Bacterial Diversity and Characterisation of Secondary Metabolite from Halophilic Bacterial Isolated from Popular Metropolitan Marine Oniru Beach, Lagos, Nigeria

Bacterial Diversity and Characterisation of Secondary Metabolite from Halophilic Bacterial Isolated from Popular Metropolitan Marine Oniru Beach, Lagos, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bacterial Diversity and Characterisation of Secondary Metabolite from Halophilic Bacterial Isolated from Popular Metropolitan Marine Oniru Beach, Lagos, Nigeria Abike Christianah Olaleye, Habeebat Adekilekun Oyewusi, Kolajo Adedamola Akinyede, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7131305/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Oct, 2025 Read the published version in Archives of Microbiology → Version 1 posted 12 You are reading this latest preprint version Abstract This study reports the bacterial diversity and bioactive compounds emanating from halophilic bacterial isolates in popular metropolitan marine Oniru Beach, Lagos, Nigeria. The physicochemical analysis of the water sample depicts a moderately saline, slightly alkaline and oligotrophic environment with low oxygen levels, favouring halophilic bacteria growth. Different metal concentrations, including potassium, calcium, and iron, that influence microbial metabolism and secondary metabolite synthesis or production are contained in appreciable amounts. A high-throughput next-generation sequencing approach and Gas Chromatography-Mass Spectrometry analysis (GC-MS) revealed the diverse bacterial community and bioactive secondary metabolites produced, respectively. The results obtained from 16S rRNA metagenomics showed the bacterial community phyla Proteobacteria (53.72%), Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%) and Firmicutes (1.37%) in their order of dominance or abundance. In addition, the five top genera; Acinetobacter (14.00%), Stenotrophomonas (11.60%), Chryseobacterium (2.56%), Enterobacter (5.36%), and Pseudomonas (2.90%) were identified out of the thirty-nine (37) assigned and one (1) assigned genus, indicating a complex and multifunctional microbial community. The phylogenetic identification analysis of extremely halophilic isolates obtained from salt-tolerance assays and 16S rRNA sequencing depicts Serratia marcescens, Staphylococcus edaphicus, and Kurthia gibsonii , which exhibit diverse phenotypic and biochemical traits. The bioactive compounds or secondary metabolites produced by these isolates showed a diverse range of compounds, including dodecane, glycerol, arabinose, galactose, mannitol, 1,12 tri decadiene and 3-tetracadiene. Collectively, these findings demonstrate that Oniru Beach harbours a rich reservoir of halophilic bacteria with specialized adaptations to salinity and metal stress and with diverse secondary metabolism, offering promising avenues for biotechnological applications such as novel bioactive compounds discovery and development Bacterial diversity Halophilic bacteria Marine environment Oniru beach Secondary metabolites Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1.0 Introduction Marine ecosystems cover over 70% of the Earth’s surface and comprise roughly 98% of the planet’s inhabitable volume, offering vastly more three-dimensional habitat space than terrestrial or freshwater realms (Geta, 2022 ). Marine environment is uniquely one of the microbial ecosystems, with the largest aquatic space and primarily very important source of biodiversity on the planet. It harbours 31 of the 33 recognized animal phyla, with 15 phyla exclusive to marine settings, and supports approximately 250,000 described species; an estimated 750,000 additional species remain to be discovered (Rogers et al., 2023 ). Different life forms, such as bacteria, sponges, algae, fungi, and fish, thrive under the harsh conditions of coastal marine ecosystems, characterized by high salinity, high pressure, limited light, varying temperatures, different pH, a photic surface zone, and in-depth aphotic surfaces, which support growth and survival (Wang et al., 2024 ) Halophilic bacteria are taxonomically diverse, spanning Gram-negative (e.g., Halomonas, Chromohalobacter ) and Gram-positive (e.g., Nesterenkonia, Marinococcus ) lineages and are classified by optimal salt requirements into slight (0.2–0.5 M), moderate (0.5–2.5 M), and extreme (2.5–5.2 M) halophiles (Gunjal and Badodekar, 2021 ; Guevara-Luna et al., 2024 ). The exploration of these vast halophilic bacteria and other microbes from the marine environment has some drawbacks or challenges. Marine microbes account for roughly half of global primary production and mediate key steps in the nitrogen (fixation, nitrification, denitrification) and sulfur (sulfate reduction, sulfide oxidation) cycles (Wang et al., 2022 ). Their metabolic flexibility underpins elemental cycling and influences climate via production of gases such as dimethyl sulfide and methane, and their sheer biomass suggests that removal of marine microbes would dramatically elevate atmospheric CO₂ levels (Jackson and Gabric, 2022 ). Traditional methods allow culturable microbes to be isolated and thrive; however, approximately 70% of the ocean biomass is made up of undiscovered and unculturable marine microbes that need to be explored. The marine microbes that remain unexplored are potential armoury of secondary metabolites (Nigam et al., 2019 ) in the approximately 10 million species of marine organisms on the earth’s biomass (Bar-On et al., 2018 ). The conventional method of metagenomics offers insightful information for microbes that cannot be cultured (microbial diversity, genetic and evolutionary relationships, population patterns, functional activity, cooperative relationships and environmental interaction) and circumvents the herculean task associated with unculturable microbes in their pure form, thus providing the opportunity for scientific investigation and application in different fields. Metagenomic analyses of hypersaline sediments highlight the prevalence of archaeal taxa (e.g., Haloquadratum ) alongside bacterial groups, while genome-enabled studies uncover novel lineages and biosynthetic gene clusters for secondary metabolites (Vera-Gargallo and Ventosa, 2018 ). Recent culture-dependent investigations in South African saltpans characterized halophilic isolates across ten phyla, identifying strains with cellulase, lipase, and hydrocarbon-degrading activities and profiling secondary metabolites such as diketopiperazines and 2,3-butanediol via GC-MS and LC-MS (Selvarajan et al., 2017 ). In foreshore soils of Korea, BOX-PCR and 16S rRNA sequencing revealed dominant genera ( Bacillus, Halomonas, Shewanella ) and underscored the untapped diversity of coastal microflora (Oktavitri et al., 2021 ). Metagenomic analyses of Red Sea brine pool libraries have uncovered orphan biosynthetic gene clusters with selective anticancer effects against MCF-7 cells (Elbehery et al., 2023 ). Ramprasath et al., ( 2021 ) conducted a comprehensive review of halophilic bacterial metabolites, detailing alkaloids, peptides, terpenoids, and phenazines with antibacterial and antifungal properties and highlighted the adaptive links between osmotic stress and metabolite biosynthesis. Srinivasan et al., ( 2021 ) isolated an alkaloid from Pseudomonas sp. associated with Padina tetrastromatica , demonstrating Gram-negative pathogen inhibition at 300 µg. Furthermore, Pelagiobacter variabilis produced pelagiomicins A–C with selective activity against Staphylococcus sp., underscoring the untapped chemical space in marine holobionts (Srinivasan et al., 2021 ). A small portion of the current halophile diversity has been investigated, mainly for the synthesis of enzymes and other uses such as the synthesis of bioactive compounds and suitable compatible solutes that can be employed as stress-reduction agents or biomolecule stabilizers (Berberov et al., 2025 ). Secondary metabolites are low-molecular-mass organic compounds synthesized during stationary or idiophase growth, not essential for primary metabolism but conferring ecological advantages such as defense, competition, and signaling (Marks et al., 2025 ). Marine bacterial secondary metabolites exhibit potent bioactivities, including antimicrobial, anticancer, and anti-inflammatory effects, with examples such as cytarabine and trabectedin already approved as drugs (Sugumaran et al., 2022 ). Numerous bioactive substances, including lipopeptides, polypeptides, polyketides, isocoumarins, and macrolactins, have been found in secondary metabolites of halophilic microorganisms. (Ali and Farahat, 2024 ; Berberov et al., 2025 ). The demand for these compounds in many industries, especially pharmaceutical, places a premium on them because they are eco-friendly and sustainable for solving variety of problems or infections regarding plants, animals and humans. Despite the recognized importance of halophilic bacteria in marine ecosystems and their proven capacity to produce valuable secondary metabolites. However, there is a paucity of studies on their diversity and metabolite profiles in specific coastal environments such as Oniru Beach. This study analysed bacterial diversity and their secondary metabolites from the extract obtained from the popular metropolitan marine Oniru Beach, Lagos, Nigeria. Indeed, based on the literature search, there is little or no study detailing the bacterial diversity and production of secondary metabolites from isolated strains from this marine habitat. This gap will promote the discovery of novel taxa, bioactive compounds and their biotechnological applications. The characterised metabolites may serve as leads for antimicrobial, anticancer and enzymatic applications. Overall, this will pave the way for their bioprospecting of these secondary metabolites in drug discovery and application. 2.0 Materials and Methods 2.1 Sample Collection Surface seawater was aseptically collected from three ecologically distinct high-tidal zones along Oniru Beach (Latitude: 6.446472 Longitude: 3.434052), Lagos, Nigeria, during the peak dry season (October 2024). This marine habitat located in Ozumba Mbadiwe Avenue, Eti- Osa, Lagos State, southwestern Nigeria. They are bound by the Atlantic Ocean and serve as “fun spots” for tourists and fun seekers (Oyewusi et al., 2024a ). At each site, duplicate 1 L Nalgene bottles, pre‐rinsed three times with native seawater, were submerged to ~ 1 m depth, filled, and capped underwater to preclude air entrapment. All bottles were immediately stored on ice in opaque containers to inhibit photodegradation and microbial shifts. It was immediately transferred to the laboratory for analysis. 2.2 Physicochemical Analysis of Oniru Beach Water A composite aliquot from each triplicate sample was subjected to standardized analyses (APHA/AWWA/WEF, 23rd Ed., 2017). In situ temperature (°C) and pH were recorded on site. Conductivity meter measures Electrical conductivity (µS/cm), while salinity (‰) was determined using a calibrated refractometer. Dissolved oxygen (mg/L) was measured both electrometrically and via Winkler titration to ensure accuracy. Chloride concentration was established by argentometric titration; nitrate and phosphate were quantified spectrophotometrically (UV–Vis Spectrophotometer, Model) using the cadmium-reduction and molybdenum‐blue (ascorbic acid) methods, respectively; and sulphate was measured turbidimetrically (Ngah et al., 2022 ). All measurements were performed in triplicate, and mean values with standard deviations were reported. 2.3 Metal Analysis of Oniru Beach Water For trace and major element profiling, 500 mL of the composite sample underwent acid digestion (HNO₃) according to EPA Methods 200.7/3015A. Digested samples were analysed by ICP-OES (Model, Manufacturer) under optimized plasma conditions (Ishak et al., 2015 ). Calibration curves were generated using certified multi‐element standards, with method validation achieved through analysis of reagent blanks, laboratory duplicates, and certified reference materials for marine matrices. Elemental concentrations are expressed in µg/L and were assessed against WHO and Nigerian regulatory thresholds. 2.4 Amplicon Sequencing Analysis 2.4.1 DNA Extraction For water sample 2ml of water was centrifuged at 6000rpm for 5 mins and supernatant discarded to which 520 µl TE (10 mMTrisHCl, 1mM EDTA, pH 8.0) was added. For the sand sample 1ml te was added to the sand sample centrifuged and 520 µl was collected from the supernatant. Fifteen microliters of 20% SDS and 3 µl of Proteinase K (20 mg/ml) were then added. The mixture was incubated for 1 hour at 37 ºC, then 100 µl of 5 M NaCl and 80 µL of a 10% CTAB solution in 0.7 M NaCl were added and votexed. The suspension was incubated for 10 min at 65 ºC and kept on ice for 15 min. An equal volume of chloroform: isoamyl alcohol (24:1) was added, followed by incubation on ice for 5 min and centrifugation at 7200g for 20 min. The aqueous phase was then transferred to a new tube and isopropanol (1: 0.6) was added and DNA precipitated at − 20 ºC for 16 h. DNA was collected by centrifugation at 13000g for 10 min, washed with 500 µl of 70% ethanol, airdried at room temperature for approximately three hours and finally dissolved in 50 µl of TE buffer. 2.4.2 PCR amplification, library preparation, and Illumina MiSeq sequencing Bacterial composition was investigated by targeting the V1 -V9 hypervariable regions of the 16S rRNA gene. Amplicons were generated using the bacteria-specific oligonucleotide primers 27F (5ˈAGAGTTTGATCCTGGCTCAG3ˈ) and 1492R (3ˈGGTTACCTTGTTACGACTT5ˈ) (Weisburg et al., 1991) and amplification was carried out in a 50 µl reaction volume that contained purified genomic DNA (gDNA), 0.3 pmol of each primer, 1 µl DNA Taq polymerase (1 U/µl) (Sigma-Aldrich), and PCR buffer containing dNTPs and pure water (PCR/Amplification kit, Sigma-Aldrich). PCR was performed according to the following conditions: 1 cycle of 94°C for 2 min (initial denaturation), 20 cycles for 98°C for 10 sec (annealing) and 51°C 30 sec, and 68°C for 1 min (extension) of the amplified DNA. Then, amplicons were extracted from a 1.7% Tris-acetate-EDTA agarose gel and purified using a DNA Gel Extraction kit (Axygen Bioscience, Union City, USA) and quantified using QuantiFluor ST (Promega, Madison, USA). The eluted products were then used for library preparation using a 16S rRNA metagenomic sequencing library preparation protocol (Klindworth et al., 2012). Finally, purified library products were pooled in equimolar amounts and sequenced (paired-end, 2 × 300 bp) on an Illumina MiSeq platform by IITA (Nigeria). The quality and quantity of PCR products and libraries were assessed using the TapeStation 4200 Picogreen DNA quantification reagent and spectrophotometry. 2.4.3 Bioinformatic analyses The raw reads were quantified using the sequence analysis program Trimmomatic ( http://www.usadellab.org/cms/?page=trimmomatic ) (Bolger et al., 2014). All raw reads were quality filtered and checked using a minimum quality score of 25 over at least 75% of the sequence read, and low-quality sequences containing > 10 consecutive low-quality base pairs, ambiguous bases, errors in barcode sequences, or > 2 nt mismatches from the primer sequences were discarded. Paired-end reads were merged using USEARCH software (version 11.0.667, http://www.drive5.com/usearch/ ). All sequences of 600 bp (sequenced on the MiSeq platform) were disregarded. Reads were then aligned with the SILVA 16S rRNA database (Release 132) and inspected for chimeric errors using VSEARCH v2.6.2. Chimeric sequences were identified and removed using UCHIME (Edgar et a l., 2011). and the RDP Naïve Bayesian Classifier in the SLIVA database ( http://wwwarbsilva.de ) (Quast et a l., 2012) was applied to perform sequence-level taxonomic classification. 2.5 Bacterial Isolation and Cultivation Aliquots (100 µL) of serial dilutions (10⁻¹ to 10⁻⁶) were spread-plated onto Zobell Marine Agar and nutrient agar supplemented with 3% (w/v) NaCl. Plates were incubated aerobically at 30°C for 48–120 h. Distinct colony morphotypes were repeatedly streaked to purity. 2.5.1 Halotolerance Profiling of Bacterial Isolates Sixteen purified isolates were screened for growth in nutrient agar augmented with NaCl at 3%, 6%, 9%, 15%, 20%, 25%, and 30% (w/v). Each plate was spot-inoculated with a standardized loopful of exponential‐phase culture and incubated at 30°C for seven days. Daily observations were recorded, and growth was scored as positive (+) or negative (–) at day 7 to delineate halotolerance limits. 2.5.2 Phenotypic and Biochemical Characterization of Extremely Halophilic Isolates Five isolates exhibiting growth at ≥ 25% NaCl were selected for in-depth phenotypic and biochemical studies. Colonial attributes (morphology, pigmentation, margin, elevation) were documented on ZMA and NA‐15% plates after 72 h incubation. Cell shape, arrangement, and Gram reaction were determined by light microscopy of cultures in exponential phase. Biochemical profiling followed Bergey’s Manual protocols using HiMedia reagents: catalase and oxidase tests, Simmons citrate utilization, motility assays, methyl red, and carbohydrate fermentation (lactose, sucrose, mannitol) in phenol‐red broth. 2.5.3 Taxonomic Identification using 16S rRNA sequence. 2.5.3.1 DNA extraction, amplification, and sequencing of 16S rRNA Genomic DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen). Briefly, the homogenized single colony was grown in an 8% nutrient broth culture medium and after 24 hours of shaking and the cell-free supernatant was transferred to a 5-mL transport vial and sent for gene sequencing. The DNA was extracted using Qiagen DNeasy kit (Qiagen GmbH, Hilden, Germany). The extracted DNA samples were amplified using universal oligonucleotide primers of 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-TACGGTTACCTTGTTACGACTT-3′) for 16S rRNA gene. The amplified DNA was subjected to electrophoresis on a 0.8% agarose gel and a NanoDrop spectrometer (ND-1000 spectrometer, NanoDrop Technologies, Willington, CT, USA) was used to measure the quality of the genomic DNA. The Sanger sequencing method or chain-termination DNA was used to sequence the amplicons. An automated DNA Analyzer (ABI 3730XL Capillary Sequencers, Applied Biosystems, Bengaluru, India) was used to automate a modified Sanger method commonly used to check the sequence of templates (Saleem et al., 2024 ). Identification to genus or species level was based on ≥ 98.7% sequence similarity to type strains. Representative sequences were deposited in GenBank (Accession Nos. OP909706, OP909717, OP909733, OP909738, OP909753). 2.5.3.2 Phylogenetic Analysis Near-complete 16S rRNA sequences of representative isolates were aligned with closely related type strains retrieved from GenBank using MUSCLE. Phylogenetic trees were constructed in MEGA X via the Maximum Likelihood method (Tamura–Nei model) with 1,000 bootstrap replicates; complementary Neighbor-Joining trees (Kimura 2-parameter) validated clade support. BLASTn analysis provided percentage similarities, predicted taxa, and reference accession numbers (Hall and Beiko, 2018). 2.6 Secondary Metabolite Extraction and Identification Selected halophiles (HOKA1, HOKA3, HOKA8, HOKA15, HOKA16) were cultured in 1 L of optimized production medium (Zobell Marine Broth with 15% NaCl) at 30°C, 150 rpm, for 7–10 days. Cultures were centrifuged (10,000 × g, 20 min, 4°C) to separate biomass. Cell-free supernatants were exhaustively extracted with ethyl acetate (1:1 v/v, three cycles). Organic extracts were pooled, dried over anhydrous Na₂SO₄, filtered, and concentrated under reduced pressure. Crude residues were dissolved in HPLC‐grade methanol for GC‐MS analysis. 2.7 Gas Chromatography–Mass Spectrometry (GC-MS) Analysis Crude extracts were analyzed on an Agilent 7890B GC coupled to a 5977B MSD, equipped with an HP-5MS capillary column (30 m × 0.25 mm ID, 0.25 µm film). Helium served as the carrier gas at 1.0 mL/min. Injector temperature was set to 250°C with a split ratio of 10:1 and a 1 µL injection volume. The oven program ramped from 60°C (2 min hold) to 300°C at 10°C/min, with a final hold of 10 min. MS parameters included EI ionization at 70 eV, ion source temperature of 230°C, quadrupole temperature of 150°C, and scan range m/z 40–600. Metabolites were tentatively identified by matching spectral data against the NIST library, accepting only matches with ≥ 85% similarity and retention index agreement. 3.0 Results and Discussion 3.1 Physiochemical analysis of Oniru water Microbes are the most prevalent and successful organisms on earth, able to withstand a broad variety of physicochemical challenges (Oyewusi et al., 2021a ). Nonetheless, it is now well acknowledged that over 95% of microorganisms live in uncharted settings (Oyewusi et al., 2021b ). Microbial communities that are functionally and taxonomically diverse can be found in extreme settings, such as marine or hypersaline habitats (Vera-Gargallo et al., 2023 ). The physicochemical characteristics of these ecosystems, such as pH, salinity, and ionic compositions, vary greatly (An et al., 2023 ). Table 4.1 showed the physiochemical analysis of Oniru beach water. Oniru Beach surface water temperature averaged 26.35°C, well below the World Health Organization guideline maximum of 30°C for tropical coastal waters, indicating a thermally stable environment with minimal risk of heat-induced stress on aquatic life. Water temperature, defined as the measure of thermal energy in the aquatic environment, influences dissolved oxygen solubility, metabolic rates of organisms, and microbial community composition (Larance et al., 2025 ). The observed mean of 26.35°C suggests optimal conditions for mesophilic marine microbes and supports normal rates of photosynthesis in phytoplankton without exacerbating thermal stratification (Staehr and Birkeland, 2006 ). Beegam et al., ( 2022 ) recorded similar thermal stability in the Red Sea, reporting 25.8–27.5°C across multiple sites (p. 115), underscoring regional climatic parallels. Conversely, in the cooler Atlantic-influenced shores of northern Spain, Martínez, Pire and Martínez-Espinosa, (2022) documented temperatures ranging 18–22°C, reflecting latitudinal variation. In contrast, tropical estuarine systems such as Ghana’s Volta Estuary reached 29.0–31.2°C during the dry season, occasionally exceeding the WHO limit and stressing local biota (Nyarko et al., 2017 ). Thus, Oniru Beach’s sub-30°C regime is consistent with stable, non-stressful tropical coastal waters. The pH of surface water was 8.3, placing it in the mildly alkaline range and within the typical marine bracket (6.5–8.5). pH quantifies the hydrogen-ion activity, with values above 7 indicating alkalinity that affects metal speciation, nutrient availability, and enzyme activity in marine organisms (Dickson, 2010 ). A pH of 8.3 favors calcifying organisms by promoting carbonate ion saturation but may slightly limit the growth of acidophilic microbes. Behera and Naik, ( 2024 ) reported pH values of 8.1–8.4 along India’s Odisha coast, attributing slight alkalinity to carbonate buffer systems in nearshore waters. Aljohny ( 2015 ) found Red Sea surface pH averaging 8.2 ± 0.1, reflecting global marine norms. In contrast, urbanized estuaries such as Chesapeake Bay recorded pH as low as 6.8 during algal blooms due to CO₂ accumulation and organic acid production (Behara et al., 2024 ). The consistency of Oniru Beach’s pH with other oligotrophic coastlines suggests limited anthropogenic acidification and stable carbonate buffering. Electrical conductivity averaged 208.16 µS/cm, and TDS measured 112.53 mg/L, both well below coastal thresholds of 750 µS/cm and 500 mg/L, respectively. Electrical conductivity reflects ionic strength by quantifying the water’s capacity to carry an electrical current, while TDS represents the total concentration of dissolved inorganic solids (Rusydi, 2018 ). Low values indicate limited mineral runoff and oligotrophic conditions, with minimal risk of metal toxicity or osmotic stress to marine taxa. Ogbuagu and Ayoade ( 2011 ) characterized oligotrophic coastal waters in the Gulf of Guinea with conductivity of 180–250 µS/cm and TDS of 100–150 mg/L, matching our Oniru data. In contrast, eutrophic estuaries such as Nigeria’s Lagos Lagoon exhibited conductivity > 600 µS/cm and TDS > 400 mg/L due to industrial effluents (Popoola and Olaniyi, 2020 ). Salinity was 30.25‰, closely aligning with the global open-ocean average of ~ 35‰. Salinity, defined as the total concentration of dissolved salts expressed in parts per thousand, governs water density, stratification, and osmoregulation in marine organisms (United States Environmental Protection Agency, 2025 ). A value of 30.25‰ supports typical marine flora and fauna while indicating some freshwater influence or rainfall dilution relative to open ocean. Al-Johny ( 2015 ) measured Red Sea salinity of 35–37‰, reflecting strong evaporation with minimal riverine input. In the oligotrophic eastern Mediterranean, Galanopoulos et al. ( 2019 ) recorded 38‰, whereas the Amazon estuary near Belém exhibited dramatic fluctuations between 10–20‰ due to seasonal discharge (Dias, Gouveia, & Menezes, 2020 ). Oniru’s slightly lower salinity suggests limited freshwater influx, likely from small streams or urban runoff, but remains within the tolerance range for most marine taxa. DO concentration averaged 3.81 mg/L, falling below the 7 mg/L guideline and indicating the presence of hypoxic microzones. Dissolved oxygen is the amount of gaseous O₂ dissolved in water, essential for aerobic metabolism; values below 5 mg/L are considered hypoxic, potentially stressing obligate aerobes and favouring facultative anaerobes (Diaz and Rosenberg, 2008 ). Sotto, Campini, and Willson ( 2014 ) described DO of 3.5–4.5 mg/L in semi-enclosed bays undergoing periodic hypoxia, attributing fluctuations to stratification and microbial respiration. By contrast, the open Red Sea maintained DO > 6 mg/L year-round (Beegam, Khaleel and Yusuf, 2022 ). In highly eutrophic Chesapeake Bay, DO frequently fell below 2 mg/L in deep channels, creating anoxic zones (Behara, Li, and Sanchez, 2024 ). Oniru’s sub-5 mg/L DO suggests mild hypoxia, possibly seasonal or localized, which could influence fish distribution and benthic community structure. Nitrate was 0.50 mg/L, phosphate 0.05 mg/L, and sulfate 2.73 mg/L, consistent with oligotrophic waters defined by low nutrient concentrations and limited primary productivity. Nutrient levels measure inorganic inputs supporting autotrophic growth. Oligotrophy denotes nutrient scarcity (< 1 mg/L nitrate; < 0.1 mg/L phosphate), constraining phytoplankton biomass (Wetzel, 2001 ). Ogbuagu and Ayoade ( 2011 ) characterized West African coastal oligotrophy with nitrate 0.3–0.6 mg/L and phosphate 0.02–0.08 mg/L, aligning with Oniru. The Red Sea exhibited nitrate < 0.5 mg/L and phosphate 0.5 mg/L due to agricultural runoff, driving eutrophic blooms (Behara et al., 2024 ). The low sulphate at Oniru further indicates minimal industrial discharge. Table 1 Physiochemical analysis of Oniru beach water PARAMETERS Water sample WHO’s permissible limit (mg L − 1 ) Temp 26.35 o C 30 o C pH 8.3 6.5–85 EC (µS/cm) 208.155 750 TDS (mg/l) 112.530 500 Salinity(mg/l) 30.25 DO (mg/l) 3.810 7 Chloride(mg/l) 75.31 250 Nitrate(mg/l) 0.5 5 Phosphate 0.05 - Sulphate(mg/l) 2.73 250 3.2 Mineral Analysis of Oniru beach water Minerals are classified as inorganic nutrients indispensable for maintaining specific physicochemical processes and determining microbial structure in an ecosystem (Abdullah et al., 2022 ). Table 4.2 showed the metal analysis of Oniru Beach surface water. Sodium (Na⁺) was 68.4 mg/L and magnesium (Mg²⁺) was 12.15 mg/L, both within the World Health Organization (WHO) coastal water quality guidelines (200 mg/L for Na⁺; 30 mg/L for Mg²⁺). Sodium and magnesium are the dominant seawater cations, governing salinity, osmotic balance, and microbial osmoadaptation (Madigan et al., 2018 ). Their observed levels suggest unimpacted seawater chemistry with sufficient ionic strength for normal microbial physiology. Along the Red Sea coast, Beegam et al. ( 2022 ) reported Na⁺ of 60–75 mg/L and Mg²⁺ of 10–14 mg/L, mirroring Oniru Beach values. In the tropical Pacific, Millero ( 2013 ) documented Na⁺ at 66.2 ± 3.5 mg/L and Mg²⁺ at 11.8 ± 1.0 mg/L in undisturbed open-ocean waters. Conversely, coastal discharge from desalination plants in South Korea elevated Mg²⁺ to 18–25 mg/L (Kim et al., 2020 ). Potassium (K⁺) was 50.8 mg/L, substantially exceeding the WHO guideline of 12 mg/L for recreational waters. As an essential intracellular cation, K⁺ regulates osmotic pressure and activates microbial enzymes (Epstein, 2003 ). Elevated coastal K⁺ often derives from terrestrial runoff, fertilizer leaching, or sewage discharge and can shift microbial communities toward halotolerant taxa. Skowron et al. ( 2018 ) measured K⁺ spikes of 45–60 mg/L in Baltic Sea sites adjacent to agricultural catchments, while Ahmad and Izhar ( 2021 ) found 48.2 mg/L near Pakistan’s Indus Delta. In contrast, pristine Pacific atolls typically exhibit K⁺ < 10 mg/L (Walter et al., 2017 ), underscoring Oniru’s deviation likely from anthropogenic inputs. Calcium (Ca²⁺) measured 115.1 mg/L, above the 75 mg/L standard for marine recreational waters. Calcium contributes to water hardness, carbonate buffering, and serves as a cofactor for microbial cell-wall stability and signal transduction (Domínguez et al., 2015 ). Excess Ca²⁺ can precipitate carbonate minerals and influence biofilm formation. Nearshore waters of the South China Sea exhibit Ca²⁺ of 100–130 mg/L, attributed to limestone watershed dissolution (Zhou et al., 2024 ), whereas open‐ocean Sargasso Sea samples maintain Ca²⁺ ≈ 85 ± 5 mg/L (Thompson & Sigman, 2018 ). Oniru’s elevated Ca²⁺ thus likely reflects regional carbonate inputs or urban runoff. Iron (Fe) concentration was 2.71 mg/L, over nine times the WHO limit of 0.30 mg/L. Iron is a limiting micronutrient in marine systems, essential for respiration and enzymatic reactions (de Baar et al., 2005 ). Excess Fe can catalyse oxidative stress yet also fuel siderophore-producing bacteria. Seasonal upwelling in the Arabian Sea produces Fe of 2–4 mg/L, correlating with Vibrio blooms (Raval et al., 2022 ). In Brazilian coastal lagoons, Fe > 2 mg/L arises from iron‐ore processing discharge, favoring siderophilic Actinobacteria (Ferreira et al., 2019 ). In the open ocean, Fe rarely exceeds 0.002 mg/L (Boyd & Ellwood, 2010 ), highlighting Oniru’s enrichment, likely from urban or industrial sources. Selenium (Se) at 0.052 mg/L and zinc (Zn) at 0.195 mg/L were within WHO safety ranges (Se < 0.1 mg/L; Zn < 3 mg/L). Both elements are critical micronutrients for antioxidant enzymes, glutathione peroxidases and superoxide dismutases, respectively (Vallee & Auld, 1990; Hatfield & Gladyshev, 2005 ). Lahiri et al. ( 2021 ) documented Se 0.03–0.07 mg/L and Zn 0.18–0.22 mg/L in coastal waters near Mumbai, reflecting baseline urban influence. By contrast, Zn often exceeds 1 mg/L near smelting zones in China (Wang et al., 2018 ). Arsenic (As) measured 0.015 mg/L and lead (Pb) 0.010 mg/L, both at or above WHO toxicity thresholds (0.01 mg/L). Arsenic disrupts cellular respiration by substituting phosphate in ATP, while lead impairs enzyme function and membrane integrity (Nordstrom, 2002 ; Patrick, 2006 ). Martínez-García et al. ( 2020 ) found as 0.01–0.02 mg/L and Pb 0.005–0.012 mg/L in Spanish Mediterranean harbors, linked to historic mining. In remote Pacific atolls, As and Pb are typically < 0.001 mg/L (Tanoue et al., 2019 ), underscoring Oniru’s moderate heavy-metal exposure, likely from urban runoff or atmospheric deposition, posing ecological and public‐health concerns. Table 2 Mineral Analysis of Oniru beach water PARAMETERS Water sample WHO’s permissible limit (mg L − 1 ) Sodium(mg/l) 68.4 200 Calcium(mg/l) 115.1 75 Potassium(mg/l) 50.8 12 Magnesium 12.146 50 Selenium 0.052 0.2 Iron(mg/l) 2.710 0.30 Nickel(mg/l) ND 0.02 Arsenic(mg/l) 0.015 0.01 Lead(mg/l) 0.010 0.01 Vanadium ND - Zinc(mg/l) 0.195 3.0 3.3 Bacterial community The microbial community structure in the collected water samples was analysed using targeted 16S rRNA amplicon sequencing. As shown in Fig. 1 , the amplicon sequencing of Oniru Beach surface water revealed Proteobacteria as the dominant phylum (53.72%), followed by Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%), and Firmicutes (1.37%). In microbial ecology, a phylum represents a high-level taxonomic rank grouping organisms that share fundamental structural and genetic traits (Ruggiero et al., 2015 ). The predominance of Proteobacteria, a highly diverse phylum encompassing many Gram‐negative lineages involved in nutrient cycling reflects typical marine community structure (Gu et al., 2024 ). Bacteroidetes, known for polymer degradation and peptide utilization, comprise key heterotrophs in oligotrophic waters (Hahnke et al., 2016 ). The relatively low abundance of Actinobacteria, Deinococci, and Firmicutes indicates selective pressures favoring Gram‐negative, halotolerant taxa under saline and UV‐intense conditions. Coastal and open‐ocean surveys consistently report Proteobacteria proportions of 40–60% in oligotrophic marine systems (Zhou et al., 2020 ). Ambati and Kumar, ( 2022 ) documented Proteobacteria at 57% in Indian Arabian Sea waters, comparable to our 53.7%. Behera and Naik, ( 2024 ) observed Gammaproteobacteria alone comprising ~ 35% of isolates in the Arabian Gulf, underpinning Proteobacterial ubiquity in saline habitats. Mediterranean surveys record Bacteroidetes at 20–30% and Actinobacteria at 10–20% (Gallè et al., 2020 ), whereas Oniru’s slightly higher Bacteroidetes and lower Actinobacteria mirror the genuine oligotrophic signature of Nigerian coastal waters. The taxonomic abundances of classes from the most abundant to least abundant are presented in Fig. 2 . At the class level (Fig. 2 ), Gammaproteobacteria dominated (47.72%), followed by Bacteroidia (29.43%) and Alphaproteobacteria (5.80%). Gammaproteobacteria include numerous metabolically versatile genera (e.g., Pseudomonas, Acinetobacter) that thrive under nutrient-limited, saline conditions by exploiting diverse carbon sources (Kateete et al., 2017 ). Bacteroidia (formerly the Bacteroidetes class) drive polysaccharide degradation, critical for recycling marine organic matter (McKee et al., 2021 ). Alphaproteobacteria, often oligotrophic specialists like SAR11, typically dominate open-ocean surface waters; their lower abundance here may reflect Oniru’s nearshore nutrient profiles. Gulf of Mexico metagenomes show Gammaproteobacteria at ~ 40% and Alphaproteobacteria at ~ 25% in coastal sites (Cevallos and Degli Esposti, 2022 ). Oniru’s elevated Gammaproteobacteria aligns with Liu and Liu, ( 2020 ) findings of Gammaproteobacterial predominance (~ 35%) in Arabian Gulf samples, suggesting that nearshore anthropogenic inputs selectively boost copiotrophic Gammaproteobacteria. In contrast, truly oligotrophic open‐ocean sites, such as the Sargasso Sea, display Alphaproteobacteria dominance (> 50% SAR11) (Giovannoni, 2017 ), highlighting Oniru’s transitional nearshore ecology. The classification of total reads into lower taxonomic levels revealed extremely diverse bacterial communities in collected water samples, with up to 39 genera being detected (Fig. 3 ). Among identified genera (Fig. 3 ), Acinetobacter (14.00%), Stenotrophomonas (11.60%), Chryseobacterium (2.56%), Enterobacter (5.36%), and Pseudomonas (2.90%) were most abundant. Genera such as Acinetobacte r and Pseudomona s are notable for metabolic plasticity and halotolerance, enabling survival in fluctuating salinities and nutrient conditions (Lupo et al., 2018 ). Stenotrophomonas often colonizes both environmental and clinical niches, reflecting its versatile stress-response mechanisms. Chryseobacterium sp. produces exopolysaccharides that facilitate adhesion and protection against desiccation and UV (Casillo et al., 2018 ). Beegam et al., ( 2022 ) reported Stenotrophomonas comprising ~ 12% of culturable isolates from Thailand’s coastal waters, identical to our 11.6%. Acinetobacter frequently represents 10–20% of marine bacteria in oligotrophic settings, as seen in Mediterranean sediments (Sawale et al., 2014 ) and Arabian Gulf studies (Pavloudi et al., 2016 ). In European coastal lagoons, Pseudomonas accounted for ~ 5% of total reads (Ebohon et al., 2023 ), comparable to our 2.9%. Chryseobacterium prevalence (2–4%) mirrors findings by Jung et al., ( 2023 ) in Mediterranean sediment microbiomes, suggesting its niche specialization under saline stress. A total of 80 distinct bacterial species were identified in the water samples. Most of the species identified are Human-associated opportunists ( Acinetobacter baumannii, Klebsiella quasipneumoniae, Stenotrophomonas maltophilia, Mycobacterium tuberculosis ) co-occurred with environmental specialists ( Moraxella osloensis, Pedobacter chitinilyticus, Deinococcus ficus ) and key functional taxa ( Comamonas terrigena, Rhizobium spp., Microbacterium esteraromaticum ). Species richness quantifies the number of distinct taxa present, a key metric of community diversity (Bhatt, 2005 ). The co-presence of opportunistic pathogens and extremophiles underscores the dual public-health and ecological significance of Oniru’s microbiome: pathogens signal fecal or anthropogenic inputs, while extremotolerant taxa reflect selective pressures from UV radiation, salinity, and nutrient scarcity. Functional groups involved in nitrogen cycling and pigment production indicate active biogeochemical processes. Coastal surveys often report 50–100 bacterial species in oligotrophic waters, paralleling our 80‐species tally (Logue et al., 2012 ). Deinococcus spp. have been identified in UV‐exposed Mediterranean and Pacific intertidal zones at ~ 2% abundance due to robust DNA‐repair systems (Jeong et al., 2024 ). Nitrogen‐cycling genera ( Comamonas, Rhizobium ) contribute ~ 5–10% of coastal bacterial assemblages in the Baltic Sea, supporting similar roles in Oniru (Lo et al., 2022 ). These parallels reinforce the existence of a global “core marine halophilic microbiome,” modulated by local inputs and selective pressures. 3.4 Screening of the isolates for salt tolerance An important parameter for the laboratory study of newly isolated strains from saline environments is the assessment of salt tolerance either on solid or liquid media. The ability of the isolated bacterial strains to grow on agar supplemented with NaCl concentrations ranging from 3 to 30% was further evaluated in Table 3 . Salt-tolerance assays of 16 bacterial isolates from Oniru Beach revealed three distinct tolerance categories (Table 3 ). Isolates 1, 3, 4, 8, 15, and 16 demonstrated robust growth in media containing up to 30% NaCl, classifying them as extremely halophilic. A second group of isolates grew optimally at 15–20% NaCl, consistent with moderately halophilic behavior. Finally, isolates 2, 7, and 9–12 failed to grow above 20% NaCl, indicating halotolerant phenotypes with upper tolerance limits below extreme conditions. Halophiles are organisms requiring or tolerating high salt concentrations for growth; they are conventionally categorized as slight (2–5% NaCl), moderate (5–20% NaCl), or extreme (> 20% NaCl) halophiles (Irshad et al., 2014 ). Halotolerant microbes grow across a broad salinity range but do not require high salt concentrations. In our assays, the ability of six isolates to proliferate at 30% NaCl underscores their adaptation to severe osmotic stress, likely via specialized cellular mechanisms such as compatible solute accumulation and salt-in strategies (Neagu and Stancu, 2025 ). The intermediate group’s tolerance to 15–20% NaCl suggests typical moderate halophile physiology, wherein Osmo protection is balanced to maintain enzyme functionality (Irshad et al., 2014 ). The halotolerant subset, ceasing growth above 20% NaCl, likely relies on more limited osmoregulatory capacities. Yoo et al., ( 2023 ) reported that coastal isolates from the Yellow Sea exhibited optimum growth at 15–25% NaCl, with only a few strains surviving at 30%, paralleling our observation that most Oniru Beach isolates are moderate halophiles, while only select strains achieve extreme halophily (Yoo et al., 2023 ). Ben Hamad Bouhamed et al., ( 2024 ) characterized Halobacterium salinarum from solar salterns, canonical extreme halophiles showing robust growth at 25–30% NaCl, analogous to our six extreme halophiles, suggesting similar osmoregulatory adaptations such as high‐affinity K⁺ uptake and intracellular KCl accumulation. In the Arabian Sea, Javid et al. ( 2020 ) delineated halotolerance among Gammaproteobacteria isolates: moderate halophiles tolerated 10–30% NaCl, whereas extreme halophiles grew at 40–50% NaCl, illustrating an even broader tolerance spectrum. Although our extreme isolates thrived at 30% NaCl, none reached the 40% threshold, suggesting Oniru Beach’s salinity selects for but does not fully mimic solar salt extremophile. Table 3 Isolation of bacteria at different Salt concentration Isolates 3% 6% 9% 15% 20% 25% 30% 1 + + + + + + + 2 - + + + + + - 3 + + + + + + + 4 - + + + - - - 5 + + + + + + - 6 + + + + - - - 7 - + + - - - - 8 + + + + + + + 9 - + + + + + - 10 - + + + + + - 11 - + + + + - - 12 - + + + - - - 13 + + + + + + - 14 + + + + - - - 15 + + + + + + + 16 + + + + + + + 3.4 Phenotypic and Biochemical Characterization of selected isolates The isolated halophilic bacteria exhibited distinct morphological and biochemical traits, highlighting variations in their structural and metabolic characteristics as shown in Table 4 . Five isolates exhibiting growth at ≥ 25% NaCl were selected for in-depth phenotypic and biochemical studies. Colonial attributes (morphology, pigmentation, margin, elevation) were documented on ZMA and NA‐15% plates after 72 h incubation. Cell shape, arrangement, and Gram reaction were determined by light microscopy of cultures in exponential phase. Biochemical profiling followed Bergey’s Manual protocols using HiMedia reagents: catalase and oxidase tests, Simmons citrate utilization, motility assays, methyl red, and carbohydrate fermentation (lactose, sucrose, mannitol) in phenol‐red broth. Gram staining revealed that isolates 1 and 3 were Gram-negative, while 8, 15 and 16 were Gram-positive (Table 4 ). The isolates exhibited distinct cellular morphologies as shown in Table 4 . Additionally, motility was observed in isolates 1,3,15 and 16, whereas 8 were non-motile. Although some differences were observed in their characteristics (e.g., colony colour, Gram staining, morphology). The isolate 8 were catalase-negative, whereas 1,3,15 and 16 were catalase-positive. No differences were observed in oxidase activity and methyl red reaction, as all isolates were oxidase-negative (Table 4 ). Table 4 Phenotypic and Biochemical characteristics of the extremely halophilic bacteria isolates Characteristics 1 3 8 15 16 Colonial morphology Circular Circular irregular Regular regular Colony Convex Convex Flat Convex Convex Colony density Opaque Opaque Opaque Opaque translucent Pigmentation red red Cream Cream White Cell shape Rod rod cocci Rod Rod Gram staining -ve -ve +ve +ve +ve Catalase +ve `+ve -ve +ve +ve citrate +ve +ve -ve +ve +ve Motility +ve +ve -ve +ve +ve Oxidase -ve -ve -ve -ve -ve Methyl red -ve -ve -ve -ve -ve Lactose - ve -ve +ve +ve +ve Sucrose +ve +ve +ve +ve +ve Mannitol +ve +ve +ve +ve +ve -ve = negative, +ve = positive 3.5 Molecular identification of selected isolates The genetic analysis of the 5 isolates was performed using PCR-based molecular methods, specifically 16S rRNA gene amplification. Successful PCR amplification of the bacterial 16S rRNA gene using the 27f/1492r primers in all 5 isolates confirmed their bacterial origin as shown in Fig. 4. High-throughput 16S rRNA gene sequencing of the 5 halophilic isolates yielded clear species assignments (Fig. 4). Isolates 1 and 3 shared 99.78% and 98.93% sequence similarity to Serratia marcescens (Fig. 4a and b). Isolate 8 matched Staphylococcus edaphicus at 99.85% similarity (Fig. 4c), while isolates 15 and 16 corresponded to Kurthia gibsonii at 99.93% and 99.78%, respectively (Fig. 4d and e). All sequences were deposited in GenBank under accessions OP909706–OP909753. According to the commonly accepted threshold for bacterial species delineation—≥98.7% 16S rRNA similarity, these values provide robust confirmation of species identity (Beye et al., 2017 , Oyewusi et al ., 2020). The 16S rRNA gene encodes the RNA component of the small ribosomal subunit and is highly conserved among bacteria, making it the gold standard for phylogenetic placement and species identification (Byrne et al., 2018 ). Ecologically, S. marcescens , primarily known as an opportunistic pathogen has been recovered from saline environments, demonstrating halotolerance (Ho et al., 2025 ). Its presence in Oniru Beach suggests either terrestrial runoff or adaptation to marine microhabitats. S. edaphicus , originally isolated from arid desert soils, similarly tolerates moderate salinity and may carry Osmo adaptive genes enabling survival in coastal matrices (Pantůček et al., 2018 ). K. gibsonii has been described from saline soils and displays growth profiles aligning with our extreme-halophile phenotypes (Chauhan and Samant, 2022 ). These concordances between molecular identity and phenotypic salt tolerance reinforce the validity of our taxonomic assignments and hint at shared osmoregulatory strategies across divergent environments. Ho et al., ( 2025 ) demonstrated that marine isolates of S. marcescens possessed Na⁺/H⁺ antiporter systems enabling growth at 8–10% NaCl, paralleling our isolates’ moderate halotolerance. Pantůček et al., ( 2018 ) characterized S. edaphicus strains from Saharan soils that grew optimally at 5% NaCl and survived up to 15%, matching our isolate’s phenotypic profile. Chauhan and Samant ( 2022 ) reported K. gibsonii tolerating 20–25% NaCl, corroborating the extreme-halophilic capacity we observed. Together, these studies illustrate the ecological plasticity of these taxa and confirm that 16S rRNA–based identification reliably predicts salt-tolerance phenotypes across habitats. A neighbour-joining phylogenetic tree constructed from aligned 16S rRNA sequences resolved three well-supported clades (Fig. 4). Serratia marcescens isolates formed a distinct branch within the Enterobacterales, exhibiting > 95% bootstrap support. Staphylococcus edaphicus grouped with environmental Staphylococci in the Firmicutes, and Kurthia gibsonii isolates clustered as a tight Actinobacteria subclade. Phylogenetic trees graphically represent evolutionary relationships; the neighbour-joining method reconstructs trees based on pairwise distance matrices and is particularly suited for large datasets. Bootstrap support values, percentages derived from resampling provide confidence estimates for individual branches, with values > 70% indicating robust clade stability (Lemoine and Gascuel, 2024 ). The high bootstrap support (> 95%) across our major branches underscores the resolution power of 16S rRNA for genus-level discrimination among halophilic bacteria. Ecologically, phylogenetic clustering often mirrors adaptation to similar niches: halophiles from solar salterns form discrete clades corresponding to taxonomic lineages and environmental pressures (Elshafey et al., 2023 ). In our analysis, the clear separation of Proteobacteria (Enterobacterales, Staphylococci) and Actinobacteria ( Kurthia ) reflects both genetic divergence and ecological specialization in saline habitats. Soto-Varela et al., ( 2024 ) reported > 90% bootstrap support for 16S-based clades of halotolerant Bacilli and Gammaproteobacteria isolated from Spanish salterns, demonstrating the method’s reproducibility. Plominsky et al., ( 2018 ) highlighted that phylogenetic clustering of halophiles often correlates with osmoadaptation mechanisms. These studies confirm that 16S rRNA neighbor-joining analysis reliably reconstructs evolutionary and ecological relationships among halophilic bacteria. 3.6 Secondary Metabolites of Halophilic Isolated Bacteria Bacteria isolated from saline environments are known to produce novel secondary metabolites, which are clinically important natural products and may be the next frontier of drug discovery (Oyewusi et al., 2024b ) Consequently, we evaluated the capacity of newly halotolerant isolated bacterial strains to novel secondary metabolites as shown in Table 6 and Fig. 5. GC–MS analysis of five extreme halophilic isolates yielded 36 distinct compounds, among which glycerol, arabinose, mannitol, propanoic acid, and dodecane were consistently detected across all strains. Compatible solutes are small organic molecules that accumulate intracellularly to counterbalance external osmotic pressure without perturbing macromolecular function (Oyewusi et al., 2021a ). Glycerol, a triol, stabilizes proteins and membranes under hyperosmotic stress (Szél et al., 2019 ). Arabinose and mannitol, pentose and hexitol sugars respectively, function similarly by promoting cytoplasmic osmolality (Desai and Rao, 2010 ). Propanoic acid and dodecane may modulate membrane fluidity and oxidative stress responses. The conservation of these osmolytes suggests a shared core osmoadaptation pathway among marine halophiles, mirroring findings in diverse saline environments (Mukhtar et al., 2020 ). Marine halophiles frequently synthesize ectoine and hydroxyectoine, yet glycerol and mannitol remain widespread (Sharma et al., 2023 ). Ho et al. ( 2025 ) reported arabinose accumulation in Serratia from terrestrial salterns. The presence of propanoic acid and dodecane aligns with Diomandé et al. ( 2015 ), who identified similar fatty acid derivatives in Bacillus halophiles, reinforcing these osmolytes’ ubiquity across marine and terrestrial halophiles. Serratia sp. strain HOKA1 produced 1,12-tridecadiene and ergostane, whereas HOKA3 uniquely synthesized tetral glycol and ascorbic acid. Terpenoids such as ergostane are steroid-like isoprenoids implicated in membrane modulation and oxidative stress defence (Câmara et al., 2024 ). Ascorbic acid (vitamin C) serves as antioxidants, scavenging reactive oxygen species generated under salt stress (Zheng et al., 2024 ). The detection of these molecules highlights metabolic specialization within Serratia isolates, suggesting niche differentiation even among close relatives. Clements-Decker et al., ( 2023 ) characterized Serratia from salt flats, reporting ergostane derivatives as key adaptive metabolites. Alhaj Hamoud et al., ( 2025 ) noted ascorbic acid production in marine Serratia marcescens , linking it to enhanced oxidative resistance. Staphylococcus sp . strain HOKA8 synthesised 13-octadecenoic acid and N-acetylindole. Unsaturated fatty acids like 13-octadecenoic acid adjust membrane fluidity, preserving functionality in hyperosmotic conditions (Harayama and Antonny, 2023 ). N-acetylindole, a tryptophan derivative, may act as a signaling molecule influencing biofilm formation and stress resilience (Scherzer et al., 2009 ). This metabolite suite underscores the dual structural and regulatory adaptations employed by Staphylococcus in saline niches. Omotoyinbo et al., ( 2016 ) detected similar fatty acids in Staphylococcus aureus from seawater, correlating unsaturation levels with halotolerance. Le and Otto, ( 2015 ) described N-acetylindole in coastal Staphylococcus isolates, linking it to quorum-sensing modulation under osmotic stress. Our findings confirm that marine Staphylococcus deploy both membrane‐centric and signaling metabolites to thrive in high‐salt environments. Kurthia sp. strains HOKA15 and HOKA16 share tetraethylene glycol, 3-octadecanone, and inoleic acid, with HOKA16 exhibiting an additional peak for inoleic acid at ~ 28 min (Fig. 5). Polyethylene glycols like tetraethylene glycol stabilize proteins and membranes by forming hydration shells (Samanta et al., 2016 ). Long-chain ketones (3-octadecanone) and unsaturated fatty acids (inoleic acid) modulate membrane phase behavior under osmotic stress (Demirbolat et al., 2021 ). The extra inoleic acid peak in HOKA16 may reflect strain-level variation in membrane composition, impacting fluidity and permeability. Yasmin et al., ( 2022 ) documented 3-octadecanone in Bacillus halophiles, linking it to enhanced surface activity and potential biosurfactant function. Inoleic acid enrichment echoes observations by Wang et al., ( 2023 ) in Halomonas species, indicating that unsaturated fatty acids are central to marine bacterial adaptation. Two compounds; acetamide and fucopyranose were detected in all five extreme halophiles, suggesting conserved pathways. Acetamide can serve as a nitrogen source and inhibit protease activity under stress (Qi et al., 2020 ). Fucopyranose, a deoxyhexose sugar, may function in extracellular polysaccharide synthesis, enhancing biofilm formation and desiccation resistance (Limoli et al., 2015 ). Their universal presence points to shared protective mechanisms across phylogenetically diverse halophiles. Corral et al., ( 2019 ) identified acetamide in Vibrio halophiles as part of osmoregulatory nitrogen assimilation. Kaur and Dey, ( 2023 ) described fucopyranose incorporation into halophilic exopolysaccharides, improving cell–cell adhesion in high-salt matrices. Table 6 Secondary metabolites identified from isolated bacteria Serratia sp. strain HOKA1 Serratia sp. strain HOKA3 Staphylococcus sp. strain HOKA8 Kurthia sp. strain HOKA15 Kurthia sp. strain HOKA16 1 Dodecane Propanoic acid Dodecane Dodecane Propanoic acid 2 Glycerol Acetamide Glycerol Glycerol Acetamide 3 Arabinose Tetral gyycol Arabinose Arabinose Tetral gyycol 4 Galactose d-Glucose Galactose Galactose d-Glucose 5 Mannitol Xylopyranose Mannitol Mannitol Dodecane 6. 1, 12-tridecadiene Lyxofuranose 13-Octodecenoic acid 13-Octodecenoic acid Glycerol 7 3-tetradecene Dicholoacetic acid 13- Docosenoamide 13- Docosenoamide Arabinose 8 Tridecane Trehalose Propanoic acid Propanoic acid Galactose 9 3-tetradecane Mannobiose N-acetylindole N-acetylindole Mannitol 10 3-tetradecene Sucrose Anethole Anethole 1, 12-tridecadiene 11 Hexadecane d-Glucitol Tagatofuranose Tagatofuranose 3-tetradecene 12 Ergostane Ascobic acid Ergostane Ergostane Tridecane 13 13-Octodecenoic acid d-xylose Acetin Acetin 3-tetradecane 14 13- Docosenoamide Maltose Sorbose Sorbose 3-tetradecene 15 Propanoic acid Dodecane Tagatose Tagatose Fructose 16 3-octadecanone Glycerol 3-octadecanone 3-octadecanone Inoleic acid 17 1-octadecanethiol Fucopytanose 1-octadecanethiol 1-octadecanethiol N-acetylindole 18 Methyllinolelaidate Uridine Methyllinolelaidate Methyllinolelaidate Methyllinolelaidate 19 Methylelaidate Methylelaidate Methylelaidate Methylelaidate 20 Methyl-octadecenoate Methyl-octadecenoate Methyl-octadecenoate Methyl-octadecenoate 21 1-docosene 1-docosene 1-docosene 1-docosene 22 Acetamide Glucuronic acid Glucuronic acid Acetamide 23 Fucopyranose Fucopyranose Fucopyranose Fucopyranose 24 Campesterol Allose Allose Campesterol 25 Rhamnitol Rhamnitol Rhamnitol Rhamnitol 26 Butane Talose Talose Butane 27 Acetamide Acetamide Acetamide 28 Tetraethylene glycol Tetraethylene glycol 29 Acetin Acetin 30 Threose Threose 31 Ergostane 32 13-Octodecenoic acid 33 13- Docosenoamide 34 Propanoic acid 35 3-octadecanone 36. 1-octadecanethiol Conclusion Numerous microbes that have evolved to survive in environments with high salt concentrations serve as reservoirs for a variety of compounds that may have commercial value. The problem facing the research of biological compounds made by halophiles at the moment is that their possible uses could not be fully understood or even recognized. 16S rRNA amplicon sequencing analysis revealed a high abundance of Proteobacteria (53.72%), Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%) and Firmicutes(1.37%), with Gammaproteobacteria (47.72%) being the most abundant classes in the water sample. Moreover, using culture-dependent study five halophilic bacteria isolates 1,3,8,15 and 16 were confirmed as Serratia sp. strain HOKA1, Serratia sp. strain HOKA3, Staphylococcus sp. strain HOKA8, Kurthia sp. strain HOKA15 and Kurthia sp. strain HOKA16, respectively, using biochemical and molecular approaches. The current study contributes to the knowledge of microbial ecology which have also creates new avenues for the study of the discovery of novel organisms in extreme environments. These isolated halophilic bacteria may provide biotechnologically essential chemicals for a variety of uses, including the synthesis of industrially important bioactive compounds and other commercial products. Declarations Conflict of Interest There are no conflicts to declare. Funding This work was partly funded by the TETFund 2020_2024 Institutional Based Research Professional through the Centre for Research and Innovative Development (CRID), Federal Polytechnic Ado-Ekiti, Ekiti State, Nigeria. Author Contribution OHA and OOO developed the original idea. OHA developed the protocol. OHA, OAC and OOO performed the experiments and were involved in the collection of data. AAK and BFO wrote the preliminary draft of the article. OHA and OOO analyzed the data. All authors reviewed the manuscript. All authors read and approved the manuscript for publication. 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Journal of Marine Systems, 187 , 1–10. https://doi.org/10.1016/j.jmarsys.2018.12.002 Thompson, A. F., & Sigman, D. M. (2018). Calcium isotopes as tracers of ocean processes. Nature Geoscience, 11 (4), 331–336. https://doi.org/10.1038/s41561-018-0086-4 Tu, Q., & Lin, L. (2016). Gene content dissimilarity for subclassification of highly similar microbial strains. BMC Genomics, 17. United States Environmental Protection Agency. (2025). Indicators: Salinity. (https://www.epa.gov/national-aquatic-resource-surveys/indicators-salinity). Accessed January 1, 2025. Vera-Gargallo, B., & Ventosa, A. (2018). Metagenomic Insights into the Phylogenetic and Metabolic Diversity of the Prokaryotic Community Dwelling in Hypersaline Soils from the Odiel Saltmarshes (SW Spain). Genes , 9 (3), 152. https://doi.org/10.3390/genes9030152 Vera-Gargallo, B., Hernández, M., Dumont, M. G., & Ventosa, A. (2023). Thrive or survive: prokaryotic life in hypersaline soils. Environmental microbiome , 18 (1), 17. Walter, J., Smith, R., & Jones, P. (2017). Pristine Pacific atoll seawater composition: A reference dataset. Journal of Geophysical Research: Oceans, 122 (7), 5000–5012. https://doi.org/10.1002/2016JC012345 Wang, F., Li, X., & Chen, Y. (2018). Zinc contamination from smelting activities in coastal China. Science of the Total Environment, 622–623 , 129–138. https://doi.org/10.1016/j.scitotenv.2017.11.235 Wang, J., Liu, Y., Ma, Y., Wang, X., Zhang, B., Zhang, G., Bahadur, A., Chen, T., Liu, G., Zhang, W., & Zhao, Y. (2023). Research progress regarding the role of halophilic and halotolerant microorganisms in the eco-environmental sustainability and conservation. Journal of Cleaner Production, 418, 138054. Wang, S., Yang, Y., & Jing, J. (2022). A Synthesis of Viral Contribution to Marine Nitrogen Cycling. Frontiers in microbiology , 13 , 834581. https://doi.org/10.3389/fmicb.2022.834581 Wang, Z., Li, Y., Gao, X., Xing, J., Wang, R., Zhu, D., & Shen, G. (2023). Comparative genomic analysis of Halomonas campaniensis wild-type and ultraviolet radiation-mutated strains reveal genomic differences associated with increased ectoine production. International microbiology : the official journal of the Spanish Society for Microbiology , 26 (4), 1009–1020. https://doi.org/10.1007/s10123-023-00356-y Wang, S., Li, X., Yang, W., & Huang, R. (2024). Exploring the secrets of marine microorganisms: Unveiling secondary metabolites through metagenomics. Microbial Biotechnology, 17 (8), e14533 Wetzel, R. G. (2001). Limnology: Lake and River Ecosystems (3rd ed.). Academic Press. https://doi.org/10.1016/B978-012744760-9/50006-3 Yasmin, A., Aslam, F., & Fariq, A. (2022). Genetic evidences of biosurfactant production in two Bacillus subtilis strains MB415 and MB418 isolated from oil contaminated soil. Frontiers in Bioengineering and Biotechnology, 10, 855762. doi: 10.3389/fbioe.2022.855762 Yoo, Y., Lee, H., Lee, J., Khim, J. S., & Kim, J.-J. (2023). Insights into saline adaptation strategies through a novel halophilic bacterium isolated from solar saltern of Yellow sea. Frontiers in Marine Science, 10, 1229444. Zheng, H., Xu, Y., Liehn, E. A., & Rusu, M. (2024). Vitamin C as Scavenger of Reactive Oxygen Species during Healing after Myocardial Infarction. International journal of molecular sciences , 25 (6), 3114. https://doi.org/10.3390/ijms25063114 Zhou, H., Hu, Y. Y., Tang, Z. X., Jiang, Z. B., Huang, J., Zhang, T., Shen, H. Y., Ye, X. P., Huang, X. Y., Wang, X., Zhou, T., Bai, X. L., Zhu, Q., & Shi, L. E. (2024). Calcium Transport and Enrichment in Microorganisms: A Review. Foods (Basel, Switzerland) , 13 (22), 3612. https://doi.org/10.3390/foods13223612 Zhou, Y., Lin, X., & Wong, T. (2024). Dissolved ion concentrations in sediment‐rich nearshore waters of the South China Sea. Journal of Marine Systems, 245 , 103789. https://doi.org/10.1016/j.jmarsys.2023.103789 Zhou, Z., Tran, P. Q., Kieft, K., & Anantharaman, K. (2020). Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. The ISME journal , 14 (8), 2060–2077. https://doi.org/10.1038/s41396-020-0669-4 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7131305","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489461496,"identity":"8fd8386b-3b6b-433f-9009-8be2311b6ec4","order_by":0,"name":"Abike Christianah Olaleye","email":"","orcid":"","institution":"The Federal Polytechnic","correspondingAuthor":false,"prefix":"","firstName":"Abike","middleName":"Christianah","lastName":"Olaleye","suffix":""},{"id":489461497,"identity":"6002ee67-5f7c-4a0b-9de0-5ea54e0eb190","order_by":1,"name":"Habeebat Adekilekun Oyewusi","email":"data:image/png;base64,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","orcid":"","institution":"The Federal Polytechnic","correspondingAuthor":true,"prefix":"","firstName":"Habeebat","middleName":"Adekilekun","lastName":"Oyewusi","suffix":""},{"id":489461498,"identity":"9bc866bf-7120-4b80-9ff5-289d4a1f73de","order_by":2,"name":"Kolajo Adedamola Akinyede","email":"","orcid":"","institution":"The Federal 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13:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7131305/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7131305/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00203-025-04503-z","type":"published","date":"2025-10-13T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87501716,"identity":"2d0d429a-f07c-4ead-be52-3dc9e507ef17","added_by":"auto","created_at":"2025-07-24 13:58:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27128,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial phyla represented among the species identified in Oniru beach water\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/bbdb5c4e25e42e26ddd23758.png"},{"id":87502106,"identity":"c7489c47-8d3a-4f27-97ba-357d0673cddc","added_by":"auto","created_at":"2025-07-24 14:06:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27931,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial class represented among the species identified in Oniru beach water\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/0e234dc1003b6217d72fe775.png"},{"id":87501718,"identity":"1a93b1ca-1988-41d9-bfbb-7e02ba719dce","added_by":"auto","created_at":"2025-07-24 13:58:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":34972,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial genus represented among the species identified in Oniru beach water\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/1a9f1db29a0602607191b16c.png"},{"id":87501721,"identity":"b53792b2-1d1e-49af-b9bc-fdb970b5d5ae","added_by":"auto","created_at":"2025-07-24 13:58:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":577741,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic analysis of halophilic bacteria isolates of\u003cstrong\u003e \u003c/strong\u003e(a) \u003cem\u003eSerratia sp \u003c/em\u003estrain HOKA1 (b) \u003cem\u003eSerratia sp \u003c/em\u003estrain HOKA3 (c) \u003cem\u003eStaphylococcus sp. strain \u003c/em\u003eHOKA8 (d) \u003cem\u003eKurthia sp \u003c/em\u003estrain HOKA15 (e) \u003cem\u003eKurthia sp \u003c/em\u003estrain HOKA16\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/bb88ca51451965cfa91836b8.png"},{"id":87501719,"identity":"51f63ce9-9439-4dfb-b84f-bc86b7da66b2","added_by":"auto","created_at":"2025-07-24 13:58:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":247569,"visible":true,"origin":"","legend":"\u003cp\u003eChromatogram for GC MS analysis of (a) \u003cem\u003eSerratia sp \u003c/em\u003estrain HOKA1 (b) \u003cem\u003eSerratia sp \u003c/em\u003estrain HOKA3 (c) \u003cem\u003eStaphylococcus sp. strain \u003c/em\u003eHOKA8 (d) \u003cem\u003eKurthia sp \u003c/em\u003estrain HOKA15 (e) \u003cem\u003eKurthia sp \u003c/em\u003estrain HOKA16\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/39b1662a6287336a92a034ef.png"},{"id":93956758,"identity":"660240f6-cad5-42f3-90a9-5860c0c4ba17","added_by":"auto","created_at":"2025-10-20 16:12:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2540700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7131305/v1/ec0ae2a1-9266-4a54-89b8-c093433d12bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBacterial Diversity and Characterisation of Secondary Metabolite from Halophilic Bacterial Isolated from Popular Metropolitan Marine Oniru Beach, Lagos, Nigeria\u003c/p\u003e","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eMarine ecosystems cover over 70% of the Earth\u0026rsquo;s surface and comprise roughly 98% of the planet\u0026rsquo;s inhabitable volume, offering vastly more three-dimensional habitat space than terrestrial or freshwater realms (Geta, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Marine environment is uniquely one of the microbial ecosystems, with the largest aquatic space and primarily very important source of biodiversity on the planet. It harbours 31 of the 33 recognized animal phyla, with 15 phyla exclusive to marine settings, and supports approximately 250,000 described species; an estimated 750,000 additional species remain to be discovered (Rogers et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Different life forms, such as bacteria, sponges, algae, fungi, and fish, thrive under the harsh conditions of coastal marine ecosystems, characterized by high salinity, high pressure, limited light, varying temperatures, different pH, a photic surface zone, and in-depth aphotic surfaces, which support growth and survival (Wang et al., \u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eHalophilic bacteria are taxonomically diverse, spanning Gram-negative (e.g., \u003cem\u003eHalomonas, Chromohalobacter\u003c/em\u003e) and Gram-positive (e.g., \u003cem\u003eNesterenkonia, Marinococcus\u003c/em\u003e) lineages and are classified by optimal salt requirements into slight (0.2\u0026ndash;0.5 M), moderate (0.5\u0026ndash;2.5 M), and extreme (2.5\u0026ndash;5.2 M) halophiles (Gunjal and Badodekar, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Guevara-Luna et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The exploration of these vast halophilic bacteria and other microbes from the marine environment has some drawbacks or challenges.\u003c/p\u003e\u003cp\u003eMarine microbes account for roughly half of global primary production and mediate key steps in the nitrogen (fixation, nitrification, denitrification) and sulfur (sulfate reduction, sulfide oxidation) cycles (Wang et al., \u003cspan citationid=\"CR144\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Their metabolic flexibility underpins elemental cycling and influences climate via production of gases such as dimethyl sulfide and methane, and their sheer biomass suggests that removal of marine microbes would dramatically elevate atmospheric CO₂ levels (Jackson and Gabric, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTraditional methods allow culturable microbes to be isolated and thrive; however, approximately 70% of the ocean biomass is made up of undiscovered and unculturable marine microbes that need to be explored. The marine microbes that remain unexplored are potential armoury of secondary metabolites (Nigam et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) in the approximately 10\u0026nbsp;million species of marine organisms on the earth\u0026rsquo;s biomass (Bar-On et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The conventional method of metagenomics offers insightful information for microbes that cannot be cultured (microbial diversity, genetic and evolutionary relationships, population patterns, functional activity, cooperative relationships and environmental interaction) and circumvents the herculean task associated with unculturable microbes in their pure form, thus providing the opportunity for scientific investigation and application in different fields. Metagenomic analyses of hypersaline sediments highlight the prevalence of archaeal taxa (e.g., \u003cem\u003eHaloquadratum\u003c/em\u003e) alongside bacterial groups, while genome-enabled studies uncover novel lineages and biosynthetic gene clusters for secondary metabolites (Vera-Gargallo and Ventosa, \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent culture-dependent investigations in South African saltpans characterized halophilic isolates across ten phyla, identifying strains with cellulase, lipase, and hydrocarbon-degrading activities and profiling secondary metabolites such as diketopiperazines and 2,3-butanediol via GC-MS and LC-MS (Selvarajan et al., \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In foreshore soils of Korea, BOX-PCR and 16S rRNA sequencing revealed dominant genera (\u003cem\u003eBacillus, Halomonas, Shewanella\u003c/em\u003e) and underscored the untapped diversity of coastal microflora (Oktavitri et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Metagenomic analyses of Red Sea brine pool libraries have uncovered orphan biosynthetic gene clusters with selective anticancer effects against MCF-7 cells (Elbehery et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ramprasath et al., (\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) conducted a comprehensive review of halophilic bacterial metabolites, detailing alkaloids, peptides, terpenoids, and phenazines with antibacterial and antifungal properties and highlighted the adaptive links between osmotic stress and metabolite biosynthesis. Srinivasan et al., (\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) isolated an alkaloid from \u003cem\u003ePseudomonas\u003c/em\u003e sp. associated with \u003cem\u003ePadina tetrastromatica\u003c/em\u003e, demonstrating Gram-negative pathogen inhibition at 300 \u0026micro;g. Furthermore, \u003cem\u003ePelagiobacter variabilis\u003c/em\u003e produced pelagiomicins A\u0026ndash;C with selective activity against Staphylococcus sp., underscoring the untapped chemical space in marine holobionts (Srinivasan et al., \u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A small portion of the current halophile diversity has been investigated, mainly for the synthesis of enzymes and other uses such as the synthesis of bioactive compounds and suitable compatible solutes that can be employed as stress-reduction agents or biomolecule stabilizers (Berberov et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSecondary metabolites are low-molecular-mass organic compounds synthesized during stationary or idiophase growth, not essential for primary metabolism but conferring ecological advantages such as defense, competition, and signaling (Marks et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Marine bacterial secondary metabolites exhibit potent bioactivities, including antimicrobial, anticancer, and anti-inflammatory effects, with examples such as cytarabine and trabectedin already approved as drugs (Sugumaran et al., \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNumerous bioactive substances, including lipopeptides, polypeptides, polyketides, isocoumarins, and macrolactins, have been found in secondary metabolites of halophilic microorganisms. (Ali and Farahat, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Berberov et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The demand for these compounds in many industries, especially pharmaceutical, places a premium on them because they are eco-friendly and sustainable for solving variety of problems or infections regarding plants, animals and humans.\u003c/p\u003e\u003cp\u003eDespite the recognized importance of halophilic bacteria in marine ecosystems and their proven capacity to produce valuable secondary metabolites. However, there is a paucity of studies on their diversity and metabolite profiles in specific coastal environments such as Oniru Beach. This study analysed bacterial diversity and their secondary metabolites from the extract obtained from the popular metropolitan marine Oniru Beach, Lagos, Nigeria. Indeed, based on the literature search, there is little or no study detailing the bacterial diversity and production of secondary metabolites from isolated strains from this marine habitat. This gap will promote the discovery of novel taxa, bioactive compounds and their biotechnological applications. The characterised metabolites may serve as leads for antimicrobial, anticancer and enzymatic applications. Overall, this will pave the way for their bioprospecting of these secondary metabolites in drug discovery and application.\u003c/p\u003e"},{"header":"2.0 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Sample Collection\u003c/h2\u003e\u003cp\u003eSurface seawater was aseptically collected from three ecologically distinct high-tidal zones along Oniru Beach (Latitude: 6.446472 Longitude: 3.434052), Lagos, Nigeria, during the peak dry season (October 2024). This marine habitat located in Ozumba Mbadiwe Avenue, Eti- Osa, Lagos State, southwestern Nigeria. They are bound by the Atlantic Ocean and serve as \u0026ldquo;fun spots\u0026rdquo; for tourists and fun seekers (Oyewusi et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). At each site, duplicate 1 L Nalgene bottles, pre‐rinsed three times with native seawater, were submerged to ~\u0026thinsp;1 m depth, filled, and capped underwater to preclude air entrapment. All bottles were immediately stored on ice in opaque containers to inhibit photodegradation and microbial shifts. It was immediately transferred to the laboratory for analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Physicochemical Analysis of Oniru Beach Water\u003c/h2\u003e\u003cp\u003eA composite aliquot from each triplicate sample was subjected to standardized analyses (APHA/AWWA/WEF, 23rd Ed., 2017). In situ temperature (\u0026deg;C) and pH were recorded on site. Conductivity meter measures Electrical conductivity (\u0026micro;S/cm), while salinity (\u0026permil;) was determined using a calibrated refractometer. Dissolved oxygen (mg/L) was measured both electrometrically and via Winkler titration to ensure accuracy. Chloride concentration was established by argentometric titration; nitrate and phosphate were quantified spectrophotometrically (UV\u0026ndash;Vis Spectrophotometer, Model) using the cadmium-reduction and molybdenum‐blue (ascorbic acid) methods, respectively; and sulphate was measured turbidimetrically (Ngah et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All measurements were performed in triplicate, and mean values with standard deviations were reported.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Metal Analysis of Oniru Beach Water\u003c/h2\u003e\u003cp\u003eFor trace and major element profiling, 500 mL of the composite sample underwent acid digestion (HNO₃) according to EPA Methods 200.7/3015A. Digested samples were analysed by ICP-OES (Model, Manufacturer) under optimized plasma conditions (Ishak et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Calibration curves were generated using certified multi‐element standards, with method validation achieved through analysis of reagent blanks, laboratory duplicates, and certified reference materials for marine matrices. Elemental concentrations are expressed in \u0026micro;g/L and were assessed against WHO and Nigerian regulatory thresholds.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Amplicon Sequencing Analysis\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1 DNA Extraction\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFor water sample 2ml of water was centrifuged at 6000rpm for 5 mins and supernatant discarded to which 520 \u0026micro;l TE (10 mMTrisHCl, 1mM EDTA, pH 8.0) was added. For the sand sample 1ml te was added to the sand sample centrifuged and 520 \u0026micro;l was collected from the supernatant. Fifteen microliters of 20% SDS and 3 \u0026micro;l of Proteinase K (20 mg/ml) were then added. The mixture was incubated for 1 hour at 37 \u0026ordm;C, then 100 \u0026micro;l of 5 M NaCl and 80 \u0026micro;L of a 10% CTAB solution in 0.7 M NaCl were added and votexed. The suspension was incubated for 10 min at 65 \u0026ordm;C and kept on ice for 15 min. An equal volume of chloroform: isoamyl alcohol (24:1) was added, followed by incubation on ice for 5 min and centrifugation at 7200g for 20 min. The aqueous phase was then transferred to a new tube and isopropanol (1: 0.6) was added and DNA precipitated at \u0026minus;\u0026thinsp;20 \u0026ordm;C for 16 h. DNA was collected by centrifugation at 13000g for 10 min, washed with 500 \u0026micro;l of 70% ethanol, airdried at room temperature for approximately three hours and finally dissolved in 50 \u0026micro;l of TE buffer.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2 PCR amplification, library preparation, and Illumina MiSeq sequencing\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBacterial composition was investigated by targeting the V1 -V9 hypervariable regions of the 16S rRNA gene. Amplicons were generated using the bacteria-specific oligonucleotide primers 27F (5ˈAGAGTTTGATCCTGGCTCAG3ˈ) and 1492R (3ˈGGTTACCTTGTTACGACTT5ˈ) (Weisburg et al., 1991) and amplification was carried out in a 50 \u0026micro;l reaction volume that contained purified genomic DNA (gDNA), 0.3 pmol of each primer, 1 \u0026micro;l DNA Taq polymerase (1 U/\u0026micro;l) (Sigma-Aldrich), and PCR buffer containing dNTPs and pure water (PCR/Amplification kit, Sigma-Aldrich). PCR was performed according to the following conditions: 1 cycle of 94\u0026deg;C for 2 min (initial denaturation), 20 cycles for 98\u0026deg;C for 10 sec (annealing) and 51\u0026deg;C 30 sec, and 68\u0026deg;C for 1 min (extension) of the amplified DNA. Then, amplicons were extracted from a 1.7% Tris-acetate-EDTA agarose gel and purified using a DNA Gel Extraction kit (Axygen Bioscience, Union City, USA) and quantified using QuantiFluor ST (Promega, Madison, USA). The eluted products were then used for library preparation using a 16S rRNA metagenomic sequencing library preparation protocol (Klindworth et al., 2012). Finally, purified library products were pooled in equimolar amounts and sequenced (paired-end, 2 \u0026times; 300 bp) on an Illumina MiSeq platform by IITA (Nigeria). The quality and quantity of PCR products and libraries were assessed using the TapeStation 4200 Picogreen DNA quantification reagent and spectrophotometry.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3 Bioinformatic analyses\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe raw reads were quantified using the sequence analysis program Trimmomatic (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.usadellab.org/cms/?page=trimmomatic\u003c/span\u003e\u003cspan address=\"http://www.usadellab.org/cms/?page=trimmomatic\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Bolger et al., 2014). All raw reads were quality filtered and checked using a minimum quality score of 25 over at least 75% of the sequence read, and low-quality sequences containing\u0026thinsp;\u0026gt;\u0026thinsp;10 consecutive low-quality base pairs, ambiguous bases, errors in barcode sequences, or \u0026gt;\u0026thinsp;2 nt mismatches from the primer sequences were discarded. Paired-end reads were merged using USEARCH software (version 11.0.667, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.drive5.com/usearch/\u003c/span\u003e\u003cspan address=\"http://www.drive5.com/usearch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All sequences of \u0026lt;\u0026thinsp;150 bp or \u0026gt;\u0026thinsp;600 bp (sequenced on the MiSeq platform) were disregarded. Reads were then aligned with the SILVA 16S rRNA database (Release 132) and inspected for chimeric errors using VSEARCH v2.6.2. Chimeric sequences were identified and removed using UCHIME (Edgar \u003cem\u003eet a\u003c/em\u003el., 2011). and the RDP Na\u0026iuml;ve Bayesian Classifier in the SLIVA database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://wwwarbsilva.de\u003c/span\u003e\u003cspan address=\"http://wwwarbsilva.de\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Quast \u003cem\u003eet a\u003c/em\u003el., 2012) was applied to perform sequence-level taxonomic classification.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Bacterial Isolation and Cultivation\u003c/h2\u003e\u003cp\u003eAliquots (100 \u0026micro;L) of serial dilutions (10⁻\u0026sup1; to 10⁻⁶) were spread-plated onto Zobell Marine Agar and nutrient agar supplemented with 3% (w/v) NaCl. Plates were incubated aerobically at 30\u0026deg;C for 48\u0026ndash;120 h. Distinct colony morphotypes were repeatedly streaked to purity.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 Halotolerance Profiling of Bacterial Isolates\u003c/h2\u003e\u003cp\u003eSixteen purified isolates were screened for growth in nutrient agar augmented with NaCl at 3%, 6%, 9%, 15%, 20%, 25%, and 30% (w/v). Each plate was spot-inoculated with a standardized loopful of exponential‐phase culture and incubated at 30\u0026deg;C for seven days. Daily observations were recorded, and growth was scored as positive (+) or negative (\u0026ndash;) at day 7 to delineate halotolerance limits.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2 Phenotypic and Biochemical Characterization of Extremely Halophilic Isolates\u003c/h2\u003e\u003cp\u003eFive isolates exhibiting growth at \u0026ge;\u0026thinsp;25% NaCl were selected for in-depth phenotypic and biochemical studies. Colonial attributes (morphology, pigmentation, margin, elevation) were documented on ZMA and NA‐15% plates after 72 h incubation. Cell shape, arrangement, and Gram reaction were determined by light microscopy of cultures in exponential phase. Biochemical profiling followed Bergey\u0026rsquo;s Manual protocols using HiMedia reagents: catalase and oxidase tests, Simmons citrate utilization, motility assays, methyl red, and carbohydrate fermentation (lactose, sucrose, mannitol) in phenol‐red broth.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.5.3 Taxonomic Identification using 16S rRNA sequence.\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section4\"\u003e\u003ch2\u003e2.5.3.1 DNA extraction, amplification, and sequencing of 16S rRNA\u003c/h2\u003e\u003cp\u003eGenomic DNA was extracted using the DNeasy Blood \u0026amp; Tissue Kit (Qiagen). Briefly, the homogenized single colony was grown in an 8% nutrient broth culture medium and after 24 hours of shaking and the cell-free supernatant was transferred to a 5-mL transport vial and sent for gene sequencing. The DNA was extracted using Qiagen DNeasy kit (Qiagen GmbH, Hilden, Germany). The extracted DNA samples were amplified using universal oligonucleotide primers of 27F (5\u0026prime;-AGAGTTTGATCCTGGCTCAG-3\u0026prime;) and 1492R (5\u0026prime;-TACGGTTACCTTGTTACGACTT-3\u0026prime;) for 16S rRNA gene. The amplified DNA was subjected to electrophoresis on a 0.8% agarose gel and a NanoDrop spectrometer (ND-1000 spectrometer, NanoDrop Technologies, Willington, CT, USA) was used to measure the quality of the genomic DNA. The Sanger sequencing method or chain-termination DNA was used to sequence the amplicons. An automated DNA Analyzer (ABI 3730XL Capillary Sequencers, Applied Biosystems, Bengaluru, India) was used to automate a modified Sanger method commonly used to check the sequence of templates (Saleem et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Identification to genus or species level was based on \u0026ge;\u0026thinsp;98.7% sequence similarity to type strains. Representative sequences were deposited in GenBank (Accession Nos. OP909706, OP909717, OP909733, OP909738, OP909753).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section4\"\u003e\u003ch2\u003e2.5.3.2 Phylogenetic Analysis\u003c/h2\u003e\u003cp\u003eNear-complete 16S rRNA sequences of representative isolates were aligned with closely related type strains retrieved from GenBank using MUSCLE. Phylogenetic trees were constructed in MEGA X via the Maximum Likelihood method (Tamura\u0026ndash;Nei model) with 1,000 bootstrap replicates; complementary Neighbor-Joining trees (Kimura 2-parameter) validated clade support. BLASTn analysis provided percentage similarities, predicted taxa, and reference accession numbers (Hall and Beiko, 2018).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Secondary Metabolite Extraction and Identification\u003c/h2\u003e\u003cp\u003eSelected halophiles (HOKA1, HOKA3, HOKA8, HOKA15, HOKA16) were cultured in 1 L of optimized production medium (Zobell Marine Broth with 15% NaCl) at 30\u0026deg;C, 150 rpm, for 7\u0026ndash;10 days. Cultures were centrifuged (10,000 \u0026times; g, 20 min, 4\u0026deg;C) to separate biomass. Cell-free supernatants were exhaustively extracted with ethyl acetate (1:1 v/v, three cycles). Organic extracts were pooled, dried over anhydrous Na₂SO₄, filtered, and concentrated under reduced pressure. Crude residues were dissolved in HPLC‐grade methanol for GC‐MS analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Gas Chromatography\u0026ndash;Mass Spectrometry (GC-MS) Analysis\u003c/h2\u003e\u003cp\u003eCrude extracts were analyzed on an Agilent 7890B GC coupled to a 5977B MSD, equipped with an HP-5MS capillary column (30 m \u0026times; 0.25 mm ID, 0.25 \u0026micro;m film). Helium served as the carrier gas at 1.0 mL/min. Injector temperature was set to 250\u0026deg;C with a split ratio of 10:1 and a 1 \u0026micro;L injection volume. The oven program ramped from 60\u0026deg;C (2 min hold) to 300\u0026deg;C at 10\u0026deg;C/min, with a final hold of 10 min. MS parameters included EI ionization at 70 eV, ion source temperature of 230\u0026deg;C, quadrupole temperature of 150\u0026deg;C, and scan range m/z 40\u0026ndash;600. Metabolites were tentatively identified by matching spectral data against the NIST library, accepting only matches with \u0026ge;\u0026thinsp;85% similarity and retention index agreement.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 Results and Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Physiochemical analysis of Oniru water\u003c/h2\u003e\u003cp\u003eMicrobes are the most prevalent and successful organisms on earth, able to withstand a broad variety of physicochemical challenges (Oyewusi et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Nonetheless, it is now well acknowledged that over 95% of microorganisms live in uncharted settings (Oyewusi et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). Microbial communities that are functionally and taxonomically diverse can be found in extreme settings, such as marine or hypersaline habitats (Vera-Gargallo et al., \u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The physicochemical characteristics of these ecosystems, such as pH, salinity, and ionic compositions, vary greatly (An et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Table\u0026nbsp;4.1 showed the physiochemical analysis of Oniru beach water. Oniru Beach surface water temperature averaged 26.35\u0026deg;C, well below the World Health Organization guideline maximum of 30\u0026deg;C for tropical coastal waters, indicating a thermally stable environment with minimal risk of heat-induced stress on aquatic life. Water temperature, defined as the measure of thermal energy in the aquatic environment, influences dissolved oxygen solubility, metabolic rates of organisms, and microbial community composition (Larance et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The observed mean of 26.35\u0026deg;C suggests optimal conditions for mesophilic marine microbes and supports normal rates of photosynthesis in phytoplankton without exacerbating thermal stratification (Staehr and Birkeland, \u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Beegam et al., (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) recorded similar thermal stability in the Red Sea, reporting 25.8\u0026ndash;27.5\u0026deg;C across multiple sites (p. 115), underscoring regional climatic parallels. Conversely, in the cooler Atlantic-influenced shores of northern Spain, Mart\u0026iacute;nez, Pire and Mart\u0026iacute;nez-Espinosa, (2022) documented temperatures ranging 18\u0026ndash;22\u0026deg;C, reflecting latitudinal variation. In contrast, tropical estuarine systems such as Ghana\u0026rsquo;s Volta Estuary reached 29.0\u0026ndash;31.2\u0026deg;C during the dry season, occasionally exceeding the WHO limit and stressing local biota (Nyarko et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, Oniru Beach\u0026rsquo;s sub-30\u0026deg;C regime is consistent with stable, non-stressful tropical coastal waters.\u003c/p\u003e\u003cp\u003eThe pH of surface water was 8.3, placing it in the mildly alkaline range and within the typical marine bracket (6.5\u0026ndash;8.5). pH quantifies the hydrogen-ion activity, with values above 7 indicating alkalinity that affects metal speciation, nutrient availability, and enzyme activity in marine organisms (Dickson, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). A pH of 8.3 favors calcifying organisms by promoting carbonate ion saturation but may slightly limit the growth of acidophilic microbes. Behera and Naik, (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported pH values of 8.1\u0026ndash;8.4 along India\u0026rsquo;s Odisha coast, attributing slight alkalinity to carbonate buffer systems in nearshore waters. Aljohny (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found Red Sea surface pH averaging 8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1, reflecting global marine norms. In contrast, urbanized estuaries such as Chesapeake Bay recorded pH as low as 6.8 during algal blooms due to CO₂ accumulation and organic acid production (Behara et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The consistency of Oniru Beach\u0026rsquo;s pH with other oligotrophic coastlines suggests limited anthropogenic acidification and stable carbonate buffering.\u003c/p\u003e\u003cp\u003eElectrical conductivity averaged 208.16 \u0026micro;S/cm, and TDS measured 112.53 mg/L, both well below coastal thresholds of 750 \u0026micro;S/cm and 500 mg/L, respectively. Electrical conductivity reflects ionic strength by quantifying the water\u0026rsquo;s capacity to carry an electrical current, while TDS represents the total concentration of dissolved inorganic solids (Rusydi, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Low values indicate limited mineral runoff and oligotrophic conditions, with minimal risk of metal toxicity or osmotic stress to marine taxa. Ogbuagu and Ayoade (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) characterized oligotrophic coastal waters in the Gulf of Guinea with conductivity of 180\u0026ndash;250 \u0026micro;S/cm and TDS of 100\u0026ndash;150 mg/L, matching our Oniru data. In contrast, eutrophic estuaries such as Nigeria\u0026rsquo;s Lagos Lagoon exhibited conductivity\u0026thinsp;\u0026gt;\u0026thinsp;600 \u0026micro;S/cm and TDS\u0026thinsp;\u0026gt;\u0026thinsp;400 mg/L due to industrial effluents (Popoola and Olaniyi, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSalinity was 30.25\u0026permil;, closely aligning with the global open-ocean average of ~\u0026thinsp;35\u0026permil;. Salinity, defined as the total concentration of dissolved salts expressed in parts per thousand, governs water density, stratification, and osmoregulation in marine organisms (United States Environmental Protection Agency, \u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A value of 30.25\u0026permil; supports typical marine flora and fauna while indicating some freshwater influence or rainfall dilution relative to open ocean. Al-Johny (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) measured Red Sea salinity of 35\u0026ndash;37\u0026permil;, reflecting strong evaporation with minimal riverine input. In the oligotrophic eastern Mediterranean, Galanopoulos et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) recorded 38\u0026permil;, whereas the Amazon estuary near Bel\u0026eacute;m exhibited dramatic fluctuations between 10\u0026ndash;20\u0026permil; due to seasonal discharge (Dias, Gouveia, \u0026amp; Menezes, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Oniru\u0026rsquo;s slightly lower salinity suggests limited freshwater influx, likely from small streams or urban runoff, but remains within the tolerance range for most marine taxa.\u003c/p\u003e\u003cp\u003eDO concentration averaged 3.81 mg/L, falling below the 7 mg/L guideline and indicating the presence of hypoxic microzones. Dissolved oxygen is the amount of gaseous O₂ dissolved in water, essential for aerobic metabolism; values below 5 mg/L are considered hypoxic, potentially stressing obligate aerobes and favouring facultative anaerobes (Diaz and Rosenberg, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Sotto, Campini, and Willson (\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) described DO of 3.5\u0026ndash;4.5 mg/L in semi-enclosed bays undergoing periodic hypoxia, attributing fluctuations to stratification and microbial respiration. By contrast, the open Red Sea maintained DO\u0026thinsp;\u0026gt;\u0026thinsp;6 mg/L year-round (Beegam, Khaleel and Yusuf, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In highly eutrophic Chesapeake Bay, DO frequently fell below 2 mg/L in deep channels, creating anoxic zones (Behara, Li, and Sanchez, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Oniru\u0026rsquo;s sub-5 mg/L DO suggests mild hypoxia, possibly seasonal or localized, which could influence fish distribution and benthic community structure.\u003c/p\u003e\u003cp\u003eNitrate was 0.50 mg/L, phosphate 0.05 mg/L, and sulfate 2.73 mg/L, consistent with oligotrophic waters defined by low nutrient concentrations and limited primary productivity. Nutrient levels measure inorganic inputs supporting autotrophic growth. Oligotrophy denotes nutrient scarcity (\u0026lt;\u0026thinsp;1 mg/L nitrate; \u0026lt; 0.1 mg/L phosphate), constraining phytoplankton biomass (Wetzel, \u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Ogbuagu and Ayoade (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) characterized West African coastal oligotrophy with nitrate 0.3\u0026ndash;0.6 mg/L and phosphate 0.02\u0026ndash;0.08 mg/L, aligning with Oniru. The Red Sea exhibited nitrate\u0026thinsp;\u0026lt;\u0026thinsp;0.5 mg/L and phosphate\u0026thinsp;\u0026lt;\u0026thinsp;0.1 mg/L (Beegam et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, Chesapeake Bay nitrate often exceeds 5 mg/L and phosphate\u0026thinsp;\u0026gt;\u0026thinsp;0.5 mg/L due to agricultural runoff, driving eutrophic blooms (Behara et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The low sulphate at Oniru further indicates minimal industrial discharge.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysiochemical analysis of Oniru beach water\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePARAMETERS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWater sample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWHO\u0026rsquo;s permissible limit (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.35\u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u003csup\u003eo\u003c/sup\u003e C\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.5\u0026ndash;85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC (\u0026micro;S/cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e750\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDS (mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112.530\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDO (mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChloride(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrate(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhosphate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSulphate(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Mineral Analysis of Oniru beach water\u003c/h2\u003e\u003cp\u003eMinerals are classified as inorganic nutrients indispensable for maintaining specific physicochemical processes and determining microbial structure in an ecosystem (Abdullah et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Table\u0026nbsp;4.2 showed the metal analysis of Oniru Beach surface water. Sodium (Na⁺) was 68.4 mg/L and magnesium (Mg\u0026sup2;⁺) was 12.15 mg/L, both within the World Health Organization (WHO) coastal water quality guidelines (200 mg/L for Na⁺; 30 mg/L for Mg\u0026sup2;⁺). Sodium and magnesium are the dominant seawater cations, governing salinity, osmotic balance, and microbial osmoadaptation (Madigan et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Their observed levels suggest unimpacted seawater chemistry with sufficient ionic strength for normal microbial physiology. Along the Red Sea coast, Beegam et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported Na⁺ of 60\u0026ndash;75 mg/L and Mg\u0026sup2;⁺ of 10\u0026ndash;14 mg/L, mirroring Oniru Beach values. In the tropical Pacific, Millero (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) documented Na⁺ at 66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 mg/L and Mg\u0026sup2;⁺ at 11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 mg/L in undisturbed open-ocean waters. Conversely, coastal discharge from desalination plants in South Korea elevated Mg\u0026sup2;⁺ to 18\u0026ndash;25 mg/L (Kim et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePotassium (K⁺) was 50.8 mg/L, substantially exceeding the WHO guideline of 12 mg/L for recreational waters. As an essential intracellular cation, K⁺ regulates osmotic pressure and activates microbial enzymes (Epstein, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Elevated coastal K⁺ often derives from terrestrial runoff, fertilizer leaching, or sewage discharge and can shift microbial communities toward halotolerant taxa. Skowron et al. (\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) measured K⁺ spikes of 45\u0026ndash;60 mg/L in Baltic Sea sites adjacent to agricultural catchments, while Ahmad and Izhar (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found 48.2 mg/L near Pakistan\u0026rsquo;s Indus Delta. In contrast, pristine Pacific atolls typically exhibit K⁺ \u0026lt; 10 mg/L (Walter et al., \u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), underscoring Oniru\u0026rsquo;s deviation likely from anthropogenic inputs.\u003c/p\u003e\u003cp\u003eCalcium (Ca\u0026sup2;⁺) measured 115.1 mg/L, above the 75 mg/L standard for marine recreational waters. Calcium contributes to water hardness, carbonate buffering, and serves as a cofactor for microbial cell-wall stability and signal transduction (Dom\u0026iacute;nguez et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Excess Ca\u0026sup2;⁺ can precipitate carbonate minerals and influence biofilm formation. Nearshore waters of the South China Sea exhibit Ca\u0026sup2;⁺ of 100\u0026ndash;130 mg/L, attributed to limestone watershed dissolution (Zhou et al., \u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), whereas open‐ocean Sargasso Sea samples maintain Ca\u0026sup2;⁺ \u0026asymp; 85\u0026thinsp;\u0026plusmn;\u0026thinsp;5 mg/L (Thompson \u0026amp; Sigman, \u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Oniru\u0026rsquo;s elevated Ca\u0026sup2;⁺ thus likely reflects regional carbonate inputs or urban runoff.\u003c/p\u003e\u003cp\u003eIron (Fe) concentration was 2.71 mg/L, over nine times the WHO limit of 0.30 mg/L. Iron is a limiting micronutrient in marine systems, essential for respiration and enzymatic reactions (de Baar et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Excess Fe can catalyse oxidative stress yet also fuel siderophore-producing bacteria. Seasonal upwelling in the Arabian Sea produces Fe of 2\u0026ndash;4 mg/L, correlating with Vibrio blooms (Raval et al., \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Brazilian coastal lagoons, Fe\u0026thinsp;\u0026gt;\u0026thinsp;2 mg/L arises from iron‐ore processing discharge, favoring siderophilic Actinobacteria (Ferreira et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the open ocean, Fe rarely exceeds 0.002 mg/L (Boyd \u0026amp; Ellwood, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), highlighting Oniru\u0026rsquo;s enrichment, likely from urban or industrial sources.\u003c/p\u003e\u003cp\u003eSelenium (Se) at 0.052 mg/L and zinc (Zn) at 0.195 mg/L were within WHO safety ranges (Se\u0026thinsp;\u0026lt;\u0026thinsp;0.1 mg/L; Zn\u0026thinsp;\u0026lt;\u0026thinsp;3 mg/L). Both elements are critical micronutrients for antioxidant enzymes, glutathione peroxidases and superoxide dismutases, respectively (Vallee \u0026amp; Auld, 1990; Hatfield \u0026amp; Gladyshev, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Lahiri et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) documented Se 0.03\u0026ndash;0.07 mg/L and Zn 0.18\u0026ndash;0.22 mg/L in coastal waters near Mumbai, reflecting baseline urban influence. By contrast, Zn often exceeds 1 mg/L near smelting zones in China (Wang et al., \u003cspan citationid=\"CR142\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Arsenic (As) measured 0.015 mg/L and lead (Pb) 0.010 mg/L, both at or above WHO toxicity thresholds (0.01 mg/L). Arsenic disrupts cellular respiration by substituting phosphate in ATP, while lead impairs enzyme function and membrane integrity (Nordstrom, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Patrick, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Mart\u0026iacute;nez-Garc\u0026iacute;a et al. (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found as 0.01\u0026ndash;0.02 mg/L and Pb 0.005\u0026ndash;0.012 mg/L in Spanish Mediterranean harbors, linked to historic mining. In remote Pacific atolls, As and Pb are typically\u0026thinsp;\u0026lt;\u0026thinsp;0.001 mg/L (Tanoue et al., \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), underscoring Oniru\u0026rsquo;s moderate heavy-metal exposure, likely from urban runoff or atmospheric deposition, posing ecological and public‐health concerns.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMineral Analysis of Oniru beach water\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePARAMETERS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWater sample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWHO\u0026rsquo;s permissible limit (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSodium(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e115.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePotassium(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMagnesium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelenium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNickel(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArsenic(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLead(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVanadium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc(mg/l)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Bacterial community\u003c/h2\u003e\u003cp\u003eThe microbial community structure in the collected water samples was analysed using targeted 16S rRNA amplicon sequencing. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the amplicon sequencing of Oniru Beach surface water revealed Proteobacteria as the dominant phylum (53.72%), followed by Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%), and Firmicutes (1.37%). In microbial ecology, a phylum represents a high-level taxonomic rank grouping organisms that share fundamental structural and genetic traits (Ruggiero et al., \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The predominance of Proteobacteria, a highly diverse phylum encompassing many Gram‐negative lineages involved in nutrient cycling reflects typical marine community structure (Gu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Bacteroidetes, known for polymer degradation and peptide utilization, comprise key heterotrophs in oligotrophic waters (Hahnke et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The relatively low abundance of Actinobacteria, Deinococci, and Firmicutes indicates selective pressures favoring Gram‐negative, halotolerant taxa under saline and UV‐intense conditions. Coastal and open‐ocean surveys consistently report Proteobacteria proportions of 40\u0026ndash;60% in oligotrophic marine systems (Zhou et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Ambati and Kumar, (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) documented Proteobacteria at 57% in Indian Arabian Sea waters, comparable to our 53.7%. Behera and Naik, (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) observed Gammaproteobacteria alone comprising\u0026thinsp;~\u0026thinsp;35% of isolates in the Arabian Gulf, underpinning Proteobacterial ubiquity in saline habitats. Mediterranean surveys record Bacteroidetes at 20\u0026ndash;30% and Actinobacteria at 10\u0026ndash;20% (Gall\u0026egrave; et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whereas Oniru\u0026rsquo;s slightly higher Bacteroidetes and lower Actinobacteria mirror the genuine oligotrophic signature of Nigerian coastal waters.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe taxonomic abundances of classes from the most abundant to least abundant are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. At the class level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), Gammaproteobacteria dominated (47.72%), followed by Bacteroidia (29.43%) and Alphaproteobacteria (5.80%). Gammaproteobacteria include numerous metabolically versatile genera (e.g., Pseudomonas, Acinetobacter) that thrive under nutrient-limited, saline conditions by exploiting diverse carbon sources (Kateete et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Bacteroidia (formerly the Bacteroidetes class) drive polysaccharide degradation, critical for recycling marine organic matter (McKee et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Alphaproteobacteria, often oligotrophic specialists like SAR11, typically dominate open-ocean surface waters; their lower abundance here may reflect Oniru\u0026rsquo;s nearshore nutrient profiles. Gulf of Mexico metagenomes show Gammaproteobacteria at ~\u0026thinsp;40% and Alphaproteobacteria at ~\u0026thinsp;25% in coastal sites (Cevallos and Degli Esposti, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Oniru\u0026rsquo;s elevated Gammaproteobacteria aligns with Liu and Liu, (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) findings of Gammaproteobacterial predominance (~\u0026thinsp;35%) in Arabian Gulf samples, suggesting that nearshore anthropogenic inputs selectively boost copiotrophic Gammaproteobacteria. In contrast, truly oligotrophic open‐ocean sites, such as the Sargasso Sea, display Alphaproteobacteria dominance (\u0026gt;\u0026thinsp;50% SAR11) (Giovannoni, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), highlighting Oniru\u0026rsquo;s transitional nearshore ecology.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe classification of total reads into lower taxonomic levels revealed extremely diverse bacterial communities in collected water samples, with up to 39 genera being detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among identified genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), \u003cem\u003eAcinetobacter\u003c/em\u003e (14.00%), \u003cem\u003eStenotrophomonas\u003c/em\u003e (11.60%), \u003cem\u003eChryseobacterium\u003c/em\u003e (2.56%), \u003cem\u003eEnterobacter\u003c/em\u003e (5.36%), and \u003cem\u003ePseudomonas\u003c/em\u003e (2.90%) were most abundant. Genera such as \u003cem\u003eAcinetobacte\u003c/em\u003er and \u003cem\u003ePseudomona\u003c/em\u003es are notable for metabolic plasticity and halotolerance, enabling survival in fluctuating salinities and nutrient conditions (Lupo et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Stenotrophomonas often colonizes both environmental and clinical niches, reflecting its versatile stress-response mechanisms. Chryseobacterium sp. produces exopolysaccharides that facilitate adhesion and protection against desiccation and UV (Casillo et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Beegam et al., (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported Stenotrophomonas comprising\u0026thinsp;~\u0026thinsp;12% of culturable isolates from Thailand\u0026rsquo;s coastal waters, identical to our 11.6%. Acinetobacter frequently represents 10\u0026ndash;20% of marine bacteria in oligotrophic settings, as seen in Mediterranean sediments (Sawale et al., \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Arabian Gulf studies (Pavloudi et al., \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In European coastal lagoons, Pseudomonas accounted for ~\u0026thinsp;5% of total reads (Ebohon et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), comparable to our 2.9%. Chryseobacterium prevalence (2\u0026ndash;4%) mirrors findings by Jung et al., (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in Mediterranean sediment microbiomes, suggesting its niche specialization under saline stress.\u003c/p\u003e\u003cp\u003eA total of 80 distinct bacterial species were identified in the water samples. Most of the species identified are Human-associated opportunists (\u003cem\u003eAcinetobacter baumannii, Klebsiella quasipneumoniae, Stenotrophomonas maltophilia, Mycobacterium tuberculosis\u003c/em\u003e) co-occurred with environmental specialists (\u003cem\u003eMoraxella osloensis, Pedobacter chitinilyticus, Deinococcus ficus\u003c/em\u003e) and key functional taxa (\u003cem\u003eComamonas terrigena, Rhizobium spp., Microbacterium esteraromaticum\u003c/em\u003e). Species richness quantifies the number of distinct taxa present, a key metric of community diversity (Bhatt, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The co-presence of opportunistic pathogens and extremophiles underscores the dual public-health and ecological significance of Oniru\u0026rsquo;s microbiome: pathogens signal fecal or anthropogenic inputs, while extremotolerant taxa reflect selective pressures from UV radiation, salinity, and nutrient scarcity. Functional groups involved in nitrogen cycling and pigment production indicate active biogeochemical processes. Coastal surveys often report 50\u0026ndash;100 bacterial species in oligotrophic waters, paralleling our 80‐species tally (Logue et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). \u003cem\u003eDeinococcus\u003c/em\u003e spp. have been identified in UV‐exposed Mediterranean and Pacific intertidal zones at ~\u0026thinsp;2% abundance due to robust DNA‐repair systems (Jeong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nitrogen‐cycling genera (\u003cem\u003eComamonas, Rhizobium\u003c/em\u003e) contribute\u0026thinsp;~\u0026thinsp;5\u0026ndash;10% of coastal bacterial assemblages in the Baltic Sea, supporting similar roles in Oniru (Lo et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These parallels reinforce the existence of a global \u0026ldquo;core marine halophilic microbiome,\u0026rdquo; modulated by local inputs and selective pressures.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Screening of the isolates for salt tolerance\u003c/h2\u003e\u003cp\u003eAn important parameter for the laboratory study of newly isolated strains from saline environments is the assessment of salt tolerance either on solid or liquid media. The ability of the isolated bacterial strains to grow on agar supplemented with NaCl concentrations ranging from 3 to 30% was further evaluated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Salt-tolerance assays of 16 bacterial isolates from Oniru Beach revealed three distinct tolerance categories (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Isolates 1, 3, 4, 8, 15, and 16 demonstrated robust growth in media containing up to 30% NaCl, classifying them as extremely halophilic. A second group of isolates grew optimally at 15\u0026ndash;20% NaCl, consistent with moderately halophilic behavior. Finally, isolates 2, 7, and 9\u0026ndash;12 failed to grow above 20% NaCl, indicating halotolerant phenotypes with upper tolerance limits below extreme conditions.\u003c/p\u003e\u003cp\u003eHalophiles are organisms requiring or tolerating high salt concentrations for growth; they are conventionally categorized as slight (2\u0026ndash;5% NaCl), moderate (5\u0026ndash;20% NaCl), or extreme (\u0026gt;\u0026thinsp;20% NaCl) halophiles (Irshad et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Halotolerant microbes grow across a broad salinity range but do not require high salt concentrations. In our assays, the ability of six isolates to proliferate at 30% NaCl underscores their adaptation to severe osmotic stress, likely via specialized cellular mechanisms such as compatible solute accumulation and salt-in strategies (Neagu and Stancu, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The intermediate group\u0026rsquo;s tolerance to 15\u0026ndash;20% NaCl suggests typical moderate halophile physiology, wherein Osmo protection is balanced to maintain enzyme functionality (Irshad et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The halotolerant subset, ceasing growth above 20% NaCl, likely relies on more limited osmoregulatory capacities. Yoo et al., (\u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that coastal isolates from the Yellow Sea exhibited optimum growth at 15\u0026ndash;25% NaCl, with only a few strains surviving at 30%, paralleling our observation that most Oniru Beach isolates are moderate halophiles, while only select strains achieve extreme halophily (Yoo et al., \u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ben Hamad Bouhamed et al., (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) characterized \u003cem\u003eHalobacterium salinarum\u003c/em\u003e from solar salterns, canonical extreme halophiles showing robust growth at 25\u0026ndash;30% NaCl, analogous to our six extreme halophiles, suggesting similar osmoregulatory adaptations such as high‐affinity K⁺ uptake and intracellular KCl accumulation. In the Arabian Sea, Javid et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) delineated halotolerance among Gammaproteobacteria isolates: moderate halophiles tolerated 10\u0026ndash;30% NaCl, whereas extreme halophiles grew at 40\u0026ndash;50% NaCl, illustrating an even broader tolerance spectrum. Although our extreme isolates thrived at 30% NaCl, none reached the 40% threshold, suggesting Oniru Beach\u0026rsquo;s salinity selects for but does not fully mimic solar salt extremophile.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eIsolation of bacteria at different Salt concentration\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIsolates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" 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align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e+\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.4 Phenotypic and Biochemical Characterization\u003c/b\u003e of \u003cb\u003eselected isolates\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe isolated halophilic bacteria exhibited distinct morphological and biochemical traits, highlighting variations in their structural and metabolic characteristics as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Five isolates exhibiting growth at \u0026ge;\u0026thinsp;25% NaCl were selected for in-depth phenotypic and biochemical studies. Colonial attributes (morphology, pigmentation, margin, elevation) were documented on ZMA and NA‐15% plates after 72 h incubation. Cell shape, arrangement, and Gram reaction were determined by light microscopy of cultures in exponential phase. Biochemical profiling followed Bergey\u0026rsquo;s Manual protocols using HiMedia reagents: catalase and oxidase tests, Simmons citrate utilization, motility assays, methyl red, and carbohydrate fermentation (lactose, sucrose, mannitol) in phenol‐red broth. Gram staining revealed that isolates 1 and 3 were Gram-negative, while 8, 15 and 16 were Gram-positive (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The isolates exhibited distinct cellular morphologies as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Additionally, motility was observed in isolates 1,3,15 and 16, whereas 8 were non-motile. Although some differences were observed in their characteristics (e.g., colony colour, Gram staining, morphology). The isolate 8 were catalase-negative, whereas 1,3,15 and 16 were catalase-positive. No differences were observed in oxidase activity and methyl red reaction, as all isolates were oxidase-negative (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhenotypic and Biochemical characteristics of the extremely halophilic bacteria isolates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColonial morphology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCircular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCircular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eirregular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRegular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eregular\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColony\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConvex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConvex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFlat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConvex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConvex\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColony density\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOpaque\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOpaque\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOpaque\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOpaque\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etranslucent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePigmentation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ered\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ered\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCream\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCream\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCell shape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRod\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erod\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ecocci\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRod\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRod\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGram staining\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCatalase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e`+ve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecitrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOxidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethyl red\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLactose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e- ve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSucrose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMannitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+ve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e-ve\u0026thinsp;=\u0026thinsp;negative, +ve\u0026thinsp;=\u0026thinsp;positive\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Molecular identification of selected isolates\u003c/h2\u003e\u003cp\u003eThe genetic analysis of the 5 isolates was performed using PCR-based molecular methods, specifically 16S rRNA gene amplification. Successful PCR amplification of the bacterial 16S rRNA gene using the 27f/1492r primers in all 5 isolates confirmed their bacterial origin as shown in Fig.\u0026nbsp;4. High-throughput 16S rRNA gene sequencing of the 5 halophilic isolates yielded clear species assignments (Fig.\u0026nbsp;4). Isolates 1 and 3 shared 99.78% and 98.93% sequence similarity to \u003cem\u003eSerratia marcescens\u003c/em\u003e (Fig.\u0026nbsp;4a and b). Isolate 8 matched \u003cem\u003eStaphylococcus edaphicus\u003c/em\u003e at 99.85% similarity (Fig.\u0026nbsp;4c), while isolates 15 and 16 corresponded to \u003cem\u003eKurthia gibsonii\u003c/em\u003e at 99.93% and 99.78%, respectively (Fig.\u0026nbsp;4d and e). All sequences were deposited in GenBank under accessions OP909706\u0026ndash;OP909753. According to the commonly accepted threshold for bacterial species delineation\u0026mdash;\u0026ge;98.7% 16S rRNA similarity, these values provide robust confirmation of species identity (Beye et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Oyewusi \u003cem\u003eet al\u003c/em\u003e., 2020). The 16S rRNA gene encodes the RNA component of the small ribosomal subunit and is highly conserved among bacteria, making it the gold standard for phylogenetic placement and species identification (Byrne et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Ecologically, \u003cem\u003eS. marcescens\u003c/em\u003e, primarily known as an opportunistic pathogen has been recovered from saline environments, demonstrating halotolerance (Ho et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Its presence in Oniru Beach suggests either terrestrial runoff or adaptation to marine microhabitats. \u003cem\u003eS. edaphicus\u003c/em\u003e, originally isolated from arid desert soils, similarly tolerates moderate salinity and may carry Osmo adaptive genes enabling survival in coastal matrices (Pantůček et al., \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eK. gibsonii\u003c/em\u003e has been described from saline soils and displays growth profiles aligning with our extreme-halophile phenotypes (Chauhan and Samant, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These concordances between molecular identity and phenotypic salt tolerance reinforce the validity of our taxonomic assignments and hint at shared osmoregulatory strategies across divergent environments. Ho et al., (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) demonstrated that marine isolates of \u003cem\u003eS. marcescens\u003c/em\u003e possessed Na⁺/H⁺ antiporter systems enabling growth at 8\u0026ndash;10% NaCl, paralleling our isolates\u0026rsquo; moderate halotolerance. Pantůček et al., (\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) characterized \u003cem\u003eS. edaphicus\u003c/em\u003e strains from Saharan soils that grew optimally at 5% NaCl and survived up to 15%, matching our isolate\u0026rsquo;s phenotypic profile. Chauhan and Samant (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported \u003cem\u003eK. gibsonii\u003c/em\u003e tolerating 20\u0026ndash;25% NaCl, corroborating the extreme-halophilic capacity we observed. Together, these studies illustrate the ecological plasticity of these taxa and confirm that 16S rRNA\u0026ndash;based identification reliably predicts salt-tolerance phenotypes across habitats.\u003c/p\u003e\u003cp\u003eA neighbour-joining phylogenetic tree constructed from aligned 16S rRNA sequences resolved three well-supported clades (Fig.\u0026nbsp;4). \u003cem\u003eSerratia marcescens\u003c/em\u003e isolates formed a distinct branch within the Enterobacterales, exhibiting\u0026thinsp;\u0026gt;\u0026thinsp;95% bootstrap support. \u003cem\u003eStaphylococcus edaphicus\u003c/em\u003e grouped with environmental Staphylococci in the Firmicutes, and \u003cem\u003eKurthia gibsonii\u003c/em\u003e isolates clustered as a tight Actinobacteria subclade. Phylogenetic trees graphically represent evolutionary relationships; the neighbour-joining method reconstructs trees based on pairwise distance matrices and is particularly suited for large datasets. Bootstrap support values, percentages derived from resampling provide confidence estimates for individual branches, with values\u0026thinsp;\u0026gt;\u0026thinsp;70% indicating robust clade stability (Lemoine and Gascuel, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The high bootstrap support (\u0026gt;\u0026thinsp;95%) across our major branches underscores the resolution power of 16S rRNA for genus-level discrimination among halophilic bacteria. Ecologically, phylogenetic clustering often mirrors adaptation to similar niches: halophiles from solar salterns form discrete clades corresponding to taxonomic lineages and environmental pressures (Elshafey et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In our analysis, the clear separation of Proteobacteria (Enterobacterales, Staphylococci) and Actinobacteria (\u003cem\u003eKurthia\u003c/em\u003e) reflects both genetic divergence and ecological specialization in saline habitats. Soto-Varela et al., (\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported\u0026thinsp;\u0026gt;\u0026thinsp;90% bootstrap support for 16S-based clades of halotolerant Bacilli and Gammaproteobacteria isolated from Spanish salterns, demonstrating the method\u0026rsquo;s reproducibility. Plominsky et al., (\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) highlighted that phylogenetic clustering of halophiles often correlates with osmoadaptation mechanisms. These studies confirm that 16S rRNA neighbor-joining analysis reliably reconstructs evolutionary and ecological relationships among halophilic bacteria.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Secondary Metabolites of Halophilic Isolated Bacteria\u003c/h2\u003e\u003cp\u003eBacteria isolated from saline environments are known to produce novel secondary metabolites, which are clinically important natural products and may be the next frontier of drug discovery (Oyewusi et al., \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e) Consequently, we evaluated the capacity of newly halotolerant isolated bacterial strains to novel secondary metabolites as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;5. GC\u0026ndash;MS analysis of five extreme halophilic isolates yielded 36 distinct compounds, among which glycerol, arabinose, mannitol, propanoic acid, and dodecane were consistently detected across all strains. Compatible solutes are small organic molecules that accumulate intracellularly to counterbalance external osmotic pressure without perturbing macromolecular function (Oyewusi et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Glycerol, a triol, stabilizes proteins and membranes under hyperosmotic stress (Sz\u0026eacute;l et al., \u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Arabinose and mannitol, pentose and hexitol sugars respectively, function similarly by promoting cytoplasmic osmolality (Desai and Rao, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Propanoic acid and dodecane may modulate membrane fluidity and oxidative stress responses. The conservation of these osmolytes suggests a shared core osmoadaptation pathway among marine halophiles, mirroring findings in diverse saline environments (Mukhtar et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Marine halophiles frequently synthesize ectoine and hydroxyectoine, yet glycerol and mannitol remain widespread (Sharma et al., \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ho et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported arabinose accumulation in Serratia from terrestrial salterns. The presence of propanoic acid and dodecane aligns with Diomand\u0026eacute; et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), who identified similar fatty acid derivatives in Bacillus halophiles, reinforcing these osmolytes\u0026rsquo; ubiquity across marine and terrestrial halophiles.\u003c/p\u003e\u003cp\u003eSerratia sp. strain HOKA1 produced 1,12-tridecadiene and ergostane, whereas HOKA3 uniquely synthesized tetral glycol and ascorbic acid. Terpenoids such as ergostane are steroid-like isoprenoids implicated in membrane modulation and oxidative stress defence (C\u0026acirc;mara et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Ascorbic acid (vitamin C) serves as antioxidants, scavenging reactive oxygen species generated under salt stress (Zheng et al., \u003cspan citationid=\"CR150\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The detection of these molecules highlights metabolic specialization within Serratia isolates, suggesting niche differentiation even among close relatives. Clements-Decker et al., (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) characterized Serratia from salt flats, reporting ergostane derivatives as key adaptive metabolites. Alhaj Hamoud et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) noted ascorbic acid production in marine \u003cem\u003eSerratia marcescens\u003c/em\u003e, linking it to enhanced oxidative resistance.\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus sp\u003c/em\u003e. strain HOKA8 synthesised 13-octadecenoic acid and N-acetylindole. Unsaturated fatty acids like 13-octadecenoic acid adjust membrane fluidity, preserving functionality in hyperosmotic conditions (Harayama and Antonny, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). N-acetylindole, a tryptophan derivative, may act as a signaling molecule influencing biofilm formation and stress resilience (Scherzer et al., \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This metabolite suite underscores the dual structural and regulatory adaptations employed by Staphylococcus in saline niches. Omotoyinbo et al., (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) detected similar fatty acids in \u003cem\u003eStaphylococcus aureus\u003c/em\u003e from seawater, correlating unsaturation levels with halotolerance. Le and Otto, (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) described N-acetylindole in coastal Staphylococcus isolates, linking it to quorum-sensing modulation under osmotic stress. Our findings confirm that marine Staphylococcus deploy both membrane‐centric and signaling metabolites to thrive in high‐salt environments.\u003c/p\u003e\u003cp\u003e\u003cem\u003eKurthia sp.\u003c/em\u003e strains HOKA15 and HOKA16 share tetraethylene glycol, 3-octadecanone, and inoleic acid, with HOKA16 exhibiting an additional peak for inoleic acid at ~\u0026thinsp;28 min (Fig.\u0026nbsp;5). Polyethylene glycols like tetraethylene glycol stabilize proteins and membranes by forming hydration shells (Samanta et al., \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Long-chain ketones (3-octadecanone) and unsaturated fatty acids (inoleic acid) modulate membrane phase behavior under osmotic stress (Demirbolat et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The extra inoleic acid peak in HOKA16 may reflect strain-level variation in membrane composition, impacting fluidity and permeability. Yasmin et al., (\u003cspan citationid=\"CR148\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) documented 3-octadecanone in Bacillus halophiles, linking it to enhanced surface activity and potential biosurfactant function. Inoleic acid enrichment echoes observations by Wang et al., (\u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in Halomonas species, indicating that unsaturated fatty acids are central to marine bacterial adaptation.\u003c/p\u003e\u003cp\u003eTwo compounds; acetamide and fucopyranose were detected in all five extreme halophiles, suggesting conserved pathways. Acetamide can serve as a nitrogen source and inhibit protease activity under stress (Qi et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Fucopyranose, a deoxyhexose sugar, may function in extracellular polysaccharide synthesis, enhancing biofilm formation and desiccation resistance (Limoli et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Their universal presence points to shared protective mechanisms across phylogenetically diverse halophiles. Corral et al., (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) identified acetamide in Vibrio halophiles as part of osmoregulatory nitrogen assimilation. Kaur and Dey, (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) described fucopyranose incorporation into halophilic exopolysaccharides, improving cell\u0026ndash;cell adhesion in high-salt matrices.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSecondary metabolites identified from isolated bacteria\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSerratia\u003c/em\u003e sp. strain HOKA1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eSerratia\u003c/em\u003e sp. strain HOKA3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus\u003c/em\u003e\u0026nbsp;sp. \u003cem\u003estrain\u003c/em\u003e HOKA8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eKurthia\u003c/em\u003e sp. strain HOKA15\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eKurthia\u003c/em\u003e sp. strain HOKA16\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDodecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDodecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDodecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArabinose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTetral gyycol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eArabinose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eArabinose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTetral gyycol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGalactose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ed-Glucose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGalactose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGalactose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ed-Glucose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMannitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eXylopyranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMannitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMannitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDodecane\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1, 12-tridecadiene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLyxofuranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13-Octodecenoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13-Octodecenoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3-tetradecene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDicholoacetic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13- Docosenoamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13- Docosenoamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eArabinose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTridecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTrehalose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGalactose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3-tetradecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMannobiose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN-acetylindole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN-acetylindole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMannitol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3-tetradecene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSucrose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAnethole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAnethole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1, 12-tridecadiene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHexadecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ed-Glucitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTagatofuranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTagatofuranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3-tetradecene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eErgostane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAscobic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eErgostane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eErgostane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTridecane\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13-Octodecenoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ed-xylose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcetin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAcetin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3-tetradecane\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13- Docosenoamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMaltose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSorbose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSorbose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3-tetradecene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDodecane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTagatose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTagatose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFructose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3-octadecanone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3-octadecanone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3-octadecanone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eInoleic acid\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1-octadecanethiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFucopytanose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1-octadecanethiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1-octadecanethiol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN-acetylindole\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMethyllinolelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUridine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMethyllinolelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMethyllinolelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMethyllinolelaidate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMethylelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMethylelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMethylelaidate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMethylelaidate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMethyl-octadecenoate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMethyl-octadecenoate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMethyl-octadecenoate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMethyl-octadecenoate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1-docosene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1-docosene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1-docosene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1-docosene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlucuronic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGlucuronic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFucopyranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFucopyranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFucopyranose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFucopyranose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCampesterol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAllose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAllose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCampesterol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRhamnitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRhamnitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRhamnitol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRhamnitol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eButane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTalose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTalose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eButane\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAcetamide\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTetraethylene glycol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTetraethylene glycol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcetin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAcetin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThreose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThreose\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eErgostane\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13-Octodecenoic acid\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13- Docosenoamide\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePropanoic acid\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3-octadecanone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e36.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1-octadecanethiol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNumerous microbes that have evolved to survive in environments with high salt concentrations serve as reservoirs for a variety of compounds that may have commercial value. The problem facing the research of biological compounds made by halophiles at the moment is that their possible uses could not be fully understood or even recognized. 16S rRNA amplicon sequencing analysis revealed a high abundance of Proteobacteria (53.72%), Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%) and Firmicutes(1.37%), with Gammaproteobacteria (47.72%) being the most abundant classes in the water sample. Moreover, using culture-dependent study five halophilic bacteria isolates 1,3,8,15 and 16 were confirmed as \u003cem\u003eSerratia\u003c/em\u003e sp. strain HOKA1, \u003cem\u003eSerratia\u003c/em\u003e sp. strain HOKA3, \u003cem\u003eStaphylococcus\u003c/em\u003e sp. strain HOKA8, \u003cem\u003eKurthia\u003c/em\u003e sp. strain HOKA15 and \u003cem\u003eKurthia\u003c/em\u003e sp. strain HOKA16, respectively, using biochemical and molecular approaches. The current study contributes to the knowledge of microbial ecology which have also creates new avenues for the study of the discovery of novel organisms in extreme environments. These isolated halophilic bacteria may provide biotechnologically essential chemicals for a variety of uses, including the synthesis of industrially important bioactive compounds and other commercial products.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of Interest\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no conflicts to declare.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was partly funded by the TETFund 2020_2024 Institutional Based Research Professional through the Centre for Research and Innovative Development (CRID), Federal Polytechnic Ado-Ekiti, Ekiti State, Nigeria.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eOHA and OOO developed the original idea. OHA developed the protocol. OHA, OAC and OOO performed the experiments and were involved in the collection of data. AAK and BFO wrote the preliminary draft of the article. OHA and OOO analyzed the data. All authors reviewed the manuscript. All authors read and approved the manuscript for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the Biosciences Research Foundation from Federal Polytechnic Ado-Ekiti, Nigeria for their metagenomic analysis facilities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdullah, S. M., Kolo, K., Konhauser, K. O., \u0026amp; Pirouei, M. (2022). Microbial domains and their role in the formation of minerals. In \u003cem\u003eMineral formation by microorganisms: concepts and applications\u003c/em\u003e (pp. 1-39). Cham: Springer International Publishing.\u003c/li\u003e\n\u003cli\u003eAhmad, M., \u0026amp; Izhar, S. (2021). 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Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. \u003cem\u003eThe ISME journal\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(8), 2060\u0026ndash;2077. https://doi.org/10.1038/s41396-020-0669-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aomi","sideBox":"Learn more about [Archives of Microbiology](https://www.springer.com/journal/203)","snPcode":"203","submissionUrl":"https://submission.nature.com/new-submission/203/3","title":"Archives of Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Bacterial diversity, Halophilic bacteria, Marine environment, Oniru beach, Secondary metabolites","lastPublishedDoi":"10.21203/rs.3.rs-7131305/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7131305/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study reports the bacterial diversity and bioactive compounds emanating from halophilic bacterial isolates in popular metropolitan marine Oniru Beach, Lagos, Nigeria. The physicochemical analysis of the water sample depicts a moderately saline, slightly alkaline and oligotrophic environment with low oxygen levels, favouring halophilic bacteria growth. Different metal concentrations, including potassium, calcium, and iron, that influence microbial metabolism and secondary metabolite synthesis or production are contained in appreciable amounts. A high-throughput next-generation sequencing approach and Gas Chromatography-Mass Spectrometry analysis (GC-MS) revealed the diverse bacterial community and bioactive secondary metabolites produced, respectively. The results obtained from 16S rRNA metagenomics showed the bacterial community phyla Proteobacteria (53.72%), Bacteroidetes (29.43%), Actinobacteria (3.88%), Deinococci (1.59%) and Firmicutes (1.37%) in their order of dominance or abundance. In addition, the five top genera; Acinetobacter (14.00%), \u003cem\u003eStenotrophomonas\u003c/em\u003e (11.60%), \u003cem\u003eChryseobacterium\u003c/em\u003e (2.56%), \u003cem\u003eEnterobacter\u003c/em\u003e (5.36%), and \u003cem\u003ePseudomonas\u003c/em\u003e (2.90%) were identified out of the thirty-nine (37) assigned and one (1) assigned genus, indicating a complex and multifunctional microbial community. The phylogenetic identification analysis of extremely halophilic isolates obtained from salt-tolerance assays and 16S rRNA sequencing depicts \u003cem\u003eSerratia marcescens, Staphylococcus edaphicus, and Kurthia gibsonii\u003c/em\u003e, which exhibit diverse phenotypic and biochemical traits. The bioactive compounds or secondary metabolites produced by these isolates showed a diverse range of compounds, including dodecane, glycerol, arabinose, galactose, mannitol, 1,12 tri decadiene and 3-tetracadiene. Collectively, these findings demonstrate that Oniru Beach harbours a rich reservoir of halophilic bacteria with specialized adaptations to salinity and metal stress and with diverse secondary metabolism, offering promising avenues for biotechnological applications such as novel bioactive compounds discovery and development\u003c/p\u003e","manuscriptTitle":"Bacterial Diversity and Characterisation of Secondary Metabolite from Halophilic Bacterial Isolated from Popular Metropolitan Marine Oniru Beach, Lagos, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-24 13:58:12","doi":"10.21203/rs.3.rs-7131305/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-14T00:59:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-11T04:11:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-10T14:29:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334926577636789462759375206095640923834","date":"2025-07-27T12:26:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265178546838112885600005889146410470633","date":"2025-07-24T13:20:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262431179443590754386154009036747251865","date":"2025-07-23T02:44:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29062777634761306092315660234284305675","date":"2025-07-22T12:53:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158038468428800297484986844325525774327","date":"2025-07-22T12:38:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-22T12:24:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T15:59:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-16T02:31:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Microbiology","date":"2025-07-15T13:48:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aomi","sideBox":"Learn more about [Archives of Microbiology](https://www.springer.com/journal/203)","snPcode":"203","submissionUrl":"https://submission.nature.com/new-submission/203/3","title":"Archives of Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b4ad9a01-2b66-4ac7-ba6c-3cf31ef5344f","owner":[],"postedDate":"July 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:09:36+00:00","versionOfRecord":{"articleIdentity":"rs-7131305","link":"https://doi.org/10.1007/s00203-025-04503-z","journal":{"identity":"archives-of-microbiology","isVorOnly":false,"title":"Archives of Microbiology"},"publishedOn":"2025-10-13 15:58:01","publishedOnDateReadable":"October 13th, 2025"},"versionCreatedAt":"2025-07-24 13:58:12","video":"","vorDoi":"10.1007/s00203-025-04503-z","vorDoiUrl":"https://doi.org/10.1007/s00203-025-04503-z","workflowStages":[]},"version":"v1","identity":"rs-7131305","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7131305","identity":"rs-7131305","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}