From Lebanese Soil to Antimicrobials: A Novel Streptomyces Species with Antimicrobial Potential

Abstract

The ongoing threat of antimicrobial-resistant pathogens has intensified the need for new antimicrobial agents, making the discovery of novel natural products crucial. This study focuses on the isolation and characterization of a novel Streptomyces species from the Anjar region in Lebanon, an area rich in microbial diversity that is largely unexplored for its biotechnological potential. Soil samples were collected and processed, leading to the isolation of Streptomyces strain ANJ10. Comprehensive morphological, physiological, and genomic analyses were conducted, including whole-genome sequencing (WGS) to identify biosynthetic gene clusters (BGCs) and broth microdilution (BMD) assays to evaluate antimicrobial activity. The ANJ10 genome revealed 42 BGCs, significantly more than the average number in Streptomyces species, suggesting a high potential for secondary metabolite production. Phylogenetic analysis confirmed ANJ10 as a novel species, and BMD assays demonstrated its strong antimicrobial activity against several gram-negative pathogens, specifically, Acinetobacter baumannii. These findings underscore the potential of this strain as a significant source of new antimicrobial compounds, reinforcing the importance of exploring underexploited environments like Lebanon for microbial bioprospecting.

1. Introduction

Despite significant advances in microbiology, the vast majority of bacterial species remain uncharacterized, with environmental microbiologists estimating that only around 2% can be cultivated in a controlled laboratory setting [1]. This limited culture capability restricts our understanding of microbial diversity and the potential applications of these microorganisms. Identifying and culturing environmental bacteria is crucial as it allows for the exploration of novel biochemical pathways and secondary metabolites, and plays a role in deepening our understanding of nutrient cycling, ecosystem functioning, and environmental sustainability [2,3]. The integration of genomics, metabolomics, and bioinformatics accelerates the identification and characterization of previously uncultured microorganisms and novel secondary metabolites, revealing the immense diversity and biotechnological potential of bacterial natural products [4,5].

However, pathogenic bacteria have increasingly developed antimicrobial resistance, posing a major public health challenge. The slow development of new antimicrobials lags behind the rapid emergence of resistant bacterial strains, creating a critical treatment gap [6]. In response to these challenges, there has been an increasing focus on natural sources, such as environmental microorganisms, for the discovery of novel bioactive compounds with therapeutic potential [7]. Environmental bacteria, which adapt to diverse habitats, from soil and water to extreme conditions, produce an abundance of secondary metabolites, making them promising targets for drug development [8,9].

Streptomycetes are Gram-positive bacteria characterized by significantly elevated guanine and cytosine (G + C) genomic content. They are classified under the family Streptomycetaceae in the order Actinomycetales [10]. These bacteria are frequently encountered in various environments, including marine and freshwater habitats, rhizosphere soil, compost, and vermicompost. Remarkably, Streptomycetes represent 50% of the total population of soil actinobacteria [11]. This genus is known to produce a variety of bioactive compounds, including antifungal, antibacterial, antiviral, and anticancer agents, as well as insecticides, herbicides, immunosuppressants, antioxidants, and enzyme inhibitors. They account for 39% of these secondary metabolites and have been extensively studied for their potential [8].

Notably, the majority of known antimicrobials are produced by Streptomyces species. Despite the extensive characterization of metabolites from this genus over the past century, genome sequencing initiatives have revealed that the chemical diversity identified using conventional culture-based methods represents only a fraction of the total potential of this genus. [12]. A notable number of cryptic BGCs responsible for the production of various metabolites remain undiscovered in Streptomyces genomes. This holds promise for the discovery of novel natural products that may lead to the development of next-generation antimicrobials [13]. The average genome size and BGC content in Streptomyces are 8.5 Mbp and 33 BGCs per genome, respectively, whereas the majority of groups display a broad spectrum of BGC abundance, varying from 20 to 45 BGCs per genome [14].

During investigations of soil samples collected from Anjar, Lebanon, bacterial isolation revealed the presence of a novel Streptomyces species isolated from desiccated soil samples. This strain exhibited a higher-than-average BGC count and produced secondary metabolites with antimicrobial activity. This successful cultivation of the previously undiscovered strain highlights the diverse microbial population present in Lebanese ecosystems and its potential for novel bacterial discovery.

1.1. Sample Processing and Bacterial Isolation

1.1.1. Sample Collection

Soil samples were collected from Anjar, Lebanon (33°43′33″ N, 35°55′47″ E) in sterile containers and transported to the Bacteriology and Molecular Microbiology Laboratory at the American University of Beirut, Lebanon, for analysis. Details regarding the isolated environmental bacterium, including its origin, order of isolation, and target pathogens, are provided in Supplementary Table S1.

1.1.2. Sample Processing and Bacterial Isolation

Sample processing was performed as described by Awada et al. [15]. Briefly, soil samples were dehydrated, dissolved in water, and heated to enrich for spore-forming microorganisms. The soil suspensions were then diluted and inoculated on soil (30 g dried soil sample, 18 g bacteriological agar, 10 g corn starch in 1 L distilled water) and ISP3 (20 g oats, 18 g bacteriological agar, 2.5 mL ISP3 trace elements—each 1 mL trace salts solution contains 0.1 g FeSO₄ × 7H₂O + MnCl₂ × 4H₂O + ZnSO₄ × 7H₂O and 100 mL dH₂O-, in 1 L of distilled water, pH = 7.8) agars. After a 14-day incubation period, the formed colonies were sub-cultured, isolated, purified, and banked for further manipulation (Supplementary Figure S1). The name ANJ10 was derived from the name of the Lebanese region (Anjar) from which the 10th isolate was obtained.

1.2. Morphological, Biochemical, and Physiological Characterization

The shape and color of the bacteria were observed on ISP2 (10 g malt extract, 4 g yeast extract, 4 g glucose, 15 g bacteriological agar, in 1 L distilled water) and ISP3. Gram staining was performed to phenotypically classify the isolates. Furthermore, the optimal conditions for growth were first evaluated for Sodium Chloride (NaCl) resistance by inoculating on agar 5339 (10 g casein peptone, 5 g yeast extract, 20 g agar, in 1 L distilled water, pH = 7) with varying NaCl concentrations (0, 2.5, 5, 7.5, and 10%). In addition, a pH tolerance test was performed by inoculating ISP2 agar at different pH levels (3, 4, 5, 6, 7, 8, 9, and 10). For biochemical and physiological properties, API 20 E was employed according to the manufacturer’s instructions (BioMérieux, Lyon, France).

1.3. Scanning Electron Microscopy (SEM)

SEM was employed to examine the detailed morphology of ANJ10. In summary, overnight bacterial cultures were centrifuged at 5000× g for 2 min at 4 °C. After discarding the supernatant, the pellet was washed with 1X PBS and centrifuged again at 6000× g for 2 min at 4 °C. The resulting pellet was resuspended in 50 μL of 2% formaldehyde (FA). A 10 μL portion of the FA/bacterial mixture was placed on a carbon adhesive tab affixed to an aluminum specimen mount. The samples were incubated at room temperature for 25 min for primary fixation, washed with 10 μL of 1X PBS, and treated with 2.5% glutaraldehyde (GA). After another 25 min of incubation, the samples were washed with 20 μL of autoclaved distilled water. Once dry, the fixed samples were coated with a 5 nm layer of gold and observed using SEM (MIRA3 LMU with OXFORD EDX detector).

1.4. Genomic Characterization

1.4.1. DNA Extraction and WGS

Bacterial strains were cultivated in TSB broth, after which the cultures were centrifuged at 4000 rpm and 4 °C for 5 min to pellet the cells. The supernatant was discarded, and the pellet was resuspended in 200 µL PBS. Following the manufacturer’s instructions, DNA was extracted and purified to achieve ultra-pure DNA using the Zymo Research Quick-DNA Fungal/Bacterial Miniprep Kit and the Zymo DNA Clean & Concentrator^®-5 kit, respectively. The obtained gDNA from the extraction and purification processes was assessed for both purity and yield using a Nanodrop spectrophotometer. gDNA was used for library preparation, whereas for short-read sequencing, the Illumina DNA Prep kit was used according to the manufacturer’s instructions with 500 ng of gDNA for library preparation, and the prepared libraries were then sequenced using the MiSeq Reagent Kit v2 (500-cycles) on a MiSeq device over 36 h. For long-read sequencing, library preparation was performed using the Rapid Barcoding Kit V14 from Oxford Nanopore Technologies, following the manufacturer’s instructions, with 50 ng of gDNA as input. Sequencing was performed on an MK1B device, a rapid barcoding 96 v14 flow cell, with data acquisition and base calling conducted in real time over 72 h. For assembly and annotation, the FASTQ files, both short and long reads (which were concatenated into one file in advance), were processed through the nf-core/bacass pipeline version 2.1.0 [16], where the hybrid assembly step used Unicycler, specifying the assembly type as hybrid in the pipeline parameters, and BUSCO [17] was used to assess the genome completeness. A genomic map was drawn using the DNAPlotter function in Artemis version 18.2.0 [18].

1.4.2. Phylogenetic Classification

Two methods were employed for the taxonomic classification of Streptomyces. The first method used the Saffrontree tool [19] for phylogenetic analysis based on whole-genome sequencing data, comparing 602 Streptomyces reference genomes in the NCBI database, and performing Average Nucleotide Identity (ANI) calculations using pyANI [20] and DNA-DNA hybridization using the GGDC tool [21]. The second method involved the use of Type Strain Genome Server (TYGS), accessed at https://tygs.dsmz.de, accessed on 22 June 2024, for comprehensive taxonomic analysis. The TYGS uses the MASH algorithm to determine closely related type strains based on genome similarity. Additionally, 16S rDNA sequences extracted from user genomes using RNAmmer were BLASTed against a database of 21,278 type strains to refine taxonomic distances using Genome BLAST Distance Phylogeny (GBDP). Phylogenomic inference was conducted via pairwise genome comparisons using GBDP, with branch support inferred through FASTME 2.1.6.1, and rooted midpoint trees visualized using PhyD3. Type-based species clustering utilized a 70% dDDH radius around 18 type strains, with subspecies clustering employing a 79% dDDH threshold [21,22,23,24,25,26,27,28,29,30]. All trees were visualized using MEGA software v11.0.13.

1.4.3. Functional Annotation

Biosynthetic gene cluster (BGC) identification was performed using the Unicycler assembly FASTA file as an input for the antiSMASH software [31]. All available search features in antiSMASH were enabled to analyze genomic data and identify potential BGCs. Additionally resistance markers and potential antimicrobial targets were screened using the ARTS web server [32]. For BGC networking, BiG-SCAPE [33] was used to analyze the diversity of BGCs in our sample dataset. The ‘mix’ option was applied, combining all BGC classes into a single network file for comprehensive analysis. BiG-SCAPE constructed sequence similarity networks among the BGCs with a 0.75 cut-off, and the files were visualized using Cytoscape v3.10.1. Furthermore, prokaryotic protein sequences were classified into Cluster of Orthologous Genes (COG) functional categories using COGClassifier [34].

1.5. Small-Scale Secondary Metabolite Production and Extraction

The first seed was prepared by removing multiple colonies, spores, or a sizable portion of ANJ10 mycelia cultured on ISP3 agar and inoculating them into 5 mL of ISP3 broth (ISP3 medium without the addition of bacteriological agar). This was then incubated at 28 °C and 130 rpm for 48 h, and 1 mL was transferred into 10 mL of ISP3 broth to constitute the second seed. Subsequently, 1 mL of the second seed was used to inoculate 50 mL of each of the 14 different production media (Supplementary Table S2). The cultures were then fermented for 7 days to allow the isolates to produce secondary metabolites (SMs). Each of the 14 production media offered a unique combination of stimuli that activated specific cryptic pathways encoded in the bacterial genomes. Thus, exposing the same bacterium to different conditions enables it to synthesize an inimitable assortment of compounds in each medium.

Following this, SMs were extracted from small-scale bacterial cultures by adding 1 mL of Amberlite XAD 16N resins to each culture (Supplementary Figure S2). The resins were incubated with the bacterial suspension for 4 h on a shaking platform at 130 rpm to allow the SMs to adsorb onto them. Afterward, the resins and cell masses were allowed to precipitate at the bottom of the flasks before the supernatant (media) was discarded. Consequently, the SMs were extracted from the resins by adding a mixture of organic solvents (30 mL of acetone and 10 mL of methanol) to the pellet of resins and cell mass. The SMs were then dried using a rotary evaporator before being dissolved in Dimethyl Sulfoxide (DMSO) to prepare 10 mg/mL stocks of crude extracts, which were stored at −20 °C until further use.

1.6. Antibacterial Bioactivity Screening

1.6.1. Bacterial Strains

Both Gram-positive and Gram-negative ESKAPE pathogens were used to screen the crude extracts for antibacterial activity. The Gram-positive microorganisms encompassed three strains of Staphylococcus aureus (Methicillin-sensitive S. aureus (MSSA) strains, S. aureus ATCC 29213 and S. aureus Newman, and Methicillin-resistant S. aureus (MRSA) strain S. aureus N315) as well as Vancomycin-sensitive Enterococcus faecalis strain (E. faecalis ATCC 19433). In contrast, the Gram-negative bacteria comprised one Escherichia coli strain (E. coli ATCC 25922), two Klebsiella pneumoniae strains (K. pneumoniae DSM and K. pneumoniae ATCC 13883), one Acinetobacter baumannii strain (A. baumannii DSM 30008), and two Pseudomonas aeruginosa strains (P. aeruginosa mexAB and P. aeruginosa ATCC 27853).

1.6.2. Broth Microdilution (BMD) Assay

To evaluate the antibacterial activity of the crude extracts, a Broth Microdilution (BMD) assay was performed against the ESKAPE pathogens. In a 96-well plate, columns 2 to 12 were filled with 100 μL of Mueller Hinton Cation-Adjusted Broth (MHCAB), while column 1 received 195 μL of MHCAB plus 5 μL of the crude extracts. A two-fold serial dilution was performed from columns 1 to 11, creating a concentration gradient of 250 to 0.24 µg/mL. Column 12 served as the positive (PC) and negative (NC) controls. Each crude extract was tested in duplicate rows (Supplementary Figure S3).

A bacterial suspension with an optical density of 0.5 McF (10⁸ CFU/mL) was prepared from overnight cultures. This was diluted to 5 × 10⁶ CFU/mL and then to 5 × 10⁵ CFU/mL. Next, 10 μL of this final dilution was added to columns 1–11 and PC wells, while NC wells received no bacteria. The plates were incubated overnight at 37 °C and 160 rpm.

Bacterial growth inhibition was visually assessed, and optical density (OD) measurements were normalized to the NC and plotted using GraphPad Prism v10.5.0. The Minimum Inhibitory Concentration (MIC) was defined as the lowest concentration that showed visual growth inhibition.

2. Results

2.1. Morphological, Physiological, and Biochemical Characterization

2.1.1. Morphology

Scan Electron Microscopy of ANJ10 presented dense aerial mycelia and long chains of spore formation (Figure 1).

On ISP3 agar, ANJ10 appeared as spore-forming, circular, raised, white colonies with a slight pink tint. (Figure 2A,B).

2.1.2. Gram Staining

Gram-positive, filamentous.

2.1.3. Salt Tolerance

ANJ10 grew only at 0% NaCl concentration (Figure 2C).

2.1.4. pH Tolerance

ANJ10 grew at pH levels 6 and 7 (Figure 2C).

2.1.5. Biochemical Properties

ONPG and PNPG positive: β-galactosidase positive; ANJ10 is a lactose fermenter. (Figure 2D).

2.2. Genomic Characterization

2.2.1. Genome Features

The complete genome of ANJ10 is 9,939,599 base pairs (bp) in length, with a GC content of 70.68%. Genome annotation revealed 8670 coding sequences (CDS), 18 ribosomal RNA (rRNA) genes, 87 transfer RNA (tRNA) genes, and 1 transfer-messenger RNA (tmRNA) (Figure 3). BUSCO assessment showed a completeness of 99.8% (Supplementary Figure S4).

2.2.2. Phylogenetic Classification

The Saffrontree phylogenetic tree construction based on ANJ10 WGS data and comparison with all reference Streptomyces species demonstrated similarities to several Streptomyces species, including S. bicolor, S. caeruleatus, S. nigra, S. ceaneus, S. cupreus, S. chromofuscus, and S. muensis. Tree construction using these genomes showed that ANJ10 was most closely related to S. caeruleatus and S. muensis (Figure 4a). The ANI results showed that none of the comparisons exceeded the 95% threshold, which is commonly used to define species boundaries [35], and less than 70% DNA–DNA hybridization (dDDH) in all formulas and compared to all references (Figure 4b, Supplementary Table S3). As for the TYGS results, the tree inferred with FastME 2.1.6.1 from GBDP distances calculated from 16S rDNA gene sequences showed similarity to S. qaidamensis and S. cahuitamycinicus, whereas WGS showed the highest similarity to S. curaco. dDDH had the highest value of 51.1% using formula 1 when compared to S. caeruleatus, lower than the 70% threshold (Figure 5). In summary, these results indicate that ANJ10 represents a novel Streptomyces species.

2.2.3. Functional Annotation

antiSMASH analysis revealed a total of 44 BGCs, among which 11 exhibited over 75% similarity to known compounds. Notably, three of the BGCs were positioned at the contig edges, rendering them incomplete. Further examination revealed that the last three Type I polyketide synthase (T1PKS) clusters, with the latter two situated at the beginning of their respective contigs, were identical BGCs spanning three contigs. Consequently, the total number of discernible BGCs was adjusted to 42. The distribution of BGC types was as follows: Terpene—13, Nonribosomal Peptide Synthetase (NRPS)—12, Polyketide Synthase (PKS)—14, Ribosomally synthesized and post-translationally modified Peptides (RiPPs)—5, Siderophore—5, Lactone—4, Lanthipeptide—3, Melanin, Ectoine, Arylpolyene, β-lactam, and hydrogen cyanide. Additionally, three BGCs showed proximity to resistance markers. Specifically, ANJ10’s second BGC contained a carboxyl transferase domain, BGC 15 included OTCace and Asp/Orn binding domains, and BGC 36 was associated with a biotin/lipoyl attachment domain according to the ARTS results (

Table 1. ANJ10 BGC annotation. BGCs were annotated using antiSMASH. This table details each BGC found, its type, location, and the most similar known cluster, along with its type, degree of similarity, and known activity. Each colored region represents a different type of BGC; red represents BGCs on a contig edge, and green represents clusters with more than 75% similarity to known BGCs.

Region	Type	From	To	Most Similar Known Cluster	Type	Similarity
Region 1.1	lanthipeptide-class-i	270,498	296,733
Region 1.2	NRPS, NRPS-like, arylpolyene	320,092	418,525	o-dialkylbenzene 1/o-dialkylbenzene 2	Polyketide+NRP	96%
Region 1.3	T2PKS	443,846	516,361	spore pigment	Polyketide	75%
Region 1.4	NRPS	537,820	594,302	arginomycin	Other	20%
Region 1.5	terpene	662,834	683,847	albaflavenone	Terpene	100%
Region 1.6	CDPS	1,675,437	1,696,183	nocardiopsistin A/nocardiopsistin B/nocardiopsistin C	Polyketide	9%
Region 1.7	furan	1,848,929	1,869,942	methylenomycin A	Other	9%
Region 1.8	butyrolactone	1,891,210	1,902,202	triacsin C	Other	6%
Region 1.9	blactam	2,025,385	2,046,998	clavulanic acid	Other:Non-NRP beta-lactam	16%
Region 1.10	NI-siderophore	3,395,933	3,425,705	desferrioxamin B/desferrioxamine E	Other	100%
Region 1.11	melanin	3,522,101	3,532,601	istamycin	Saccharide	4%
Region 1.12	ectoine	4,844,671	4,855,075	ectoine	Other	100%
Region 1.13	NAPAA	5,081,439	5,115,026	ε-Poly-L-lysine	NRP	100%
Region 1.14	NI-siderophore	5,302,674	5,332,887	kinamycin	Polyketide	16%
Region 1.15	betalactone	5,567,365	5,593,487	JBIR-34/JBIR-35	NRP	8%
Region 1.16	RiPP-like	5,681,751	5,693,103
Region 1.17	butyrolactone, terpene	5,768,985	5,792,627	γ-butyrolactone	Other	100%
Region 1.18	terpene	5,918,195	5,939,997	rubiginone A2/rubiginone J/rubiginone K/rubiginone L/rubiginone M/rubiginone N/ochromycinone/rubiginone B2	Polyketide	20%
Region 1.19	NI-siderophore	6,035,520	6,066,813	paulomycin	Other	13%
Region 1.20	lassopeptide	6,088,809	6,111,354	citrulassin D	RiPP	100%
Region 2.1	RiPP-like	116,451	128,376
Region 2.2	terpene	187,177	208,133
Region 2.3	NRPS, T1PKS	339,857	390,604	Sch-47554/Sch-47555	Polyketide	3%
Region 2.4	NI-siderophore	424,258	456,845	peucechelin	NRP	30%
Region 2.5	lanthipeptide-class-iii, RiPP-like	467,702	494,891	informatipeptin	RiPP:Lanthipeptide	100%
Region 2.6	terpene	527,615	548,646	cyphomycin	Polyketide	2%
Region 2.7	T1PKS, NRPS-like, NRPS	626,113	713,163	antimycin	NRP+Polyketide	93%
Region 2.8	NRP-metallophore, NRPS	840,099	907,141	cahuitamycin A/cahuitamycin B/cahuitamycin C	NRP	62%
Region 2.9	NRPS-like	997,843	1,040,518	deoxyhangtaimycin	Polyketide+NRP	11%
Region 2.10	T1PKS	1,080,440	1,125,278	herbimycin A	Polyketide	30%
Region 2.11	linaridin, lanthipeptide-class-iv	1,466,740	1,516,503	Sch-47554/Sch-47555	Polyketide	3%
Region 3.1	terpene	12,267	33,244	rimomycin A/rimomycin B/rimomycin C	NRP	6%
Region 3.2	terpene, T1PKS	130,006	180,149	malacidin A/malacidin B	NRP:Lipopeptide:Ca+-dependent lipopeptide	5%
Region 3.3	T1PKS, NRPS	181,637	269,950	foxicin A/foxicin B/foxicin C/foxicin	NRP+Polyketide	14%
Region 3.4	terpene	331,138	352,196	ebelactone	Polyketide	5%
Region 3.5	hydrogen-cyanide, betalactone, NRPS, T1PKS	739,801	807,911	rakicidin A/rakicidin B	NRP:Cyclic depsipeptide+Polyketide:Modular type I polyketide	20%
Region 3.6	T1PKS	1,001,424	1,032,706	niphimycins C-E	Polyketide	29%
Region 4.1	PKS-like	40,613	81,626	sanglifehrin A	NRP+Polyketide	6%
Region 4.2	terpene, PKS-like	118,451	167,319	sanglifehrin A	NRP+Polyketide	4%
Region 4.3	terpene	182,354	209,122	hopene	Terpene	92%
Region 4.4	NRPS, T1PKS	512,984	576,593	althiomycin	NRP+Polyketide:Modular type I polyketide	100%
Region 4.5	T1PKS	760,445	800,778	niphimycins C-E	Polyketide	35%
Region 5.1	T1PKS	1	20,202	griseochelin	Polyketide	46%
Region 6.1	T1PKS	1	14,357	ECO-0501	Polyketide	14%

, Figure 6). BGC network analysis revealed that while some regions were networked with BGCs from the miBIG repository, 28 regions showed no genomic similarities to known BGCs, highlighting the potential for novel secondary metabolite discovery (Figure 6, Supplementary Table S4). COG analysis revealed a diverse distribution of functional genes, highlighting significant clusters in transcription (K), carbohydrate metabolism (G), and amino acid metabolism (E). Notably, secondary metabolite biosynthesis, transport, and catabolism (Q) featured prominently, with 267 genes, suggesting a robust potential for secondary metabolite production. Additional notable categories included cell wall biogenesis (M), protein modification and turnover (O), and ion transport (P), underscoring the metabolic versatility of the organism and its potential for ecological interactions through secondary metabolites (Figure 7).

2.3. Antimicrobial Activity Testing

The antimicrobial potential of ANJ10 crude extracts produced in 14 different media was assessed in small-scale production against known ESKAPE pathogens. Based on this, the antimicrobial activity was evaluated. Most of the tested crude extracts showed relatively low activity against a panel of ESKAPE pathogens. However, ANJ10’s crude extract produced in Media V demonstrated visual inhibition against five pathogens, specifically E. coli ATCC 25922 and A. baumannii DSM 30008, with the lowest MIC values (

Table 2. Broth Microdilution (BMD) Assay Results for ANJ10. Pathogenic strains were tested using crude extracts from different media. The values, expressed in µg/mL, indicate the MIC (minimum inhibitory concentration), defined as the lowest concentration that shows growth inhibition. (-) represents MIC > 250 µg/mL.

Name of Producing Strain	Media
Bacteria	V	Veg	A	B	C	INA	RA3	GPMY	V6	AF/MS	GYM	M8	COM	NL2
S. aureus ATCC 29213	-	-	-	-	250	-	-	250	-	-	-	-	-	-
S. aureus Newman	125	125	125	125	-	-	-	-	-	-	-	250	-	-
S. aureus N315	-	-	-	-	250	-	-	-	-	-	-	-	-	-
E. feacalis ATCC 19433	-	-	-	-	-	-	-	-	125	-	-	-	-	-
K. pneumonaie DSM	-	-	-	-	250	-	-	-	-	-	250	-	-	-
A. baumannii DSM 30008	125	250	250	250	62.5	250	250	250	125	250	250	250	250	125
K. pneumonaie ATCC 13883	-	-	-	-	-	-	-	-	-	-	-	-	-	-
P. aeruginosa ATCC 27853	250	-	-	-	250	-	-	-	-	250	250	250	250	250
P. aeruginosa mexAB	250	-	250	-	-	-	-	-	250	250	250	125	250	250
E. coli ATCC 25922	62.5	125	62.5	250	-	-	-	-	-	125	-	-	-	-

). Based on these results, we conducted large-scale production in medium V and tested it against A. baumannii DSM 30008. For a better assessment, we used OD measurements to assess the turbidity of the media, reflecting bacterial growth. The results showed a significant reduction in OD across all tested concentrations, highlighting the antimicrobial activity of ANJ10 crude extract (Figure 8).

3. Discussion

The genus Streptomyces plays a critical role in natural product drug discovery, particularly due to its extensive repertoire of biosynthetic gene clusters (BGCs) [36]. The novel Streptomyces species isolated from Anjar, Lebanon, stands out in this regard, displaying a higher-than-average number of BGCs compared to typical Streptomyces genomes, which generally harbor 33 BGCs per genome [14]. This highlights the strain’s strong potential to produce a diverse array of secondary metabolites, including therapeutically valuable compounds such as cyclosporine, a crucial immunosuppressant in organ transplantation and autoimmune disease treatment [37], and rapamycin, which has applications in immunosuppression and cancer therapy [38].

Phylogenetic analysis not only revealed significant divergence from known Streptomyces species but also confirmed that the strain represents a novel species. This is supported by the identification of numerous unique genes within its biosynthetic gene clusters, with 28 failing to cluster confidently with any entries in the miBiG database, indicating that these loci likely encode previously uncharacterized biosynthetic pathways [33]. These poorly clustered regions vary widely in type and genomic length and have less than 5% similarity to known BGCs. For example, short clusters such as Region 1.16, classified as a RiPP-like biosynthetic gene cluster and spanning approximately 11.4 kilobases, and Region 2.1, another RiPP-like cluster of similar size, are typically associated with a range of bioactivities [39]. Other regions are larger and more complex, such as Region 4.2, a hybrid terpene and PKS-like cluster approximately 48.9 kb in length, and Region 2.2, a terpene cluster spanning approximately 20.9 kb. Several clusters also fall into high-interest classes, such as NRPS, PKS, and lanthipeptides, including Region 1.1 and Region 2.3, enzyme systems often responsible for the biosynthesis of bioactive natural products, such as antibiotics, cytotoxins, and immunosuppressants [40]. The structural and enzymatic diversity observed among these BGCs, combined with their failure to form strong clustering with any known reference pathways, strongly suggests that they may direct the biosynthesis of entirely novel chemical scaffolds.

In addition to these unclustered regions, several BGCs exhibited low similarity to known clusters. For instance, Region 1.9 showed 16% similarity to the clavulanic acid biosynthetic cluster, Region 1.18 shared 20% similarity with the rubiginone cluster, and Region 3.5 shared 20% similarity with the rakicidin biosynthetic pathway. These cases may represent cryptic or divergent pathways, where limited domain-level similarity is insufficient to support confident clustering, but may hint at the production of structurally or functionally related analogs.

In contrast, the genome also harbors several biosynthetic gene clusters that are one hundred percent identical to well-characterized reference pathways. These include those responsible for the production of albaflavenone, ectoine, gamma-butyrolactone, desferrioxamine, althiomycin, ε-poly-L-lysine, informatipeptin, and citrulassin D. Their presence supports the accuracy and robustness of the genome mining approach, while also demonstrating the strain’s capacity to produce well-established bioactive compounds with known functions, such as antibacterial activity, metal chelation, or cytoprotection [41,42,43,44,45]. Altogether, this dual landscape of known and unclustered or low-similarity BGCs underscores both the evolutionary novelty and biosynthetic richness of this strain and highlights the value of genome mining for the discovery of natural products.

The ecological significance of Streptomyces is immense. As prolific producers of secondary metabolites, these bacteria play vital roles in soil ecosystems, influencing microbial community dynamics [46]. The discovery of unique genes with ANJ10 is not entirely unexpected, given Lebanon’s rich and varied ecosystem. Such ecological diversity fosters unique microbial niches and evolutionary pressures, providing fertile ground for the emergence of novel microbial species with specialized metabolic capabilities, as shown by Awada et al. [47].

Given the novelty of the isolated Streptomyces species, we evaluated its antimicrobial potential. The urgent need for new antibiotics, particularly against ESKAPE pathogens, which are major contributors to antimicrobial resistance (AMR), further motivated this investigation [6]. To assess bioactivity, the strain was cultured in 14 different production media, each offering distinct nutritional conditions and stressors known to influence the activation of specific biosynthetic pathways [48]. Notably, variations in antimicrobial activity were observed across different media, underscoring the importance of environmental factors in modulating secondary metabolite expression.

Among the tested media, Medium V exhibited the broadest and most potent antimicrobial activity. Consequently, the crude extract was selected for further testing against Acinetobacter baumannii, a clinically relevant ESKAPE pathogen. Remarkably, significant bacterial inhibition was observed even at low extract concentrations. This sustained activity at reduced concentrations may be attributed to the complex nature of the crude extract, which likely contains a mixture of secondary metabolites that act synergistically or exhibit overlapping antimicrobial spectra at varying MICs.

Future work will focus on the purification and characterization of individual bioactive compounds in this extract. This may uncover novel antimicrobial agents with the potential for development into clinically applicable therapeutics, an essential step in combating the escalating challenge of multidrug-resistant pathogens.

4. Conclusions

In conclusion, Lebanon’s geographical location and diverse ecosystems make it a crucial area for exploring microbial diversity. The discovery of this new Streptomyces species not only adds to the growing repository of bioactive compounds but also reinforces the potential of Lebanon as a significant source of microorganisms with promising applications in drug discovery. The high number of BGCs identified in this strain suggests vast, unexplored chemical diversity that could lead to the development of next-generation antimicrobials and other therapeutic agents. Moreover, the isolation and characterization of this novel Streptomyces species from Anjar, Lebanon, highlights the pivotal role of this genus in natural product drug discovery and underscores the ecological and biotechnological significance of exploring diverse environments. The unique genetic and biochemical properties of this strain position it as a valuable candidate for further research, particularly in the development of new antimicrobial drugs.