IntroductionAll living organisms undergo cellular processes to maintain a healthy life. These cellular processes are categorized into primary and secondary metabolism, and their difference lies in their biological effects1. Primary metabolites, including nucleotides, carbohydrates, and amino acids, are vital for growth, cellular maintenance, and the development of microorganisms. The secondary metabolites, also known as natural products (NPs), are not directly involved in growth or reproduction and the above-mentioned basic cellular functions. They play a chief role in ecological interactions, such as communication, defense mechanisms, and competition with other organisms2. Studies have revealed that more than 300,000 natural products are derived from diverse biological sources, such as marine organisms, plants, and microorganisms. These bioactive compounds have revolutionized the therapeutic industry, with approximately 50% of all marketed drugs originating from natural products. The remarkable structural diversity and therapeutic potential of NPs serve as a foundation for developing novel immunosuppressants, antineoplastic, and antibiotic agents3,4,5.The historic discovery of the natural product penicillin, derived from Penicillium notatum, a filamentous fungus, by Sir Alexander Fleming in 1929, defined the therapeutic use of this compound in the 1940s. This event marked the onset of the usage of microorganisms instead of plants as vital sources of natural therapeutic products6,7. Microorganisms are a significant source of structurally diverse bioactive metabolites that have yielded some predominant products for the pharmaceutical industry. Among the microbiota, bacteria have proven to be the most extensive microbial producers of bioactive natural products. They are considered living bio-factories due to their versatile biocatalytic activity, allowing them to interact with various substrates and undergo rapid evolutionary change8,9.Novel natural therapeutic products can be obtained by applying advanced applications, such as genetic engineering of microorganisms, animal models, genome sequencing, and high-throughput analysis (Fig. 1)10,11. NPs like antibiotics, such as penicillin (from Penicillium notatum and Penicillium chrysogenum), cephalosporins (from Cephalosporium acremonium), aminoglycosides (from Streptomyces griseus and Micromonospora purpurea), tetracyclines (from Streptomyces aureofaciens and Streptomyces rimosus), and other polyketides of many structural types have their different modes of action12,13,14. This is due to the difference in chemical and biological properties of the microorganisms from which they are derived, allowing them to act differently on pathogens. NPs such as immunosuppressive agents, cholesterol-lowering agents, anti-helminthic agents, antidiabetic agents, antineoplastic agents, etc., also act as per their source microorganisms15,16.Fig. 1Schematic Representation of the production and processing of NPs.Full size imageBacteria exhibit a method for exchanging genetic information, enabling them to modify chemical production for various applications. It is mainly due to a group of co-localized genes known as biosynthetic gene clusters (BGCs). BGCs perform their functions by encoding ‘core biosynthetic and tailoring enzymes’ and providing resistance to ‘small molecular compounds’. The genetic packages coded by BGCs, also known as “Selfish Operons”, are highly evolved for horizontal gene transfer17. They are considered independent evolutionary entities due to their mobile genetic elements. This exchange of genetic elements is highly favored among closely related strains due to the mechanism of DNA mismatch, repair, and maintenance. These genomic clusters mainly work via two major biosynthetic pathways: Polyketide Synthases (PKSs), type 1 and type 2, and Non-Ribosomal Peptide Synthases (NRPSs)18,19. PKS and NRPS are renowned targets in genome mining for producing natural therapeutic products. PKSs have a large multifunctional enzyme that acts successively in an assembly line fashion by adding acyl units onto the growing polyketide chain20. Consequently, non-ribosomal peptide synthetases function by adding an extended unit of amino acids. They perform post-translational modifications of ribosome-synthesized precursors. Numerous prominent peptide-derived metabolites, such as penicillin, cephalosporin, glycopeptide, and cyclosporin, are assembled in both bacteria and fungi by the NRPS21,22.Different investigations have shown that bacteria constitute several ‘Orphan BGCs’, which do not encode for natural products. ‘Genome Mining’ has enabled easier isolation and taxonomical analysis for myriad compounds. However, most of these compounds are not linked to their respective BGCs. It is difficult to decipher the number of ‘Orphan Clusters’ that encode for novel or known compounds whose biosynthetic machinery has not been identified yet23,24. The current study exhibits the isolation, identification, and analysis of four novel bacterial isolates: Klebsiella pneumoniae, Klebsiella quasi-pneumoniae, Streptomyces minutiscleroticus, and Streptomyces peucetius. It highlights their antagonistic activity and potential to produce natural therapeutic products by studying the optimization of media conditions and establishing a statistical and neural network regression model. Further research could lead to the development of novel medications that can contribute to expanding the understanding of microbial biochemistry and pave the way for the progress of innovative pharmaceuticals that could play a crucial role in addressing current challenges in healthcare and transforming the landscape of natural therapeutic products.Materials and methodsSample collectionThe bacterial samples were collected from agricultural fields near the Ranga Reddy district, Telangana, India (“17.3891 N 77.8367 E”). The sampling site was rich in flora and consisted of diverse agricultural plant species. A soil probe or trowel was utilized to collect the rhizosphere soil samples at varying depths. Subsequently, numerous soil sub-samples were prepared, added to a larger container, and mixed thoroughly to make a homogenous mixture. After mixing, a small amount (~ 300 mg) of the prepared homogenous mixture was added to 50 mL sterilized, self-sealed, and labeled Falcon tubes. The sterilized Falcon tubes were initially kept at ambient temperature and then at 4 °C. The temperature was maintained until the next step of analysis25,26.Isolation of the microbial consortiaAfter field sampling, the collected bacterial consortia were isolated, 90 mL of peptone saline solution (0.1% peptone (w/v), 0.85% NaCl) and 10 g of the homogenized soil sample were suspended, incubated in an orbital shaker for 1 h at 30 °C at 150 rpm, and then allowed to stand for 30 min. After incubation, 1mL of the aliquot was taken and added to 99 mL of nutrient broth (g/L): 5U supplemented with 5 U of peptone, 1 U of beef/yeast extract, 15 U of agar, 5 U of NaCl and distilled water (HiMedia, India). 4 U of nystatin antifungal agent was added to prevent fungal growth and the solution was then re-incubated for 3–4 days at 30 °C at 150 rpm. After incubation, suspensions were serially diluted (10−1 to 10−8). 100 µL from each dilution was spread plated onto the nutrient agar plates using a L-shaped sterilized spreader. The plates were re-incubated at 30 °C for 48 h. Distinct bacterial colonies were chosen and subjected to subculturing in fresh nutrient media. Pure cultures were stored at 4 °C. The concentration of the bacterial consortia was obtained using a UV/Vis spectrophotometer (Optical Density (OD) at A600) (Thermo Fisher Scientific)6,27,28.Standardization and preparation of the inoculum to produce NPsFor the standardization procedure, a 0.5 McFarland solution was prepared by mixing 99.5 mL of 0.18 mol/L (1% v/v) of sulfuric acid (H2SO4) and 0.5 mL of 0.048 mol/L (1.1750% w/v) of dehydrated barium chloride (BaCl2) solution. Subsequently, the turbidity of the standardized solution was calculated in different test tubes. The absorbance of 0.5 McFarland solution was computed at OD – 600 nm (A600) (0.8–1.0) (Thermo Fisher Scientific). To prevent evaporation and concentration loss due to light, the standardized solution was kept in an airtight container at room temperature (RT). Before comparing the bacterial suspension, the turbidity standard tube was thoroughly mixed using a vortex to obtain a consistent turbid appearance. After overnight incubation, a 5 mL (0.5 McFarland) bacterial culture was suspended in a nutrient broth and incubated for 4 h at 37 °C. The turbidity was regulated by employing a sterile cotton swab. The inoculum was distributed uniformly in the entire agar medium by swirling the plate at an angle of 60°28,29.Screening of the bacterial isolates to produce NPsPrimary screeningThe production of NPs was assessed by determining the potential antagonistic activity of the selected isolates. The primary screening was conducted against the test bacterial strains by employing a transverse pattern on nutrient agar plates. The selected bacterial strains were streaked horizontally and incubated for 24–36 h at 30 °C. After incubation, the test microorganisms (Escherichia coli (MTCC 739) and Bacillus subtilis (MTCC 121)) were streaked perpendicularly (at 90 °) to the screened isolates. The plates were re-incubated for 24–48 h at 30 °C. The antagonistic activity was determined by observing the inhibitory or lytic activity at the intersecting regions. The bacterial isolates that gave affirmative results were selected for secondary screening to validate their bioactivity. All the experiments were conducted in triplicate. Their outcomes were assessed in the form of mean ± standard error mean (SEM)30,31.Seed overlay method/crowd plate techniqueThe bacterial isolates displaying antagonistic activity in primary screening were subjected to the seed overlay assay. The isolates were spot-inoculated using a sterile metal needle onto a rich nutrient agar plate and incubated for 48 h at 30 °C. After incubation, 2 mL of chloroform was added to each plate to stop the bacterial growth and allow production of secondary metabolites only. The plates were re-incubated for 1 h at RT. 100 µL of test pathogenic bacteria (Bacillus subtilis (MTCC 121)) was mixed thoroughly with 2 mL of chilled nutrient broth containing 0.6% agar and spread uniformly over treated plates and incubated for 24 h. The antagonistic activity was determined by calculating the zone of inhibition (ZOI), suggesting the effective production of bioactive compounds. All the experiments were conducted in triplicate. Their outcomes were assessed in the form of mean ± standard error mean (SEM)31,32.Secondary screeningThe bacterial strains that demonstrated positive results in the preceding assays were further selected for secondary screening by using the agar well diffusion method. All the active bacterial strains were cultured in the nutrient broth at 30 °C and 150 rpm for 24 h. After incubation, the cultures were adjusted to procure an OD-600 nm (A600) ~ 0.8 using a UV/Visible Spectrophotometer (Thermo Fisher Scientific). The cultures were centrifuged for 10 min at 5000 x g to obtain a cell-free crude extract, then stored at 4 °C.The test pathogen (Staphylococcus aureus (MTCC 96)) was swabbed onto Muller Hinton (MH) agar (HiMedia, India) plates to generate a carpet texture using a sterile cotton swab. After swabbing, five wells (6 mm diameter and 10 mm deep) were constructed on the agar plate using a sterile cork borer. Each well was loaded with 100 µL of the crude extract at different concentrations: C1–100%, C2–50%, and C3–25%. An antibiotic disc (ciprofloxacin) at 100 ppm was used as the positive control, while distilled water was used as the negative control. The plates were allowed to rest for 1–2 h and incubated for 24 h at 37 °C, and then their ZOIs were measured. All the experiments were conducted in triplicate. Their outcomes were assessed in the form of mean ± standard error mean (SEM)24,24.Determination of MBC and MICThe Minimum Bacterial Concentration (MBC) and Minimum Inhibitory Concentration (MIC) of the subsequent bacterial strains were determined from the cell-free crude extract against the test pathogen (Staphylococcus aureus (MTCC 96)). The secondary metabolites obtained from secondary screening were extracted and concentrated in a dissolved nutrient broth. A two-fold serial dilution of the extract was made at varying concentrations (100%, 50%, 25%, 12.5%, 6.25%, 3.125%, and 1.562%). 0.1 mL of the standardized test inoculum and 0.1 mL of cell extract were added to all eight test tubes. Additionally, 0.1 mL of distilled water was added as a negative control in the remaining test tube. All the test tubes were incubated for 18–24 h at 37 °C. After incubation, the MIC was determined by observing the test tubes with no visible turbidity. 0.1 mL solution was taken from these test tubes and plated onto MH agar (HiMedia, India) and incubated for 24 h at 37 °C. Following incubation, MBC was assessed by studying the presence or absence of bacterial colonies. All the experiments were conducted in triplicate. Their outcomes were assessed in the form of mean ± standard error mean (SEM)24,33.Antibiotic susceptibility testing (AST)Antibiotic Susceptibility Testing (AST) was conducted, employing the disk diffusion method. The selected bacterial cultures were swabbed onto MH agar plates (HiMedia, India) using a sterile cotton swab to make a carpet texture. The plates were then incubated for 10 min. After equal spreading, the selected isolates were tested for their activity against six antimicrobial agents at various concentrations: amoxicillin (10 µg), cefotaxime (30 µg), ampicillin (10 µg), ciprofloxacin (5 µg), amikacin (30 µg), and erythromycin (15 µg). The plates were then sealed and incubated for 24 h at 37 °C. Antagonistic behavior was determined by measuring the ZOI. All the experiments were conducted in triplicate. Their outcomes were assessed in the form of mean ± standard error mean (SEM)33,34.Biochemical and morphological screeningThe examined bacterial isolates were stored in nutrient slants at 4 °C. Primary identification was done by determining the cell morphology characteristics, colony formation, and Gram staining. A series of biochemical tests were conducted to identify secondary identification of bacterial strains. The observed bacterial characteristics were compared with Bergey’s Manual of Determinative Bacteriology as a reference. A temperature of 37 °C was maintained for all the biochemical tests35.gDNA isolation, purification, and PCR amplificationAfter a series of screening procedures, the genomic DNA (gDNA) was extracted, employing the phenol/chloroform method. For verifying the purity and integrity of the bacterial strains, the extracted gDNA was run on 1% agarose gels in 1x TAE buffer (Tris-acetate-EDTA: pH 8.3, 89 mM Tris base, 89 mM boric acid, and 2 mM EDTA in 1 L of water) at 10 V mm-1 for 90 min. The results were inspected under a UV transilluminator and recorded using Bio-Rad’s Gel Doc XR. The samples were amplified using GeneJET PCR Purification and Gel Extraction Kit (Thermo Fisher Scientific), which contained a master mix of 50 µL: 1 µL of Taq DNA polymerase enzyme (3U/mL), 1 µL of gDNA template, 10X Polymerase assay buffer, 4 µL of deoxy-nucleoside triphosphates dNTPs (2.5mM each), 2 µL of universal forward and reverse universal primers (each), 1X of gel loading buffer, and 30 µL of water. The amplified products were run for 30 cycles. The gDNA was stored at 4 °C. PCR product was obtained and reloaded onto the 1% agarose gels against the 500 bp ladder for gDNA detection32,36,37,38,39.16S rRNA sequencingThe amplified and eluted gene products were further subjected to chain termination sequencing (16S rRNA sequencing; ribotyping) to identify the specific bacterial 16S rRNA gene products. After obtaining the necessary partial sequences, raw data files (trace files exhibiting forward and reverse sequence information) were procured from each sequenced sample. DNA Baser software version 5.15 was used to assemble the trace files (.ABI files) that were obtained from the sequencer to create the contigs. The contigs were stored in fasta format for further bioinformatic analysis40,41,42,43,44,45. The bacterial source of the sequence was identified by aligning it against sequences exhibiting the maximum identity score from the NCBI-GenBank Database46. For comparative analysis, the BLASTn47 was used. BLASTn-generated hits of the recorded sequences exhibiting 95% similarity were selected. The generated BLASTn hits pertained to query coverage, percentage identity score, E-value, and other edifying details.The phylogenetic assessment was performed by multiple sequence alignment using the Muscle algorithm in MEGA-XI software. The algorithm calculated a complex matrix that was manually aligned. Species-specific trees were constructed by employing the NJ method. The coding gaps were signified in binary format. The branch support and the subsequent topology were unaffected by the missing data. A phylogram was devised by taking twenty nucleotide sequences in total. All the ambiguous positions were removed from every sequence pair using the pairwise deletion position method. All the trees were inferred from 1000 replicates of the bootstrap consensus algorithm. The branches reproducing partitions in