carbon (C), organic matter (OM), total nitrogen (N), phosphorus (P), potassium (K), sodium (Na), aluminum (Al), calcium (Ca), magnesium (Mg), pH and potential acidity (H + Al) and saturation. The values of each point (P1, P2, P3, P4, P5, and P6) were obtained after mixing three replicates of each.
Table 1. Physicochemical parameters table. Carbon (C), organic matter (OM), total nitrogen (N), phosphorus (P), potassium (K), sodium (Na), aluminum (Al), calcium (Ca), magnesium (Mg), pH and potential acidity (H + Al) and saturation. The values of each point (P1, P2, P3, P4, P5, and P6) were obtained after mixing three replicates of each.
SamplesCOMNNRatioPKNaAlCaCa + MgpHH + AlCECSaturation
IDg/kgg/kg%g/kgC/Nmg/dm3cmol/dm3Watercmolc/dm3Total (cmol/dm3)Effective (cmol/dm3)Base (V%)Aluminum (m%)
P1 (Degraded)10.818.70.080.8113.391130323,0720533.25.90136.81136.831000.01
P2 (Preserved)16.528.50.070.7322.81644439570.12.58.56.43.8230.6626.9187.550.26
P3 (Recovery)10.4180.11.0310.185139119,96706.129.95.60.49120.75120.2999.60.02
P4 (Preserved)24.842.80.131.2919.24378810,95703.617.45.82.0969.1467.0796.970.04
P5 (Preserved)21.737.50.070.73303491911,97603.215.75.10.7970.9370.1898.890.04
P6 (Preserved)8.414.50.070.711.92887612,08203.115.25.50.970.8970.0398.730.04
Table
Table 2. Sequencing and alpha diversity indexes results.
Table 2. Sequencing and alpha diversity indexes results.
SampleCollection PointMangrove ZoneLibrary SizeOTUsChao1ShannonSimpson
S1P1Degraded90,50818462221.6865.6422080.9890705
S2P1Degraded131,79416722213.5355.4766730.9883609
S3P2Preserved72,72343075320.1976.9454220.9969483
S4P2Preserved93,86548766218.2627.0894950.9973286
S5P2Preserved65,00446635628.6417.0916190.9972898
S6P3Recovery43,32844915379.2877.1555580.9974265
S7P3Recovery124,52351856733.5967.2960430.9975854
S8P3Recovery89,94242845545.8466.9363120.9966584
S9P4Preserved80,00647385771.2787.0653840.9965857
S10P4Preserved84,81646346056.4637.0518240.9972325
S11P5Preserved67,83641255065.6426.9375170.9961980
S12P5Preserved55,65241405362.0786.8421380.9962226
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Costa, G.M.d.; Costa, S.S.; Baraúna, R.A.; Castilho, B.P.; Pinheiro, I.C.; Silva, A.; Schaan, A.P.; Ribeiro-dos-Santos, Â.; Graças, D.A.d. Effects of Degradation on Microbial Communities of an Amazonian Mangrove. Microorganisms 2023, 11, 1389. https://doi.org/10.3390/microorganisms11061389

AMA Style

Costa GMd, Costa SS, Baraúna RA, Castilho BP, Pinheiro IC, Silva A, Schaan AP, Ribeiro-dos-Santos Â, Graças DAd. Effects of Degradation on Microbial Communities of an Amazonian Mangrove. Microorganisms. 2023; 11(6):1389. https://doi.org/10.3390/microorganisms11061389

Chicago/Turabian Style

Costa, Gleyciane Machado da, Sávio Souza Costa, Rafael Azevedo Baraúna, Bruno Pureza Castilho, Izabel Cruz Pinheiro, Artur Silva, Ana Paula Schaan, Ândrea Ribeiro-dos-Santos, and Diego Assis das Graças. 2023. "Effects of Degradation on Microbial Communities of an Amazonian Mangrove" Microorganisms 11, no. 6: 1389. https://doi.org/10.3390/microorganisms11061389

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop