Untargeted Metabolomics and Antibacterial Properties of Streptomyces Species Sourced From Thai Mangrove

Research Article Untargeted Metabolomics and Antibacterial Properties of Streptomyces Species Sourced From Thai Mangrove Samson Cheruiyot Koech , 1 , 2 Atchara Paemanee , 3 , 4 Wasu Pathom-aree , 5 Phitchayapak Wintachai , 6 Chonticha Romyasamit , 7 Zdenek Kamenik , 8 and Amit Jaisi 1 , 9 1 School of Pharmacy, Walailak University, Tasala, Nakhon Si Tammarat 80160, Tailand 2 College of Graduate Studies, Walailak University, Tasala, Nakhon Si Tammarat 80160, Tailand 3 National Omics Center, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Tani 12120, Tailand 4 Food Biotechnology Research Team, Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Tani 12120, Tailand 5 Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Tailand 6 School of Science, Walailak University, Tasala, Nakhon Si Tammarat 80160, Tailand 7 School of Allied Health Sciences, Walailak University, Tasala, Nakhon Si Tammarat 80160, Tailand 8 Institute of Microbiology, Czech Academy of Sciences, Videnska 1083, Prague 14200, Czech Republic 9 Biomass and Oil Palm Center of Excellence, Walailak University, Tasala, Nakhon Si Tammarat 80160, Tailand Correspondence should be addressed to Amit Jaisi; [email protected] Received 28 August 2024; Accepted 4 April 2025 Academic Editor: Omprakash Sunnapu Copyright ©2025 Samson Cheruiyot Koech et al. Scientifca published by John Wiley & Sons Ltd. Tis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Novel antimicrobial agents are urgently needed to combat the global threat of antimicrobial resistance. Actinobacteria are remarkable producers of bioactive compounds, which are crucial for the discovery of novel drugs to combat antimicrobial resistance. In the current study, bioactivity, phylogenetic analysis, and a dereplication approach were employed to quickly analyze the metabolomic profles of selected strains and aid in selection strain prioritization. Te aim of this study was to screen Tai actinobacteria isolated from the mangrove ecosystem for antibacterial activities. Taxonomic identifcation confrmed the classifcation of these isolates within the genus Streptomyces. Eleven strains identifed as Streptomyces yogyakartensis, S. globisporus, S. albiaxialis, S. misionensis, S. iranensis, S. sanyensis, and S. diastaticus. Te crude extracts of the selected actinobacteria strains exhibited antibacterial activities, with minimum inhibitory concentrations ranging from 9.9 to 1250 μg/mL against methicillin-resistant Staphylococcus aureus,Acinetobacter baumannii, and Klebsiella pneumoniae. Mass-guided molecular networking analysis of the crude extract revealed the metabolomic complexity of the isolates. Structurally unique compounds such as desferrioxamine E, elaiophylin, kanchanamycin C, bisacuberin, dehydroxynordicadamine, desmethylenylnocardamine, chymostatinol A, chymostatin B, desferrioxamine G, ferrioxamine E, and legonoxamine A were detected in the crude extracts. Notably, we report the potential of bioactive compounds isolated from Tai mangrove actinobacteria, demonstrating diverse biological activities. Tis study demonstrated the use of metabolomics to annotate putative bioactive compounds, prioritize strains, and discover novel bioactive metabolites. Keywords: actinomycetes; dereplication; GNPS; LCMS; natural products; one-health approach Wiley Scientifica Volume 2025, Article ID 5510017, 15 pages https://doi.org/10.1155/sci5/5510017 1. Introduction Antimicrobial resistance (AMR) is a growing global health threat with serious implications [1, 2]. Antibiotic resistance has been a persistent issue since the introduction of the frst class of antibiotics and has continued to evolve dynamically [3]. Key factors contributing to the rise of antibiotic resistance include overpopulation, increased global movement, misuse of antibiotics in healthcare and agriculture, selection pressure, inadequate hygiene, and poor waste disposal systems [1, 4]. In developing countries, the lack of adequate AMR surveillance, poor quality control, and clinical misappropriation of antibiotics are major contributors to drug resistance. In contrast, poor hospital regulations and the overuse of antibiotics in food production are signifcant drivers of AMR in developed countries [5, 6]. If precautionary measures are not implemented, AMR-related deaths are projected to reach 10 million annually by 2050 [7]. In 2019, the frst global report on AMR estimated that bacterial AMR was linked to 4.5 million deaths, with 1.27 million directly attributed to bacterial infections [5]. ESKAPE pathogens—Enterococcus faecium,Staphylococcus aureus,Klebsiella pneumoniae,Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species—are now the leading cause of hospital-acquired infections worldwide, with some strains lacking efective treatments [8]. Additionally, the Centers for Disease Control and Prevention (CDC) has identifed 16 bacterial and fungal species as urgent threats to human health [9]. To combat AMR, a global emphasis on the One Health approach is essential. While multiple protocols exist for AMR surveillance, the implementation of a unifed One Health strategy across diferent countries is hindered by the lack of standardized guidelines for monitoring and evaluation [10]. Nature bestowed with unlimited resources in the form of bioactive compounds and intensive research on these resources is very important in drug discovery. Tese bioactive molecules, known as natural products, are produced by living organisms such as plants, animals, and microbes as by-products [11]. Microbes are remarkable producers of various distinctive natural compounds that are crucial for the development of novel drugs. Majority of antibiotics and anticancer medications that are clinically used today were isolated from microbes during the “golden era” [12]. Conventional bioactivity screening and taxonomy-based methods often lead to the reisolation of known compounds [13, 14]. Metabolomics, an advanced “omics” approach, integrates high-throughput analytical techniques with bioinformatics to comprehensively assess metabolites. Dereplication tools such as GNPs, METLIN, and NP-MS help prioritize novel bioactive compounds for isolation [15–17]. Actinobacteria are naturally occurring microbes that play a vital role in decomposing complex organic matter. Tey are renowned for producing the majority of clinically used drugs, including antibiotics, anticancer agents, and immunosuppressants [18]. In recent years, actinobacteria have garnered signifcant attention from researchers, research organizations, and pharmaceutical companies for their applications across various felds, including medicine, agriculture, biotechnology, food, and enzyme industries [19, 20]. Te focus has shifted from screening terrestrial actinobacteria to exploring those from unique ecosystems such as marine environments, mangroves, caves, and Arctic regions [21]. Te extreme conditions in these habitats drive microbial adaptations, leading to the production of bioactive metabolites essential for survival, many of which hold potential for drug discovery [22]. To date, research on mangrove-derived actinobacteria has led to the discovery of at least 88 new species, including eight novel genera. Additionally, over 80 bioactive compounds have been identifed, among them promising molecules such as halichoblelide D, xiamycins, and indolocarbazoles [22, 23]. Four Streptomyces strains (B475, B486, B353, and B98) isolated from mangrove sediments exhibited strong antibacterial activity, particularly against Staphylococcus aureus, methicillin-resistant Staphylococcus aureus (MRSA), Bacillus subtilis, and Micrococcus luteus. Metabolite profling of strain B475 identifed seven quinoxaline-type antibiotics, including quinomycin A, quinomycin monosulfoxide, and fve novel analogs [24]. Eudesmane-5β,11-diol (1), a polycyclic sesquiterpene isolated from the endophytic Streptomyces JMRC: ST027706 associated with the mangrove plant Bruguiera gymnorhiza in Xiamen, China, exhibited potent antibacterial activity. It demonstrated broad-spectrum efcacy, particularly against drug-resistant pathogens such as MRSA, vancomycin-resistant Enterococcus faecalis, and Escherichia coli [25]. Tese fndings highlight the potential of mangrove environments as a valuable source of new antibiotics. Tailand harbors diverse bioresources that remain largely unexplored, particularly in mangrove environments. Te majority of Tailand’s maritime ecosystems have been minimally investigated [26]. While terrestrial Streptomyces species have been extensively studied, only a small fraction of marine and mangrove-derived Streptomyces have been explored, leaving a signifcant gap in our understanding of their potential to produce novel antibiotics. 2. Materials and Methods 2.1. Sample Collection andIsolation of Actinobacteria. A total of 56 mangrove sediment samples were collected from the mangrove areas of Chachoengsao and Chonburi provinces (Figure 1). Te samples were placed in sterile bags, stored at 4°C, and transported to the laboratory for further processing. Tey were then air-dried at room temperature for 1 week and ground into a fne powder. Te dried sediment samples were used for the selective isolation of actinobacteria following the protocol described by Ruttanasutja and Pathomaree [27]. 2.2. Cultivation of Actinobacteria. Pure cultures of actinobacteria were routinely grown on ISP2 agar and incubated at 30°C for 7–14 days. For broth cultivation, a single colony was inoculated into a 5-mL tube of ISP2 broth and incubated on a rotary shaker at 150 RPM and 30°C for 4 days to establish a starter culture. Tis starter culture was then transferred to a 100-mL fask containing ISP2 broth and incubated under the same conditions for 7–14 days. 2Scientifca 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2.3. Extraction of Metabolites From Actinobacteria. Actinobacterial crude extracts were prepared in accordance with the growth medium conditions. Actinobacteria were cultured mostly in ISP2 medium either in agar or in a broth media; hence, the three crude extracts, agar media, supernatant (broth), and mycelia, were prepared for each strain. Firstly, the agar extracts were prepared from fully grown actinobacteria under the necessary conditions (14 days, 30°C) on ISP2 agar media, and then, the agar media along with actinobacteria were cut into small pieces inside the biosafety cabinet and macerated in 50 mL of 100% methanol (RCI LABSCAN, Tailand) with continuous shaking in an incubator for 24 h. Secondly, the pure colonies of actinobacteria were allowed to grow in broth media for 7–14 days, then on the last day of incubation, the broth culture were centrifuged at 5000 rpm/minute for 20 min to separate the supernatant and mycelia. Te supernatant was extracted by the addition of activated XAD 16N resin (Sigma-Aldrich, France) and allowed to extract the necessary metabolites for 12 h on a rotary shaker at 90 rpm, followed by separation of the resin from the supernatant using a Buchner funnel and washing with sterile distilled water. Te washed resin was then placed in a 125-mL fask with 50 mL methanol and extracted three times for 1 h on a rotary shaker at 90 rpm. Lastly, the mycelia were extracted once with 100 mL acetone on a rotary shaker at 90 rpm Tereafter, all the three extracts were pooled together and fltered through Whatman paper flter no. 1, and the resulting fltrate was concentrated using a rotary evaporator (Heidolph, Germany) to evaporate the organic solvents and then freeze-dried in a lyophilizer machine (Christ, Germany) to obtain the dry crude extract. All dried crude extracts were stored in airtight containers at −20 °C until further use for liquid chromatography–mass spectrometry (LC-MS) and biological screening. 2.4. Assessing the In Vitro Antibacterial Activities of the Crude Extracts 2.4.1. Determination of Minimum Inhibitory Concentration (MIC). Te antibacterial activity of the crude extracts from each actinobacterial strain was assessed using the microdilution technique to determine the MIC against MRSA, PW01, Acinetobacter baumannii (PW01), and Klebsiella pneumoniae (PW01), following the protocol outlined by Wiegand et al. 2008 [28] with minor modifcations. Briefy, the crude extract (5 mg/mL) of each active actinobacteria extract was dissolved in 5% dimethyl sulfoxide (DMSO) and dispensed into the 96-microtiter plate. A positive control with a known antibiotic was used and 2.5% DMSO was used as the negative control. Fresh test pathogens, adjusted to a turbidity of OD 625 nm at 0.1 (1 ×10 8 CFU/mL), were prepared in Mueller–Hinton broth. Tese were diluted 20-fold and then inoculated into 96-well microtiter plates. A series of two-fold dilutions were performed across all columns, with each well containing a total volume of 100 μL. Te 96-microtiter plate was incubated at 37°C for 16–18 h, and then 20 μL of resazurin was added and incubated again for 3–4 h. Colistin sulfate (GoldBio, USA, Lot#:0603.073120A) and vancomycin hydrochloride (GoldBio, USA, Lot#:0111.011921A) were used as the positive controls for Gram-negative and Gram-positive bacteria, respectively. Te MIC of the crude extract was determined as the lowest concentration inhibiting visible bacterial growth. All experiments were conducted in triplicate (n�3). 2.4.2. Determination of Minimum Bactericidal Concentration (MBC). A 10-μL sample from the MIC of each test pathogen was taken and inoculated onto a sterile, antibiotic-free Mueller–Hinton agar plate. A spreader was used to spread inoculated serial dilutions to determine the concentration of the crude extract that killed 99.99% of the bacteria. Te inoculated plates were incubated at 37°C for 16–18 h, and the results were recorded. Te concentration of the crude extract that killed 99.99% of the bacterial pathogens was determined as the MBC. All the tests were carried out in triplicates (n�3). 2.5. Assessment of Actinobacteria Against BacterialPathogens. Te agar overlay method was used to evaluate the ability of selected actinobacteria to inhibit the target pathogens MRSA (PW01), A. baumannii (PW01), and K. pneumoniae (PW01). Actinobacteria were grown on marine and ISP2 agar for 5 days at 30°C, with regular monitoring for colony growth. Semisolid Mueller–Hinton agar (0.7% w/v agar) was prepared under aseptic conditions and inoculated with test pathogens, adjusted to an optical density (OD) of 0.1 at 625 nm (1 ×10 8 CFU/mL). Te standardized pathogen Figure 1: A map showing the location where mangrove sediments were collected (courtesy of https://www.pptmaps.com/Editablemap-of-Tailand.html). Scientifca 3 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License suspension was mixed with the semisolid Mueller–Hinton agar and overlaid onto the agar plates where the actinobacteria were already grown. Te plates were then incubated at 37°C for 16–18 h. Active actinobacterial strains were identifed by the presence of clear zones of inhibition around their colonies. All tests were performed in triplicate for each strain (n�3). 2.6. LC-MS Analysis. Approximately 100 mg of each extract was dissolved in 75% methanol (v/v). Te dissolved sample was then mixed and adjusted to a concentration of 50–300 mg/L. Te mixture was then centrifuged at 120,00 ×gat 25°C for 15 min. After that, the resulting supernatant was carefully transferred to a clean 1.5-mL microcentrifuge tube and fltered using a hydrophilized PTFE membrane (pore size: 0.22 μm, diameter: 13 mm). A volume of 5 μL was then injected into an ultra-highperformance liquid chromatography–high-resolution mass spectrometer coupled with an Orbitrap mass analyzer (UHPLCHRMS/MS) for mass identifcation. Te injected sample extract was separated using a Hypersil GOLD™Vanquish C18 column (2.1 ×100 mm, 1.9 μm, Termo Scientifc) with a guard column. Te separation process was performed at 40°C and a fow rate of 0.4 mL/min. Mobile Phase A consisted of 0.1% formic acid (FA) in water, whereas mobile Phase B consisted of 0.1% FA in acetonitrile. Te elution gradient started with 5% B for 4 min, and the percentage of Phase B was then increased to 90% over a period of 10 min. Ten, the column was fushed with 90% Phase B for 4 min, followed by a reduction in the concentration of Phase B to 5% within 1 min, before returning to the initial conditions, with a total runtime of 25 min. Data acquisition was performed using a Termo Scientifc Q-Exactive HF-X hybrid quadrupole-Orbitrap mass spectrometer equipped with a heated electrospray ionization (HESI) source. Full scan MS and data-dependent MS 2 spectra were acquired in both positive and negative ion modes. Ionization parameters included a spray voltage of 3.5 kV (positive) or 2.5 kV (negative), sheath gas of 45 arbitrary units, auxiliary gas of 10 arbitrary units, and sweep gas of two arbitrary units. Te capillary temperature was set to 320°C, and the auxiliary gas temperature was set at 400°C for stable ionization. During the acquisition process, fullscan MS 1 and data-dependent MS 2 (dd-MS 2 ) modes (top n) were acquired with resolutions of 120,000 (with a maximum injection time of 100 ms) and 30,000 (with a maximum injection time of 50 ms), respectively, covering a scan range from 100 to 1500 m/z. Te automatic gain control target was set to 3e6 for consistent signal intensities. Stepped N(CE) values of 20 eV, 30 eV, and 40 eV were set to ensure the desired collision energies. 2.7.Data Processingand MolecularNetworking. Te acquired data fles from LC-MS were processed using Compound Discoverer software 3.3. LC-MS data were processed using a peak-picking algorithm with a minimum peak intensity threshold of 10,000 counts, ensuring only signifcant metabolites were included in the dereplication analysis. For molecular networking, similarity thresholds for MS/MS fragmentation patterns were carefully chosen to cluster structurally related compounds while avoiding false positives. Te ore-cleaned raw data from the data-dependent acquisition mode were converted to mzXL format using an MS converter and uploaded to the global natural products social molecular networking (GNPS) [29] (https://gnps.ucsd.edu) to create an online molecular network. Te MS 2 fragment tolerance and parent mass of tolerance were both set at 0.02 Da. Te network was created with a cosine score of 0.65. more than three matched peaks. Edges were created between two nodes within the network and kept within the network if the node appeared in the top 10 similar nodes. Te molecular family was set to a maximum size of 100. Background signals were eliminated by incorporating media and solvent blank spectra into the spectral library. Cytoscape Version 3.9.1 from the U.S. National Institute of General Medical Sciences was used to visualize the output of molecular networking [30]. Te dereplication method excluded known compounds efciently, allowing us to prioritize novel bioactive strains. [31]. All MS data are publicly available in GNPS (https://gnps.ucsd.edu) under the molecular network search id �e8d5e43b6b104702a07a10099a9644923 and MolNetEnhancer id �bef431f45fd54f3da385a5a50410022 d. 2.8. MicrobeMASST. A search tool within the GNPS platform, designed for taxonomically curating mass spectra in untargeted metabolomics of natural products, was also utilized in this study [32]. Te USI or spectrum peaks, along with the precursor mass of the annotated compound, were copied and uploaded to the following link (https://masst.gnps2.org/microbemasst) to generate a taxonomic tree. Te precursor and fragment ion tolerances were set to 0.05 Da, while the cosine score threshold was set to 0.7, requiring the merging of at least three peaks. 2.9. Molecular Identifcation by 16S rRNA Gene Sequencing. Selected actinobacteria were cultivated in ISP2 medium for 3 days. Total genomic DNA was then extracted using a modifed protocol of the Gene Elute™Bacterial Genomic DNA Kit (Sigma-Aldrich, USA), which included an extended incubation step. Te purifed genomic DNA served as a template for PCR amplifcation of the 16S rRNA gene using universal primers (27F: 5′-AGAGTTTGATCCTGGCTCAG3′and 1492R: 5′-TACGGCTACCTTGTTACGACTT-3′). Te resulting amplicons were sequenced by the Sanger sequencing using the same primers at U2Bio Co., Ltd., Tailand. 2.10. Phylogenetic Analysis. Overlapping regions at the beginning and end of each 16S rRNA sequence from the actinobacterial strains were removed, and the resultant sequences were assembled into contigs using BioEdit Sequence Alignment Editor 7.2. Te obtained nucleotide sequences were analyzed using 16S-based ID BLAST in the EzBiocloud database (https:// www.ezbiocloud.net/) [33] to identify their closest phylogenetic neighbors. Molecular Evolutionary Genetics Analysis (MEGA) Version 11.0 was used for construction of phylogenetic using the neighbor-joining method with 1000 bootstrap replicates to assess the reliability of the branching patterns. Evolutionary 4Scientifca 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License distances were calculated using the maximum composite likelihood method, which was chosen due to its accuracy in estimating phylogenetic relationships in microbial populations [34]. 3. Results and Discussion 3.1. Antibacterial Activities. Preliminary screening of methanolic crude extracts of 165 actinobacteria showed that only 23 strains exhibited antimicrobial activities accounting for 14% of the total actinobacterial strains. Te microdilution technique using the 96 microtiters well plate was used to determine the MIC of the selected active actinobacterial extracts in comparison with the positive control. Selected actinobacterial methanolic extracts exhibited antimicrobial activity against MRSA (PW01), K. pneumonia (PW01), and A. baumannii (PW01) with an MIC range of between (<9.9 - >1250 μg/mL; Table 1). Te MIC and MBC values for strains S1-SC3, 1-3, 1-522, RH1-5-10, AV2-5-14, RH1-5-14, S2-SC16, S1-SC1, and RH1-5-22 ranged from 9.9 to 1250 μg/mL. Tese values are particularly noteworthy, as similar fndings have been reported in only a few studies on mangrove-derived actinobacteria. Tis suggests a potentially unique antibacterial mechanism. Furthermore, agar overlay assay was used to confrm the antibacterial activity of the 23 strains and to narrow down to active specifc strains. However, based on agar overlay assays only, 12 actinobacterial strains exhibited antimicrobial activity against MRSA (PW01), accounting for 48% of the active actinobacteria (Tables 1 and 2, Figure 1S), whereas 11 actinobacterial strains exhibited antimicrobial activity against A. baumannii, accounting for 44% of the active actinobacterial strains (Figure 2S, Tables 1 and 2). Additionally, two actinobacteria strains exhibited residual antimicrobial activity against K. pneumoniae (PW01), accounting for 8% of the total active actinobacteria (Figure 3S, Tables 1 and 2). Furthermore, agar overlay results highlight the unique potential of mangrovederived actinobacteria as a valuable source of antibacterial compounds with 48% of active strains inhibiting MRSA, 44% targeting A. baumannii, and 8% showing residual activity against K. pneumoniae. It is also noteworthy that some of the actinobacterial strains exhibited stronger activity against Grampositive bacteria than Gram-negative bacteria, likely due to diferences in cell wall structure. Additionally, the unique bioactive metabolites produced by mangrove actinobacteria may have higher specifcity for targets present in Gram-positive pathogens, further explaining the observed selectivity. Actinobacterial strains S1-SC3, S5-SC5, S6-SC2, S4-SC11, and S5SC2 were selected for molecular networking in the GNPs platform based on their strong antibacterial activity and diverse metabolomic profles. Tese strains exhibited potent inhibition against target pathogens, and their metabolic extracts contained unique or potentially novel bioactive compounds, making them ideal candidates for further dereplication and structural annotation (Figures 2 and 3, Tables 1 and 2). 3.2. Molecular Identifcation by 16S rRNA Gene Sequencing. Te BLAST analysis identifed all selected actinobacteria as Streptomyces species with 16S rRNA gene sequence similarity values ranged between 99.21% and99.86% (Table 3). Tree isolates were closely related to S. albiaxialis, and two isolates were closely related to S. iranensis. Te remaining isolates were nearest to S. yogyakartensis, S. globisporus, S. misionensis, S. endocofeicus, S. sanyensis, and S. ardesiacus. Phylogenetic tree further confrms the assignment of these selected actinobacteria as members of the genus Streptomyces (Figure 4). 3.3. Molecular Networking. Te adopted molecular networking approach via the GNPS molecular network search and MolNetEnhancer resulted in the annotation of various classes of compounds that were grouped into diferent molecular families, namely, Families A, B, C, D, E, F, G, and H. (Figure 5, Table 4). Te dereplication method excluded known compounds efciently, allowing us to prioritize novel bioactive strains. Molecular networking analysis revealed the presences of hydroxamate-type siderophores in Family A, E, F, and G (Figure 5). Family A consisted of mainly hydroxamate-type siderophores dehydroxynorcardamine (m/z 603.27, [M + 2H] 2+ , Figure 4S), and it was detected in crude extracts of strain S1-SC3 and S6-SC2, desferioxamine D2 (m/z 587.33 [M + H] + ) was detected in crude extract of S1-SC3 only, desferioxamine G (m/z 618.38 [M + H] + , Figure 5S) was detected in crude extracts of S1-SC3 and S6SC2 (Figure 5, Table 4). Desferrioxamine D2 (m/z 587.22 [M + H] + ) was detected in the crude extracts of strains S1SC3 (Figure 5). Family E consisted of legonoxamine A (m/z 690.30 [M + H] + ), which was detected in crude extracts of S5-SC5, and Ferrioxamine B (m/z 614.10 [M + H] + ) (Figure 9S), which was also detected in strain S5-SC5 (Figure 5). Family G consisted of ferrioxamine E (m/z 652.93 [M + H] + ), (Figure 11S) which was detected in the crude extracts of S1-SC3, S6-SC2, S4-SC11, and S5-SC5 (Figure 5). Legonoxamine G (m/z 674.57, [M + H] + ) (Figure 5) was detected in crude extracts of strains S1-SC3, S6-SC2, S5-SC5 and S5-SC2. Desferrioxamine E (m/z 601.35 [M + K] + , Figure 12S) was detected in crude extracts of S1-SC3, S6SC2, and S5-SC5 and annotated in Family E (Figure 5, Table 4). Molecular network analysis of Family B revealed the presence of sarmetosides and other analogs annotated in the GNPS network. Family B consisted of sarmetoside B (m/z 663.45 [M + H] + ) (Figure 5) as the only compound annotated in this family, which was detected in the crude extracts of strains S1-SC3, S6-SC2, S5-SC5, S4-SC11, and S5-SC2 (Figure 5). Family C was composed of the macrolide antibiotic kanchanamycin C with a parent mass of (m/z 1054.64 [M + H] + ) (Figure 5, Figure 6S) and other possible novel compounds with a parent mass of (m/z 1068.65 [M + H] + Figure 5), and it was only detected in crude extracts of strain S1-SC3. Te parent mass of 1068.65 could be assigned to kanchanamycin D, which contains a molecular mass of 1069 in the literature review and an increase of Δ+14 Da (underwent methylation) (Figure 5). Family D contained ureylene-containing oligopeptides. Te molecular network contained chymostatin B (m/z 594.30 [M + H] + ) and chymostatinol A (m/z 596.31 [M + H] + ), identifed by the dereplicator plus in the GNPS dashboard (Figure 5). Scientifca 5 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Moreover, these compounds were detected only in strain S4SC11 only. Family H of macrolide antibiotic elaiophylin with a parent mass of (m/z 1047.53 M + Na) (Figure 5, Figure 13S), and it was only detected in strain S1-SC3 (Figure 5). Desmethylenylnocardamine (m/z 609.32 [M + Na] + ) (Figure 5, Figure 8S), Bisacuberin (401.24 Table 1: Te MIC of the selected actinobacterial crude extracts against methicillin-resistant Staphylococcus aureus (MRSA, PW01), Acinetobacter baumannii (PW01), and Klebsiella pneumoniae (PW01). No Strain code MRSA (PW01) A. baumannii (PW01) K. pneumonia (PW01) MIC (μg/mL) MIC (μg/mL) MIC (μg/mL) 1 S1-SC3 <9.9 <9.9 <9.9 2 1-5-22 <9.9 <9.9 <9.9 3 S2-SC16 <9.9 <9.9 <9.9 4 S5-SC5 156.25 312.5 39.6 5 1–3 <9.9 <9.9 <9.9 6 S4-SC11 625 312.5 625 7 S2-SC19 <9.9 <9.9 <9.9 8 S1-SC1 <9.9 <9.9 <9.9 9 2–27 78.125 156.25 39.6 10 AV2-5-14 39.6 78.12 78.12 11 RH1-5-14 <9.9 <9.9 <9.9 12 S2-SC10 39.6 39.6 39.6 P Colistin — 4 2 P Vancomycin 2 — — Note: Vancomycin and colistin were used as positive control. Te experiment was performed in triplicate (n�3). P �positive control. Abbreviation: ND, not detected. Table 2: Te MBC of the selected actinobacterial crude extracts against methicillin-resistant Staphylococcus aureus (MRSA, PW01), Acinetobacter baumannii (PW01), and Klebsiella pneumoniae (PW01). No Strain code MRSA (PW01) A. baumannii (PW01) K. pneumonia (PW01) MBC (μg/mL) MBC (μg/mL) MBC (μg/mL) 1 S1-SC3 1250 79.2 19.8 2 1-5-22 1250 39.6 312.5 3 S2-SC16 ND 78.12 78.12 4 S5-SC5 625 >1250 ND 5 1–3 ND 39.6 >1250 6 S4-SC11 ND ND ND 7 S2-SC19 1250 78.12 ND 8 S1-SC1 ND 78.12 78.12 9 2–27 ND 1250 ND 10 AV2-5-14 ND 625 ND 11 RH1-5-14 ND 1250 312.5 12 S2-SC10 ND 156.25 312.5 P Colistin — 8 4 P Vancomycin 4 — — Note: Vancomycin and colistin were used as positive control. Te experiment was performed in triplicate (n�3). P �positive control. Abbreviation: ND not detected. S1-SC3 S4-SC11 S5-SC5 Figure 2: Agar overlay assay of selected actinobacterial strains active against methicillin-resistant Staphylococcus aureus (PW01). 6Scientifca 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License S1-SC3 S4-SC11 S5-SC5 Figure 3: Agar overlay assay of selected actinobacterial strains active against Acinetobacter baumannii (PW01). Table 3: Taxonomic identifcation of selected actinobacterial strains using the 16S rRNA gene sequence analysis. No Strain Grown in ISP2 Identifcation % Accession no Location 1 S1-SC3 Streptomyces yogyakartensis NBRC 100777(T) 99.58 KP339493 Chachoengsao, (13°30′23″N 101°0′9″E), Rhizophora mucronata Poir. 2 S5-SC2 Streptomyces globisporus NBRC 12867 (T) 99.65 LC810198 Chonburi, (13°20′40″N 100°56′30″E), Avicennia alba 3 S5-SC5 Streptomyces albiaxialis NRRL B-24327(T) 99.22 KM678021 Chonburi, (13°20′40″N 100°56′30″E), Avicennia alba 4 S5-SC6 Streptomyces albiaxialis NRRL B-24327(T) 99.21 KM678022 Chonburi, (13°20′40″N 100°56′30″E), Avicennia alba 5 S7-SC9 Streptomyces albiaxialis NRRL B-24327(T) 99.22 KM678032 Chonburi, (13°20′35″N 100°56′35″E), mangrove sediment (no vegetation) Scientifca 7 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License [M + H] + ) (Figure 5, Figure 7S), deferoxamine (561.36 [M + 2H]2 + ) (Figure 5, Figure 10S), and ikarugamycin epoxide (m/z 495.29 [M + H] + ) (Figure 14S) were all identifed in the library search but not featured in the molecular network. Te detection of elaiophylin, kanchanamycin C, kanchanamycin D, and bisacuberin in strain S1-SC3 is particularly signifcant due to their documented activity against both Gram-positive and Gram-negative pathogens, including Staphylococcus aureus, MRSA, Escherichia coli, and vancomycin-resistant Enterococci. Teir presence in a mangrove-derived strain underscores a potentially untapped source of potent bioactive compounds, ofering promising opportunities for discovering novel antibiotics essential in the fght against AMR. 3.4. MicrobeMASST. GNPS library searches using MicrobeMASST exclusively identifed compounds produced by actinobacteria, primarily Streptomyces. Te generated phylogenetic tree clearly illustrates the hierarchical structure from which the annotated compounds originate. Te searches were conducted using the USI MS2 Table 3: Continued. No Strain Grown in ISP2 Identifcation % Accession no Location 6 S4-SC11 Streptomyces misionensis NBRC 13063(T) 99.86 KP339501 Chachoengsao, (13°30′11″N 101°0′5″E), Avicennia marina (Forssk) Vierh. 7 1-5-22 Streptomyces iranensis HM 35(T) 99.55 KM678004 Chachoengsao, (13°30′23″N 101°0′11″E), Avicennia alba 8 S2-SC10 Streptomyces iranensis HM 35(T) 99.58 KM678000 Chachoengsao, (13°30′23″N 101°0′11″E), Avicennia alba 9 S1-SC1 Streptomyces iranensis HM35(T) 99.23 KP339492 Chachoengsao, (13°30′23″N 101°0′9″E), Rhizophora mucronata Poir. 10 S6-SC2 Streptomyces sanyensis 99.85 KM678026 Chonburi, (13°20′38″N 100°56′32″E), Rhizophora mucronata Poir. 11 S2-SC2 Streptomyces diastaticus subsp. Ardesiacus NRRL B-1773(T) 99.64 KM677997 Chonburi, (13°20′40″N 100°56′30″E), Avicennia alba 8Scientifca 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License spectra deposited in the GNPS reference library, including desmethylenylnocardamine (CCMSLIB00004698381) (Figure 15S), desferrioxamine E (CCMSLIB00004695117) (Figure 16S), ferrioxamine E (CCMSLIB00005723618) (Figure 19S), desferrioxamine G (CCMSLIB00009918935) (Figure 18S), ikarugamycin epoxide (CCMSLIB00011906150) (Figure 17S), and deferoxamine (CCMSLIB00005435927) (Figure 20S). Results from the MicrobeMASST search clearly indicated that the annotated compounds were produced by known monoculture strains. Te number of MS2 spectra deposited in the GNPS database is visually represented in pie charts, where the blue section indicates a match with a monoculture, while the yellow section signifes that it was not merged. Streptomyces endocoffeicus CA3R110T (MN116545) S2-SC16 (KM678004) Streptomyces iranensis HM 35T (FJ472862) S1-SC1 (KP339492) S2-SC10 (KM678000) S1-SC3 (KP339493) Streptomyces yogyakartensis NBRC 100779T (AB249942) Streptomyces catenulae NRRL B-2342T (JODY01000075) Streptomyces angustmyceticus NRRL B-2347T (MUAY01000275) Streptomyces cacaoi NRRL B-1220T (MUBL01000215) Streptomyces albiaxialis NRRL B-24327T (AY999901) S5-SC5 (KM678021) S5-SC6 (KM678022) S7-SC9 (KM678032) Streptomyces lichenis LCR6-01T (LC360144) S2-SC2 (KM677997) Streptomyces ardesiacus NRRL B-1773 (DQ026631) Streptomyces salinarius SS06011T (LC430995) Streptomyces spinoverrucosus NBRC 14228T (AB184578) S4-SC11 (KP339501) Streptomyces misionensis DSM 40306T (FNTD01000004) Streptomyces malachitofuscus NBRC 13059T (AB184282) Streptomyces silaceus NRRL B-24166T (LIRJ01000287) S6-SC2 (KM678026) Streptomyces sanyensis 219820T (FJ261968) Streptomyces crystallinus NBRC 15401T (AB184652) Streptomyces bacillaris NBRC 13487T (AB184439) S5-SC2 (LC810198) Streptomyces globisporus NBRC 12867T (AB184203) Brevibacillus massiliensis phRT (JN837488) 64 86 98 95 66 99 62 88 96 100 81 99 97 81 67 75 75 100 98 87 99 86 0.02 Figure 4: Neighbor joining phylogenetic tree based on an almost complete 16S rRNA gene sequence of selected bioactive mangrove actinobacteria showing the relationships with their closely related type strains. Bootstrap support values (based on 1000 replicates), shown as percentages at the nodes, indicate the reliability of internal branches. Only values exceeding 50% are displayed. Te scale bar represents the number of nucleotide substitutions per site. Scientifca 9 6168, 2025, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1155/sci5/5510017 by Cochrane Czech Republic, Wiley Online Library on [01/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License