African Journal of
Microbiology Research

  • Abbreviation: Afr. J. Microbiol. Res.
  • Language: English
  • ISSN: 1996-0808
  • DOI: 10.5897/AJMR
  • Start Year: 2007
  • Published Articles: 5235

Full Length Research Paper

Molecular identification of bacterial isolates from the rhizospheres of four mangrove species in Kenya

Edith M. Muwawa
  • Edith M. Muwawa
  • Department of Biological Sciences, School of Pure and Applied Sciences, Pwani University, P. O. Box 195-80108 Kilifi, Kenya.
  • Google Scholar
Huxley M. Makonde
  • Huxley M. Makonde
  • Department of Pure and Applied Sciences, Technical University of Mombasa, P. O. Box 90420-80100, Mombasa, Kenya.
  • Google Scholar
Joyce M. Jefwa
  • Joyce M. Jefwa
  • Departement of Biological Sciences, School of Pure and Applied Sciences, Pwani University, P. O. Box 195, 80108 Kilifi, Kenya.
  • Google Scholar
James H. P. Kahindi
  • James H. P. Kahindi
  • Departement of Biological Sciences, School of Pure and Applied Sciences, Pwani University, P. O. Box 195, 80108 Kilifi, Kenya.
  • Google Scholar
Damase P. Khasa
  • Damase P. Khasa
  • Centre for Forest Research and Institute for Systems and Integrative Biology, Université Laval, 1030 Avenue de la Médecine, Québec, QC, G1V0A6, Canada.
  • Google Scholar


  •  Received: 27 July 2020
  •  Accepted: 14 September 2020
  •  Published: 30 September 2020

 ABSTRACT

Mangrove ecosystems provide a unique ecological niche for diverse microbial communities. This study aimed to identify bacterial isolates from the rhizospheres of four mangrove species (Sonneratia alba, Rhizophora mucronata, Ceriops tagal and Avicennia marina) using the 16S rRNA gene analysis approach. Rhizospheric sediment samples of the mangroves were collected from Mida creek and Gazi bay, Kenya, using standard protocols. A total of 36 representative bacterial isolates were analyzed. The isolates were characterized using morphological and molecular characters. Pure gDNA was extracted from the isolates, polymerase chain reaction amplified and sequenced. The 16S rRNA gene sequences were BLASTN analyzed against the Genbank database; the closest taxonomically related bacterial sequences were retrieved and used for phylogenetic analysis using MEGA X software. Morphologically, the isolates differed in their cultural characteristic in color, shape, margin, elevation and gram reaction. Phylogenetic analysis classified the isolates into five genera, namely Bacillus, Pseudomonas, Micrococcus, Microbacterium and Streptomyces that belong to three different phyla (Firmicutes, Proteobacteria and Actinobacteria). The findings show that the underexplored tropical mangrove rhizospheres harbor useful diverse bacteria. Further analysis of the bioactive production potential of the isolates will give more insights into the types of bioactive compounds produced and their biotechnological potential.

 

Key words: 16S rRNA gene sequence, rhizosphere, mangrove sediments, marine bacteria, biotechnology.


 INTRODUCTION

Mangroves occur in the intertidal zone of sheltered shores, lagoon, estuarine tidal stream, and swamps mudflats of  the tropical  and  subtropical  regions  of  the world (Sengupta et al., 2015). Mangrove ecosystems have unique conditions, including high salinity, high moisture, strong wind, high tides, anaerobic condition and muddy soils (Dissanayake and Chandrasekara, 2014).  Mangrove forests are considered as one of the most prolific ecosystems in the world that have well established biological, cultural, and economic importance (Goessens et al., 2014). Besides, the mangrove ecosystems have significant ecological functions that include filtering and reducing dissolved and particulate nutrients, serving as a sink for carbon, nitrogen and phosphorus, as well as retaining heavy metals from adjacent land and fluvial imports (Sanders et al., 2014).
 
Mangrove ecosystems harbor a large number of microbial communities, including bacteria, fungi, archaea, protozoa, etc whose abundance and activities are controlled by various physical and chemical factors in this environment. Thus, mangrove ecosystems form an ecological niche for a wide spectrum of microbial diversity due to their unique geographical conditions (Xu et al., 2014). Diverse groups of bacteria including diazosthrophs, phosphate solubilizers, cellulose decomposers, nitrifiers and denitrifiers, sulphur oxidizers and iron oxidizers have been identified in mangrove ecosystems (Holguin et al., 2001). The dynamic conditions and complexity of the mangrove ecosystems have generated increasing interest among microbial ecologists who sought to understand these ecosystems better.
 
Furthermore, the phylogenetic and functional description of microbial diversity in the mangrove ecosystems have not been adequately addressed to the same extent as that of terrestrial environments (Saseeswari et al., 2016). In Kenya, microbial communities have widely been studied in the terrestrial environments (Makonde et al., 2015; Kambura et al., 2016a; Muwawa et al., 2016; Josiah et al., 2018; Kambura et al., 2016b; Salano et al., 2017; Kawaka et al., 2018; Muhonja et al., 2018a, b; Salano et al., 2018)and with less focus on the mangrove ecosystems (Jenoh et al., 2019; Ntabo et al., 2018). This is partly, due to skepticism regarding the existence of indigenous populations of mangrove microbial communities. It is known that microbial communities from the terrestrial environment produce resistant spores that are transported from land into the marine environment, where they can remain available but dormant for many years (Bull et al., 2000). Thus, it has been frequently assumed that microbial communities isolated from marine samples are of mere terrestrial origin (Bull et al., 2000).
 
Studies on microbial diversity, their distribution and functional roles in mangrove ecosystems are essential, since they would improve our understanding of their roles and interactions in such ecosystems (Kathiresan and Selvam, 2006). Microorganisms form an important component of mangrove ecosystems, and there is evidence that they are key to the biogeochemical productivity of the mangrove ecosystem (Zhang et al., 2017). Hence, there is the need to understand the bacterial species composition underlining mangrove ecosystems, especially within the rhizosphere of mangrove species, which still remains  unclear.  Previous studies on mangroves in Kenya have concentrated on floristic composition and distribution of mangrove species, economic utilization and regeneration strategies of the principal species (Mohamed et al., 2009). However, data on microbial community diversity is limited due to inadequate efforts spent in exploring the mangrove habitats for microbial diversity (Ntabo et al., 2018).
 
The 16S rRNA gene is approximately 1.5-kilobase pair DNA fragment with desirable properties and is the most commonly used molecular marker. The functional constancy of this gene assures it is a valid molecular chronometer, which is essential for a precise assessment of phylogenetic relatedness of organisms. This gene is present in all prokaryotic cells and has conserved and variable sequence regions evolving at very different rates. These characteristics allow the use of 16S rRNA in the assignment of close relationships at the genus (Clarridge, 2004; Srinivasan et al., 2015)and in some cases at the species level (Conlan et al., 2012; Fettweis et al., 2012). In addition, dedicated 16S databases (Cole et al., 2009; Pruesse et al., 2007)that include near full length sequences for a large number of strains and their taxonomic placements exist. Therefore, this study was designed to isolate and characterize bacterial species from the rhizospheres of four mangrove species (Avicennia marina (Forsk.) Vierh., Ceriops tagal (Perr.) C.B. Robinson., Rhizophora mucronata Poir. and Sonneratia alba Griff.) that are commonly found along the Kenyan Coastline by analyzing the 16S rRNA gene region.


 MATERIALS AND METHODS

Ethical statement
 
The National Commission for Science, Technology and Innovation of Kenya (NACOSTI) approved this research study, National Environmental Management Authority of Kenya (NEMA) provided the access permit (for field sampling), Kenya Wild life Services (KWS), and Kenya Plant Health Inspectorate Services (KEPHIS) provided permits that facilitated the shipment of samples to Laval University, Canada. The field studies neither involved endangered nor protected species.
 
Study site
 
We investigated two mangrove sites (Mida Creek and Gazi Bay) in Kenya (Figure 1).  Mida Creek, which lies in a planigraphic area of 32 km2, is located in Kilifi County (3°21'S, 39°59'E), about 88 Km North of Mombasa and approximately 25 km South of Malindi town (Lang’at, 2008). The monthly temperature is between 23 and 27°C, rising to a maximum temperature of 34°C in the hottest months and a minimum temperature of 20°C in the coldest months; and total annual precipitation ranging between 1000 and 1600 mm (Lang’at, 2008). Gazi bay is located in Kwale County (4°44′S, 39°51′E), South Coast of Kenya, approximately 55 km from Mombasa. The Bay is sheltered from strong waves by the presence of  the  Chale  peninsula  to  the East and a fringing coral reef to the South.  The climate is hot and humid, and the average annual temperature and humidity are about 28°C and up to 95%, respectively (Lang’at, 2008). Mangrove forests in Kenya often display the typical zonation pattern of mangroves in Eastern Africa: the seaward side is predominantly occupied by the Sonneratia and Rhizophora spp. (tall) assemblage, followed by Rhizophora, Bruguiera and Ceriops spp. in the middle zone and the Avicennia, Lumnitzera and Xylocarpus spp. complex with often dwarf Avicennia on the landward side (Dahdouh-Guebas et al., 2004; Matthijs et al., 1999).
 
 
Collection of samples
 
Sampling was conducted in May 2018, according to previously described methods (Wu et al., 2016). Four species of mangrove trees common to the two sites, namely A. marina, C. tagal, R. mucronate, and S. alba were identified by use of expertise from a plant taxonomist. Four mangrove trees of each species at intervals of 10 m were selected. For each species, the rhizosphere sediments (~100g) were sampled vertically along the base of the plant at depth (1-5 cm), using a standardized core sampler (Giannopoulos et al., 2019). A total of 32 samples (from 4 mangrove species x 4 replicates x 2 sites) were kept in sterile plastic bags. They were maintained in a dry iced box before they were transported and stored at -20°C prior to further analyses that were performed at the Laval University, Canada.
 
Physicochemical analysis of sediment samples
 
Nutrient analyses of soil samples for nitrogen, carbon, phosphorus, potassium, calcium, magnesium and sodium were conducted according to standard methods (Brupbacher et al., 1968). Determination of pH was done using the calcium chloride method at a ratio of 1:2 using a digital Corning pH meter 140 (Corning Life Sciences, Massachusetts, USA). The electrical conductivity was determined using the electrical conductivity meter type CDM 2d radiometer (Radiometer, Copenhagen, Denmark).
 
Isolation of bacteria from sediment samples
 
The sediment samples were pre-processed by air-drying at room temperature (27±1°C) for seven days and sieved with a 2.5mm sieve to remove larger particles such as stone and plant debris to obtain a consistent soil particle size for bacterial isolation. The isolation of bacteria from the sediment samples was performed by serial dilution method. About 0.1g of the sediment sample was suspended in 1ml sterile distilled water in a sterile 1.5ml Eppendorf tube and serial diluted to 10-3. One hundred µl of the10-1, 10-2, and 10-3 suspensions were spread in triplicate onto three different types of isolation media which included Dextrose nitrate agar, ISP2 agar and Actinomycetes isolation agar. All media were prepared according to the manufacturer's instructions.  All the plates were incubated at 28°C for 2-7 days. Follow up was made to observe any growth on the plates (Lee et al., 2014).
 
Morphological characterization of bacterial isolates
 
Colony morphologies of the bacterial isolates were described using standard microbiological criteria with special emphasis on pigmentation, shape, form, elevation and margin formation.  Preliminary characterization by Gram staining was done of each of the isolates using the method described by (Bergey and Holt, 1994).
 
Molecular characterization of the bacterial isolates
 
Genomic DNA (gDNA) extraction and PCR amplification
 
Pure genomic DNA was extracted from pure bacterial culture using the GenElute Bacterial Genomic DNA extraction kit according to the manufacturer's instructions. The extracted DNA was quantified using NanoDrop 2000 spectrophotometer (Thermo Fisher Waltham, MA, USA) and used as a template for the amplification of the 16S rRNA gene region. Nearly full-length 16S rRNA gene sequences was PCR-amplified using a universial bacterial primer pair 27F (5'-AGAGTTTGATCCTGGCTCAG-3') and 1492R (5'-GGTTACCTTGTTACGACTT-3'). The PCR was carried out in a 25µl reaction and consisted of 2.5 ml 10x PCR buffer, 0.75µl MgCl2, 0.5µldNTPs, 0.5µl of each primer, 0.2 µl platinum Taq (Invitrogen), 1µl of template DNA and 19.05µl of water. Amplification was performed with initial heating at 95°C for 30s followed by 30 cycles of denaturation at 95°C for 50s, annealing at 54°C for 50s and extension at 72°C for 1 min and a final extension period at 72°C for 5 min using MJ Research PTC-225 Peltier Thermal Cycler. Amplicons were confirmed by visualization on 1% ethidium bromide stained agarose gels under gel documentation chamber. The PCR products were sequenced directly using the Sanger sequencing platform at the Institute for Systems and Integrative Biology of Laval University, Canada.
 
Phylogenetic analysis
 
Sequences of the isolates were manually edited in chromas and checked for presence of artifacts or sequencing errors using Mallard software (Ashelford et al., 2006), an NCBI bioinformatic tool for detecting chimera sequences.  A search for similar sequences using BLASTN (Altschul et al., 1990)was performed, and sequence alignment was performed using the CLUSTAL Omega program (http://www.clustal.org) against the nearest neighbours.  A neighbor-joining tree of the aligned sequences was constructed (Saitou and Nei, 1987)using MEGA X software (Kumar et al., 2018). Evolutionary distances were computed using the Maximum Composite  Likelihood   method  (Tamura  et  al.,  2004).  To  obtain statistical support values for the branches, bootstrapping (Felsenstein, 1985)was conducted with 1000 replicates. All sites, including gaps in the sequence alignment, were excluded pairwise in the phylogenetic analysis. Using the resultant neighbor-joining tree, each isolate was assigned to the proper taxonomic group. The taxonomic assignment was confirmed at a 95% confidence level using the RDP Naïve Bayesian rRNA Classifier Version 2.11 on the RDP website (Wang et al., 2007).
 
Statistical analyses
 
Data from physicochemical parameters were analyzed using R v3.6.1 (Somanathan et al., 2004). A two-factor (sites and mangrove species differences) test of differences in physicochemical parameters was done by the non-parametric Kruskal-Wallis H test using the agricolae package implemented in R (de Mendiburu, 2020). Post hoc test for mean separations was based on Fisher's least significant difference. Results were expressed as the mean ± SD. A p-value of ≤ 0.05 was considered statistically significant. All experiments were performed independently at least three times.


 RESULTS

Physicochemical analysis of sediment samples
 
The pH and calcium were significantly higher (Kruskal-Wallis, p ≤ 0.05) in all mangrove plant species of Mida creek compared to Gazi bay, which had significantly higher EC and salinity values (Table 1). Apart from the rhizosphere sediment samples of R. mucronata, all other rhizosphere sediment samples of the mangrove species in Gazi bay had significantly lower (p < 0.05) physicochemical properties compared to the mangrove species in Mida creek. The physicochemical parameters that were higher in the rhizosphere of R. mucronata in Gazi bay included potassium, sodium, phosphorus, total carbon, nitrogen, salinity and electrical conductivity (Table 1).
 
Isolation and morphological characterization of bacteria
 
A total of 50 bacterial isolates were isolated from the rhizospheric sediments of the mangrove species. The isolates were able to grow within a period of between three and seven days. Morphologically, the isolates exhibited diverse colony characteristics differing in their form, elevation, color, margin, cell arrangement and the Gram reaction. Majority of the isolates were circular in form, cream in color, raised elevation and had entire margins. All the isolates were rod-shaped with the exception of two isolates (SAM110B1; SAG210B1) which were cocci. The gram reaction was also positive in all the isolates with the exception of one isolate (SAM210B1) (Table 2).
 
Molecular characterization of the bacterial isolates
 
A total of 36 representative bacterial isolates from the rhizospheric sediments of the four-mangrove species were picked based on their morphological characters and further identified by analysis of their 16S ribosomal RNA gene sequences. About 44, 28, 19, and 8% of the bacterial isolates were recovered from the rhizospheric sediments of A. marina, C. tagal, S. alba and R. mucronata, respectively (Table 3). The isolates (with their accession numbers in parenthesis) in the inferred phylogenetic tree (Figure 2) were diverse and affiliated with known species from five genera (Streptomyces, Microbacterium, Micrococcus, Pseudomonas and Bacillus). Comparison of the newly isolated 16S rRNA gene sequences to known bacterial sequences in the Genbank database using BLASTN analysis indicated sequence similarities of between 98 and 100% (Table 3).
 
 
 
 
 
Affiliation of 16S rRNA gene sequences of the isolates
 
The   inferred   phylogenetic    tree    grouped   the isolates into three main clusters belonging to the phyla Firmicutes, Proteobacteria and Actinobacteria (Figure 2). Most of the isolates (~55%) were affiliated with several known bacterial species (with >97% sequence identity) belonging to the phylum Actinobacteria (Table 3). About 42% of the total bacterial isolates had between 98 and 100% sequence identities with known members of the genus Bacillus and 3% of the total isolates had 100% sequence identity with Pseudomonas stutzeri [KM076597], which belong to the phylum Proteobacteria (Table 3). About 42% of the isolates formed another large cluster with known members from the genus Bacillus. Within this large Bacillus cluster, was a sub-cluster 2 (supported by a bootstrap value of 100%) that was represented by isolates CTM15B1 [MT2494405], CTM210B2 [MT249409], AVM210B6 [MT249397], CTM25B3 [MT249407], SAM15B1 [MT249418] and AVG210B1 [MT249388] and some known Bacillus species (B. cereus  [MT020418],  B.  cereus   [MT544972],  B. cereus [MG491524], B. mycoides [MG598443] and B. proteolyticus [MT573794]) (Figure 2). Isolate SAM210B1 [MT249419] was obtained from the rhizospheric sediments of S. alba and had 100% sequence identity with Pseudomonas stutzeri [KM076597].
 
Methanoculleus thermophiles (AB065297) was used to root the tree. Pseudomonas zhhaodongesis [MH283851] formed a minor cluster supported with a bootstrap value of 100% (Figure 2).  Isolates SAG210B1 [MT249414] and SAM110B1 [MT249420] together with closely related known bacterial species (Micrococcus luteus [MH142592], Micrococcus aloeverae [KX082870] and Microbacterium paludicola [NR_114939] formed a minor sub-cluster with a bootstrap value of 99% in the inferred phylogenetic tree (Figure 2). The genus Streptomyces was represented by the majority of the isolates (50%) that together with other closely related known species formed a single large cluster supported with  a  bootstrap  value  of  100%  in  the  inferred phylogenetic tree (Figure 2 and Table 3). This large actinobacterial cluster had a sub-cluster 1, which was represented by isolates (AVM25B2 [MT249392], AVM25B1 [MT249391], AVM210B5 [MT249396], AVM410B1 [MT249399], AVM15B3 [MT249390], AVM210B4 [MT249395], AVM410B2 [MT249400], AVM210B2 [MT249393], CTG25B1 [MT249401] and RMG15B3 [MT249411] that had >97% sequence similarities with known species (Streptomyces sanyensis [NR_116599], Streptomyces sp. [MH613761], Streptomyces sp. [KX641393], and Streptomyces sp. [MK615854].
 


 DISCUSSION

In this study, we isolated and identified rhizospheric bacterial communities from four mangrove species along the Kenyan coastline using the 16S ribosomal RNA approach. A total of 50 bacterial isolates were obtained from  the   rhizospheric   sediment  samples  of  the  four-mangrove species. After morphotyping, a total of 36 bacterial isolates were further characterized. A close observation on the distribution of the identified bacterial isolates (36 isolates) among the mangrove species showed that most isolates (44% of the total isolates) were recovered from the rhizospheric sediments of A. marina in both Gazi bay and Mida creek (Table 3). This observation can be explained by the variation in nutrients and mangrove tree species in the two study sites. Nutrients such as calcium, magnesium, nitrogen, phosphorus, total carbon and pH (Table 1) may have influenced the bacterial diversity of A. marina. For example, most of the recovered bacteria from the rhizosphere of A. marina belonged to the genera Streptomyces and to a lesser extent the genus Bacillus, whose members were recovered the most in the rhizospheres of C. tagal and S. alba in Mida creek and Gazi bay. This demonstrates that the variation in nutrients and mangrove tree species may have contributed to the observed species distribution. Other studies in mangroves (Krüger et  al.,  2017;  Wu  et  al.,  2016)  and terrestrial ecosystems (Mendes et al., 2013)have indicated that bacterial communities in the rhizosphere are influenced by plant species.
 
The results from morphological characterization indicated that the majority of the isolates were circular in form, cream in color, raised elevation, had entire margins and were gram positive. Morphological features have been widely used by most researchers for preliminary identification and placing of bacterial isolates into different morphotypes (Anna et al., 2018; Haldar and Nazareth, 2018; Saseeswari et al., 2016). Although useful, the information on morphological characters is insufficient to be used for final bacterial identification and, therefore, has to be supplemented with other data including the DNA relatedness studies, DNA-DNA hybridization, small subunit (SSU) sequences, cell wall composition and other characterization (Sarker et al., 2015).
 
In this study, the phylogenetic analysis of the 16S rRNA gene sequences of the isolates helped to identify and phylogenetically placed them into three phyla, namely Firmicutes, Proteobacteria and Actinobacteria. The phylum Firmicutes was the second most dominant and represented by members of the genus Bacillus. Several other studies have reported the occurrence of bacterial species from the genus Bacillus in mangrove habitats (Anna et al., 2018; Haldar and Nazareth, 2018; Mo et al., 2020). One of the reasons is that Bacillus species are easy to culture, and some can form endospores, whose primary function is to ensure their survival under harsh environmental conditions. Bacillus species are important for degradation of cellulose (Kurniawan et al., 2018)and phenolic compounds (Anna et al., 2018). They have also been reported to play a significant role in nitrogen fixation in the mangrove environment (Tam et al., 2017). Notably, members from this genus are considered beneficial to plant growth in the mangrove ecosystems as reported by Haldar and Nazareth (2018)who isolated phosphate solubilizing Bacillus species from mangrove soil. Proteobacteria was the least observed phyla in our study and was represented by one isolate of the genus Pseudomonas. This is consistent with the findings of Behera et al. (2014a)and Kurniawan et al. (2018)who reported the occurrence of Pseudomonas species in mangrove soils. Pseudomonas species are known to be key players in cellulose degradation and sulfur oxidation in the mangrove ecosystems (Behera et al., 2014b).
 
The phylum Actinobacteria was represented by the majority of the isolates since the media and protocol used for the isolation favored their recovery. Members from three genera (Streptomyces, Mycobacterium and Micrococcus) were obtained. Species from these genera are important for recycling biomaterials by humus formation and decomposition (Maldonado et al., 2005). In mangrove ecosystems, members of the phylum Actinobacteria are known to play important roles in mineralization   of   organic   matter,   control  of   mineral nutrients cycle and environmental protection (Pupin and Nahas, 2014). Literature indicates the importance of Actinobacteria from mangrove ecosystems owing to their economic value as a source of antibiotics (Mohan et al., 2014; Naik et al., 2013). The genera Mycobacterium and Micrococcus were the least identified among the Actinobacteria. Other studies have also reported the occurrence of these genera in the mangrove ecosystems (Behera et al., 2014a; Lee et al., 2014). Members from the genus Streptomyces were identified as the most dominant in our study. Species from this genus have been known to play key roles in soil ecology because of their ability to scavenge nutrients and, in particular, to hydrolyze a wide range of polysaccharides and other natural macromolecules (Barka et al., 2016). In addition, Streptomyces species have been useful to the pharmaceutical industry due to their enhanced capacity to produce secondary metabolites with diverse biological activities (Naik et al., 2013; Sengupta et al., 2015). Our results also concur with other studies (Priya et al., 2014; Malek et al., 2014)who also reported the occurrence of Streptomyces species in the mangrove sediments.
 
Bacteria are considered as potent and functional enzyme producer due to their high growth rate, availability of multi-enzyme complexes and stability at the harsh condition (Ladeira et al., 2015). Several studies have demonstrated diverse useful potential of bacteria isolated from mangrove ecosystems (Behera et al., 2014a; Kunasundari et al., 2017; Naresh et al., 2019; Soares Júnior et al., 2013). Our findings confirm that mangrove rhizospheres are a source of diverse bacterial communities that have been shown to produce secondary metabolites. For instance, most of the isolates recovered are from the genera that have been implicated in the production of different secondary metabolites including antimicrobial compounds and different enzymes in other studies (Naik et al., 2013; Pupin and Nahas, 2014; Behera et al., 2014a; Azman et al., 2015; Barka et al., 2016; Rasigraf et al., 2019; Wu et al., 2016). Further comprehensive studies focusing on isolation and screening of bacterial isolates for production of novel and or improved natural products is, therefore, recommended in order to give more insights on the types of antibacterial compounds produced and their effectiveness as antimicrobial agents.


 CONFLICT OF INTERESTS

The authors declare that they have no conflict of interests.


 ACKNOWLEDGEMENTS

The authors appreciate the financial support provided by the Queen Elizabeth II  Jubilee  Scholarship to  EMM and NSERC discovery grant to DPK and the International Foundation for Science (Ref No.: IFS Grant A/5719-1) to HMM. The NACOSTI, NEMA, KWS and KEPHIS are acknowledged for approving the research study and providing permits that facilitated field studies and shipment of samples to Canada and also thank the Centre for Forest Research and Institute for Systems and Integrative Biology of Laval University, Canada and Pwani University for support during the project.

 



 REFERENCES

Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990). Basic local alignment search tool. Journal of Molecular Biology 215(3):403-410.
Crossref

 

Anna PSAR, Bruno FRdeO, Renan de SS, Igor DAR, Ariana AR, Danns PB, Matheus MV, José DGV (2018). Isolation and characterization of phenol degrading Bacillus species from Southeast Brazilian mangrove sediment. African Journal of Microbiology Research 12(46):1032-1038.
Crossref

 
 

Ashelford KE, Chuzhanova NA, Fry JC, Jones AJ, Weightman AJ (2006). New screening software shows that most recent large 16S rRNA gene clone libraries contain chimeras. Applied and Environmental Microbiology 72(9):5734-5741.
Crossref

 
 

Azman AS, Othman I, Velu SS, Chan KG, Lee LH (2015). Mangrove rare actinobacteria: Taxonomy, natural compound, and discovery of bioactivity. Frontiers in Microbiology 6:1-15.
Crossref

 
 

Barka EA, Vatsa P, Sanchez L, Gaveau-vaillant N, Jacquard C, Klenk H, Clément C, Ouhdouch Y, Wezel P (2016). Taxonomy, Physiology, and Natural Products of Actinobacteria. Microbiology and Molecular Biology Reviews 80(1):1-44.
Crossref

 
 

Behera BC, Parida S, Dutta SK, Thatoi HN (2014a). Isolation and Identification of Cellulose Degrading Bacteria from Mangrove Soil of Mahanadi River Delta and Their Cellulase Production Ability. American Journal of Microbiological Research 2(1):41-46.
Crossref

 
 

Behera BC, Patra M, Dutta SK, Thatoi HN (2014b). Isolation and Characterization of Sulphur Oxidising Bacteria from Mangrove Soil of Mahanadi River Delta and Their Sulphur Oxidising Ability. Journal of Applied and Environmental Microbiology 2(1):1-5.
Crossref

 
 

Bergey DH, Holt JG (1994). Bergey's manual of determinative bacteriology. 

 
 

Brupbacher RH, Bonner WP, Sedberry JRJ (1968). Analytical methods and procedures used in the soil testing laboratory: 15. View

 
 

Bull AT, Ward AC, Goodfellow M (2000). Search and Discovery Strategies for Biotechnology: The Paradigm Shift. Microbiology and Molecular Biology Reviews 64(3):573-606.
Crossref

 
 

Clarridge JE (2004). Impact of 16S rRNA Gene Sequence Analysis for Identification of Bacteria on Clinical Microbiology and Infectious Diseases. Clinical Microbiology Reviews 17(4):840-862.
Crossref

 
 

Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM (2009). The Ribosomal Database Project: Improved alignments and new tools for rRNA analysis. Nucleic Acids Research 37(1):141-145.
Crossref

 
 

Conlan S, Kong HH, Segre JA (2012). Species-Level Analysis of DNA Sequence Data from the NIH Human Microbiome Project. PLoS ONE 7(10).
Crossref

 
 

Dahdouh-Guebas F, Van Pottelbergh I, Kairo JG, Cannicci S, Koedam N (2004). Human-impacted mangroves in Gazi (Kenya): Predicting future vegetation based on retrospective remote sensing, social surveys, and tree distribution. Marine Ecology Progress Series 272:77-92.
Crossref

 
 

de Mendiburu F (2020). agricolae: Statistical Procedures for Agricultural Research. R package version 1.3-2.

 
 

Dissanayake N, Chandrasekara U (2014). Effects of Mangrove Zonation and the Physicochemical Parameters of Soil on the Distribution of Macrobenthic Fauna in Kadolkele Mangrove Forest, a Tropical Mangrove Forest in Sri Lanka. Advances in Ecology, pp. 1-13.
Crossref

 
 

Felsenstein J (1985). Confidence Limits on Phylogenies: An Approach Using the Bootstrap. Evolution 39(4):783.
Crossref

 
 

Fettweis JM, Serrano MG, Sheth NU, Mayer CM, Glascock AL, Brooks JP, Jefferson KK, Buck GA (2012). Species-level classification of the vaginal microbiome. BMC Genomics 13(8):1-9.
Crossref

 
 

Giannopoulos G, Lee DY, Neubauer SC, Brown BL, Franklin RB (2019). A simple and effective sampler to collect undisturbed cores from tidal marshes.
Crossref

 
 

Goessens A, Satyanarayana B, Van Der Stocken T, Zuniga MQ, Mohd-Lokman H, Sulong I, Dahdouh-Guebas F (2014). Is Matang Mangrove Forest in Malaysia sustainably rejuvenating after more than a century of conservation and harvesting management? PLoS ONE 9:8.
Crossref

 
 

Haldar S, Nazareth SW (2018). Taxonomic diversity of bacteria from mangrove sediments of Goa: metagenomic and functional analysis. 3 Biotech 8:436-446.
Crossref

 
 

Holguin G, Vazquez P, Bashan Y (2001). The role of sediment microorganisms in the productivity, conservation, and rehabilitation of mangrove ecosystems: An overview. Biology and Fertility of Soils 33(4):265-278.
Crossref

 
 

Jenoh EM, De Villiers EP, De Villiers SM, Okoth S, Jefwa J, Kioko E, Kaimenyi D, Hendrickx M, Dahdouh-Guebas F, Koedam N (2019). Infestation mechanisms of two woodborer species in the mangrove Sonneratia alba J. Smith in Kenya and co-occurring endophytic fungi. PLoS ONE 14(10):1-20.
Crossref

 
 

Jenoh EM, Robert EMR, Lehmann I, Kioko E, Bosire JO, Ngisiange N, Dahdouh-Guebas F, Koedam N (2016). Wide ranging insect infestation of the pioneer mangrove Sonneratia alba by two insect species along the Kenyan coast. PLoS ONE 11(5):1-15.
Crossref

 
 

Josiah OK, Huxley MM, Hamadi IB, Anne TWM, Jun U (2018). Phylogenetic diversity of prokaryotes on the snow-cover of Lewis glacier in Mount Kenya. African Journal of Microbiology Research 12(24):574-579.
Crossref

 
 

Kambura AK, Mwirichia RK, Kasili RW, Karanja EN, Makonde HM, Boga HI (2016a). Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya. BMC Microbiology 16(1):1-12.
Crossref

 
 

Kambura AK, Romano KM, Remmy WK, Edward NK, Huxley MM, Hamadi IB (2016b). Diversity of fungi in sediments and water sampled from the hot springs of Lake Magadi and Little Magadi in Kenya. African Journal of Microbiology Research 10(10):330-338.
Crossref

 
 

Kathiresan K, Selvam MM (2006). Evaluation of beneficial bacteria from mangrove soil. Botanica Marina 49(1):86-88.
Crossref

 
 

Kawaka F, H, Dida M, Opala P, Ombori O, Maingi J, Muoma J (2018). Genetic diversity of symbiotic bacteria nodulating common bean (Phaseolus vulgaris) in western Kenya. PLoS ONE 13(11):1-13.
Crossref

 
 

Krüger C, Kohout P, Janoušková M, Püschel D, Frouz J, Rydlová J (2017). Plant communities rather than soil properties structure arbuscular mycorrhizal fungal communities along primary succession on a mine spoil. Frontiers in Microbiology 8:1-1.
Crossref

 
 

Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018). MEGA X: Molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution 35(6):1547-1549.
Crossref

 
 

Kunasundari B, Naresh S, Che Zakaria NZ (2017). Isolation and characterization of cellulase producing bacteria from tropical mangrove soil. ACM International Conference Proceeding Series Part F131935(9):34-37.
Crossref

 
 

Kurniawan A, Prihanto AA, Sari SP, Febriyanti D, Kurniawan A, Sambah AB, Asriani E (2018). Isolation and Identification of cellulolytic bacteria from mangrove sediment in Bangka Island. IOP Conference Series: Earth and Environmental Science 137(1):0-6.
Crossref

 
 

Ladeira SA, Cruz E, Delatorre AB, Barbosa JB, Martins MLL (2015). Cellulase production by thermophilic Bacillus sp. SMIA-2 and its detergent compatibility. Electronic Journal of Biotechnology 18(2):110-115.
Crossref

 
 

Lang'at JKS (2008). Variability of mangrove forests along the Kenyan coast. 

 
 

Lee L, Zainal N, Azman A, Eng S, Goh B, Yin W, Mutalib NA, Chan K (2014). Diversity and Antimicrobial Activities of Actinobacteria Isolated from Tropical Mangrove Sediments in Malaysia. Hindawi: 1-14.
Crossref

 
 

Makonde HM, Mwirichia R, Osiemo Z, Boga HI, Klenk HP (2015). 454 Pyrosequencing-based assessment of bacterial diversity and community structure in termite guts, mounds and surrounding soils. SpringerPlus 4(1):471.

 
 

Maldonado LA, Stach JEM, Pathom-Aree W, Ward AC, Bull AT, Goodfellow M (2005). Diversity of cultivable actinobacteria in geographically widespread marine sediments. International Journal of General and Molecular Microbiology 87(1):11-18.
Crossref

 
 

Malek NA, Jalal A, Chowdhury K, Zainuddin Z (2014). Selective Isolation of Actinomycetes from Mangrove Forest of Pahang, Malaysia. International Conference on Agriculture, Biology and Environmental Sciences 14:9-13.

 
 

Matthijs S, Tack J, van Speybroeck D, Koedam N (1999). Mangrove species zonation and soil redox state, sulphide concentration and salinity in Gazi Bay (Kenya), a preliminary study. Mangroves and Salt Marshes 3(4):243-249.
Crossref

 
 

Mendes R, Garbeva P, Raaijmakers JM (2013). The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiology Reviews 37(5):634-663.
Crossref

 
 

Mo K, Huang H, Bao S, Hu Y (2020). Bacillus caeni sp. Nov., isolated from mangrove sediment. International Journal of Systematic and Evolutionary Microbiology 70(3):1503-1507.
Crossref

 
 

Mohamed MOS, Neukermans G, Kairo JG, Dahdouh-Guebas F, Koedam N (2009). Mangrove forests in a peri-urban setting: The case of Mombasa (Kenya). Wetlands Ecology and Management 17(3):243-255.
Crossref

 
 

Mohan YSYVJ, Sirisha B, Prathyusha K, Rao P (2014). Isolation, Screening and Characterization of Actinomycetes from Marine Sediments for their Potential to Produce Antifungal Agents. International Journal of Life Sciences, Biotechnology and Pharmaceutical Research 3(4):131-137.

 
 

Muhonja CN, Magoma G, Imbuga M, Makonde HM (2018a). Molecular characterization of Low-Density Polyethene (LDPE) degrading bacteria and fungi from Dandora dumpsite, Nairobi, Kenya. International Journal of Microbiology. Article ID 4167845.
Crossref

 
 

Muhonja CN, Makonde H, Magoma G, Imbuga M (2018b). Biodegradability of polyethylene by bacteria and fungi from Dandora dumpsite Nairobi-Kenya. PLoS ONE 13(7):1-17.
Crossref

 
 

Muwawa EM, Nancy LMB, Zipporah LO, Hamadi IB, Huxley MM (2016). Isolation and characterization of some gut microbial symbionts from fungus-cultivating termites (Macrotermes and Odontotermes spp.). African Journal of Microbiology Research 10(26):994-1004.
Crossref

 
 

Naik G, Shukla S, Kumar MS (2013). Isolation and Characterization of Actinomycetes Isolates for Production of Antimicrobial Compounds. Journal of Microbiology and Biotechnology Research 3(5):33-36.

 
 

Naresh S, Kunasundari B, Gunny AAN, Teoh YP, Shuit SH, Ng QH, Hoo PY (2019). Isolation and partial characterisation of thermophilic cellulolytic bacteria from north Malaysian tropical mangrove soil. Tropical Life Sciences Research 30(1):123-147.

 
 

Ntabo RM, Nyamache AK, Lwande W, Kabii J, Nonoh J (2018). Enzymatic Activity of Endophytic Bacterial Isolates from Selected Mangrove Plants in Kenya. The Open Microbiology Journal 12(1):354-363.
Crossref

 
 

Priya E, Thenmozhi R, Nagasathya A, Thajuddin N, Muralitharan G (2014). Diversity of Actinobacteria in Mangrove Ecosystem of Muthupet, India. International Research Journal of Environment Sciences 3(4):13-17.

 
 

Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies J, Glöckner FO (2007). SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research 35(21):7188-7196.
Crossref

 
 

Pupin B, Nahas E (2014). Microbial populations and activities of mangrove, restinga and Atlantic forest soils from Cardoso Island, Brazil. Journal of Applied Microbiology 116(4):851-864.
Crossref

 
 

Rasigraf O, Helmond NAGM, van Frank J, Lenstra WK, Egger M, Slomp C.P, Jetten MSM (2019). Metagenomic analysis reveals large potential for carbon, nitrogen and sulfur cycling in coastal methanic sediments of the Bothnian Sea. BioRxiv-Pre-Print: 553131.
Crossref

 
 

Saitou N, Nei M (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution 4(4):406-425.

 
 

Salano OA, Huxley MM, Remmy WK, Hamadi IB (2018). Isolation and characterization of fungi from a hot-spring on the shores of Lake Bogoria, Kenya. Journal of Yeast and Fungal Research 9(1):1-13.
Crossref

 
 

Salano OA, Makonde HM, Kasili RW, Wangai LN, Nawiri MP, Boga HI (2017). Diversity and distribution of fungal communities within the hot springs of soda lakes in the Kenyan rift valley. African Journal of Microbiology Research 11(19):764-775.

 
 

Sanders CJ, Eyre BD, Santos IR, Machado W, Luiz-silva W, Smoak JM, Breithaupt JL, Ketterer ME, Sanders L, Marotta H, Silva-filho E, Al SET (2014). Impacted Mangrove Wetland. Geophysical Research Letters 41(1):2475-2480.
Crossref

 
 

Sarker A, Haque M, Islam M, Rahman M, Islam M (2015). Isolation and Characterization of a Marine Bacterium from Sundarbans, Bangladesh. British Microbiology Research Journal 6(6):348-357.
Crossref

 
 

Saseeswari A, Kanimozhi G, Panneerselvam A (2016). Bacterial Diversity of Mangrove Soil in Karankadu from East Coast of Tamil Nadu, India. International Journal of Current Microbiology and Applied Sciences 5(4):750-756.
Crossref

 
 

Sengupta S, Pramanik A, Ghosh A, Bhattacharyya M (2015). Antimicrobial activities of actinomycetes isolated from unexplored regions of Sundarbans mangrove ecosystem. BMC Microbiology 15(1):1-16.
Crossref

 
 

Soares-Júnior FL, Dias ACF, Fasanella CC, Taketani RG, Lima AOdeS, Melo IS, Andreote FD (2013). Endo-and exoglucanase activities in bacteria from mangrove sediment. Brazilian Journal of Microbiology 44(3):969-976.
Crossref

 
 

Somanathan H, Mali S, Borges RM, Shilton LA, Altringham JD, Compton SG, Whittaker RJ, Russo SE, Augspurger CK, Nakashima Y, Inoue E, Inoue-Murayama M, Sukor JR, McConkey KR, Prasad S, Corlett RT, Campos-Arceiz A, Brodie JF, Rogers H, Rawat GS (2004). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Oecologia 15:413-448.

 
 

Srinivasan R, Karaoz U, Volegova M, MacKichan J, Kato-Maeda M, Miller S, Nadarajan R, Brodie EL, Lynch SV (2015). Use of 16S rRNA gene for identification of a broad range of clinically relevant bacterial pathogens. PLoS ONE 10(2):1-22.
Crossref

 
 

Tam HT, City CT, Diep CN, City CT (2017). Isolation and Characterization of Bacteria of Mangrove Rhizosphere in the Mekong Delta, Vietnam. International Journal of Innovations in Engineering and Technology 9(1):68-79.
Crossref

 
 

Tamura K, Nei M, Kumar S (2004). Prospects for inferring very large phylogenies by using the neighbor-joining method. Proceedings of the National Academy of Sciences of the United States of America 101(30):11030-11035.
Crossref

 
 

Wang Q, Garrity GM, Tiedje JM, Cole JR (2007). Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology 73(16):5261-5267.
Crossref

 
 

Wu P, Xiong X, Xu Z, Lu C, Cheng H, Lyu X, Zhang J, He W, Deng W, Lyu Y, Lou Q, Hong Y, Fang H (2016). Bacterial communities in the rhizospheres of three mangrove tree species from Beilun Estuary, China. PLoS ONE 11(10):1-13.
Crossref

 
 

Xu DB, Ye WW, Han Y, Deng ZX, Hong K (2014). Natural products from mangrove actinomycetes. Marine Drugs 12(5):2590-2613.
Crossref

 
 

Zhang Y, Yang Q, Ling J, Van Nostrand JD, Shi Z, Zhou J, Dong J (2017). Diversity and structure of diazotrophic communities in mangrove rhizosphere, revealed by high-throughput sequencing. Frontiers in Microbiology 8(8):1-11.
Crossref

 

 




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