Abstract
Endophytes are microorganisms that colonize plants, often via commensal or symbiotic associations, and regulate plant growth and metabolism. Such organisms are usually suitable alternatives to therapeuticallly relevant, bioactive, and commercially essential metabolites, particularly under optimized bioprocess conditions. The current study highlights the key research challenge of maximizing the production of Indole-3-Acetic Acid (IAA), a compound difficult to isolate from the plant due to low yield, by elucidating the genetic composition of an isolated endophyte and determining the biosynthetic pathway using the KEGG pathway. Moreover, deciphering the functional genomic and refining production optimization remain significant challenges. The whole-genome sequencing of the endophytic bacterium Bacillus cereus SKAM2 (Strain SKAM2) revealed a genome size of 5.6 Mb, a GC content of 36%, multiple tryptophan-dependent and tryptophan-independent pathways. Furthermore, the IAA biosynthetic pathways pave the way for process-optimization studies. The influence of various abiotic parameters and media supplements on IAA production in both intra- and extracellular media was compared, using a full-factorial design of experiments (DOE). The results showed the highest yield in the extracellular fraction, a 3.81-fold increase, exceeding the intracellular IAA yield. The results highlight the strong potential of strain SKAM2 as a microbial platform for sustainable IAA production.
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Introduction
The endophytes are microbes that establish symbiotic or commensal relationships with plants, providing a range of benefits to their host plants, such as enhanced defense mechanisms, increased resilience to stress, and improved overall physiological health1. The phytohormones play a significant role in plant growth and metabolism2. One of the most ubiquitous phytohormones, IAA (auxin), stimulates growth processes, tissue development, cell elongation, proliferation, and specialization in response to environmental signals3,4,5,6. The global market indicates a rising demand for IAA, which is expected to reach USD 36 million by 20287. In addition, earlier research has examined the therapeutic applications of IAA, particularly its anti-inflammatory effects8, hepatoprotective9, anticancer10, and the efficacy of chemotherapy in pancreatic cancer11.
The IAA production has been reported in various microorganisms, including actinomycetes, fungi, bacteria, and yeasts12,13,14,15,16. Aligned with sustainable development, IAA-producing microbial strains have attracted considerable attention as potential strains for providing cost-effective, eco-friendly, and large-scale biosynthesis of IAA12,17,18. Despite numerous studies on endophytic bacteria, IAA production19. Understanding functional genomics and optimizing IAA production strategies remains challenging. In addition, whole-genome analysis of endophytic bacteria facilitates the identification of genes underlying IAA production and reveals insights into their molecular and functional mechanism20. In this study, the genome sequence of an isolated endophytic bacterium, Strain Bacillus cereus SKAM2, associated with the medicinal plant Humulus lupulus, was analyzed to identify genes and pathways involved in IAA biosynthesis. Furthermore, the present study investigates the optimization of intra- and extracellular IAA production by the strain SKAM2 using a full-factorial DOE with various abiotic factors. Several studies have aimed to optimize microbial IAA production21,22,23,24; however, only a few have employed a full-factorial DOE to evaluate the influencing factors for intra- and extracellular IAA production. To the best of our knowledge, such studies are scarce in the current literature review to combine genome-level insights with a design-of-experiments approach to maximize IAA yield.
Result
The genome of strain SKAM2 revealed a size of 5.6 Mb, with an average GC content of 36%. The genome contains a circular topology, a chromosome size (bp) of 1 main chromosome (~ 5.5 Mbp), 90 tRNAs, 4 rRNAs, and 5836 protein-coding genes (CDS). The genome sequencing data of endophytic strain SKAM2, deposited under the accession number JBMFCI000000000.1 and the BioProject: PRJNA1237547. Figure 1 describes the genomic properties of the strain SKAM2.
Circular map of the strain SKAM2. Showing the coding sequence gene, transfer RNA (tRNA), ribosomal RNA (rRNA), transfer messenger RNA (tmRNA), guanine-cytosine (GC Content), and GC Skew.
Comparative genomics analysis of the SKAM2 strain
The genomic relatedness of strain SKAM2 was investigated by calculating pairwise Average Nucleotide Identity (ANI) values using the ANIm algorithm using JSpecies v1.5. SKAM2 shared ANI values exceeding 98.45% with five other Bacillus cereus genomes: M72-4 (CP119300.1), QKG-2024 (NZ_CP168976.1), DLOU-Tangshan (CP040340.1), ATCC 14,579 (JBJJSR010000003.1), and CPT56D-587-MTF (CP090081.1). Figure 2 represents the heatmap of ANI between SKAM2 and its closest relatives.
Pairwise ANI heatmap between strain SKAM2 and its closest relatives.
The antiSMASH was employed to investigate and predict secondary metabolite gene clusters. Table 1 describes the prediction and analysis of secondary metabolite BGCs. The findings indicated that the SKAM2 strain encodes multiple gene clusters involved in the synthesis of secondary metabolites. Among them are four non-ribosomal peptide synthases (NRPSs), one betalactone (betalactone-type fengycin), two terpenes, one NI-siderophore (petrobactin), and one RiPP-like (cerecyclin). Compared with known biosynthetic gene clusters related to petrobactin, cerecyclin, and bacillibactin, those in this study exhibited high similarity. In contrast, clusters associated with molybdenum cofactor and fengycin showed low similarity.
Additionally, the COG function analysis investigation detected 5,312 proteins in the genome that matched entries in the eggNOG database. Notably, 304 genes, accounting for 5.72% of the total, were associated with cell wall and membrane functions. A total of 493 genes, representing 9.28% of the genome, were linked to amino acid transport and metabolism, and 5.91% (314) of the genes were grouped into ion transport and metabolism. In addition, 5.69% (302) of carbohydrate metabolism genes were found in strain SKAM2. Figure 3 represents the COG function analysis of the genome. Furthermore, the strain SKAM2 reveals that the IAA biosynthesis and tryptophan metabolism genes were detected through the KEGG pathway (Figure S1). Table 2 describes the identified genes involved in IAA biosynthesis and tryptophan metabolism.
The COG classification of the genome strain SKAM2.
Optimization of IAA yield from intra- and extracellular sources via full factorial DOE
The investigation of the influence of different factors and culture conditions on IAA production was examined. Table 3: Describe the yield of IAA achieved in various factors. In addition, MINITAB® statistical tools results reveal that the main effects plot (Fig. 4), interaction plot (Fig. 5), Pareto chart (Fig. 6), and contour diagram (Fig. 7) were generated using MINITAB® to assess the relationships between variable effects, both intra- and extracellular IAA yield. Additionally, kinetic models for IAA yield in both intra- and extracellular IAA production processes were illustrated in Eqs. 1 and 2. Furthermore, analysis of variance (ANOVA) was used to determine the relative contribution and significance of each experimental factor governing IAA yield. The results, summarized in Table 4, include the sum of squares, mean square values, and significance levels (p-values) for both extracellular and intracellular IAA production.
Show the main effect plot, (A) extracellular and (B) intracellular IAA yield.
Shows an interaction plot for studying factors (A) extracellular and (B) intracellular IAA yield.
Illustrates the relative significance of various factors using a Pareto chart: (A) extracellular and (B) intracellular IAA yield.
Show the contour plots (A) of extracellular and (B) intracellular IAA yield.
Validation of the DOE model
The validation of the DOE model was conducted under optimized conditions predicted by the model. The validation run was performed using cultures grown under tryptophan-supplemented conditions, with static conditions, and incubated for 5 days (Table 3, run number 3), then compared with cultures grown under the same model conditions using the predicted model values. The calculated yield of the model was 0.67 mg/mL for extracellular and 0.25 mg/mL for intracellular. The experimental yield was achieved extracellular at 0.70 mg/mL and intracellular at 0.25 mg/mL. The experimental observation and predicted yields demonstrated close correspondence, confirming the model’s predictive accuracy under the optimized conditions. Figure 8 demonstrates the UPLC chromatograms corresponding to the validation runs for IAA optimization. The kinetic models for the validated model for extracellular and intracellular IAA production were represented by Eqs. 3 and 4.
UPLC chromatogram of the validation run of (A) extracellular and (B) intracellular IAA.
Discussion
The endophytic microorganisms isolated from plants are well known for conferring benefits to the host plant, ranging from growth to metabolite production25. Bacillus cereus, a scarcely identified endophyte, has garnered increasing attention for its genomic features and potential applications in sustainable agriculture and therapeutic development26. The genomic exploration of Bacillus strains demonstrated considerable biotechnological and pharmaceutical potential, offering a valuable avenue for elucidating the molecular mechanisms underlying secondary metabolite biosynthesis27. Microbial genome size and GC content act as crucial factors in shaping their adaptability to diverse environmental conditions28. Microbial strains possessing larger genome sizes are often better adapted to complex environments, potentially enabled by their capacity to encode a broader array of metabolic functions and stress-response mechanisms29. However, numerous studies have proposed that smaller bacterial genomes might offer a competitive edge, offering benefits in terms of energy efficiency and reproductive rate30,31. The current study highlighted the genome size of strain SKAM2 to be 5.6 Mb, with a GC content of 36%. The variations in the genome size of Bacillus cereus strains have been reported, ranging from 5.39 to 6.40, with similar GC content, exhibiting possible conservation of genetic composition among the genera26. Furthermore, the ANI quantifies the average level of nucleotide identity between matching genomic fragments from microorganisms. The ANI serves as a standard tool for distinguishing closely related species, owing to its high discriminatory power, with values ≥ 95% indicating the same species32,33. The ANI result of strain SKAM2 showed the highest ANI with Bacillus cereus strain M72-4 (98.59%) and Bacillus cereus strain QKG-2024 (98.58%).
In addition, genome mining was performed using the antiSMASH tools that uncovered a diverse array of biosynthetic gene clusters (BGCs)34,35 that revealed the secondary metabolic richness of strain SKAM2. The AntiSMASH analysis highlighted thirteen BGC-associated pathways. Among them, six gene clusters encoding unknown secondary metabolites were identified, including three RiPP-like clusters, NI Siderophores, and one NRPS-type cluster, indicating that the secondary metabolite profile of this strain is distinct from other reported Bacillus cereus genomes36,37. The applications of these metabolites, such as siderophores, indicate a high recurrence of plant-associated components38. The detection of RiPP-like clusters reveals the capacity of strain SKAM2 for producing ribosomally-synthesized and post-translationally-modified peptides, a group of metabolites broadly acknowledged for their potent antimicrobial activity and ecological relevance39,40. Together, the genomic insights paved a strong platform for deciphering and validating novel bioactive metabolites.
Next, we focused on identifying genes for IAA biosynthesis and tryptophan metabolism in the genome of strain SKAM2. Earlier investigations have highlighted the catalogues of endophytic microorganisms for diverse IAA biosynthesis pathways41, encompassing both tryptophan-dependent and tryptophan-independent mechanisms42,43. The tryptophan-dependent routes, including the IPyA pathway, tryptamine (TAM) pathway, indole-3-acetamide (IAM) pathway, and the indole-3-acetonitrile (IAN) pathway, were evaluated5,44. The strain SKAM2 harbors multiple genes associated with IAA biosynthesis, including ipdC, which encodes indole-3-pyruvate decarboxylase, a key gene involved in the IPyA pathway. Earlier studies have shown that the transcriptional activity of the ipdC gene correlates with the upregulation or downregulation of IAA production45,46. Further analysis of tryptophan metabolism revealed the presence of a cas operon that encompasses essential biosynthetic and metabolic genes, including trpA, trpB, trpC, trpD2, trpE, and trpF, which are crucial for IAA biosynthesis via tryptophan metabolism47. Previous results reveal that tryptophan serves as the primary precursor for the IAA biosynthetic pathway47. In addition, a tryptophan decarboxylase gene was identified in the genome of strain SKAM2, suggesting potential involvement of the TAM pathway, in which tryptophan is decarboxylated to tryptamine, an intermediate that can be further converted to IAA48. Earlier findings demonstrated that the bacteria possess multiple pathways for IAA biosynthesis49. Collectively, our observations support that the presence of a tryptophan-mediated biosynthetic pathway; the potential existence of tryptophan-independent routes in the endophytic strain SKAM2 cannot be ruled out.
Based on the genomic insights, strain SKAM2 reveals multiple tryptophan-dependent IAA pathways and tryptophan metabolism genes. To validate the genomic predictions and confirm the functional expression of these pathways, further analysis was done using full factorial DOE, which showed both intra- and extracellular IAA production due to the cascades of biosynthetic pathways. The secretion of IAA into the culture broth is rather unique and necessitates the exploration of the detailed mechanisms underlying this secretion process. The main effect (Fig. 4) analysis highlighted the significant effect of IAA yield from different factors. In extracellular IAA production, a distinct negative influence of factor rotation speed on IAA yield. In contrast, factors such as time, tryptophan, and glucose exhibited positive main effects, each contributing to a progressive enhancement in IAA yield. In addition, the main impact of intracellular IAA production factors, such as time and rotation speed, showed less impact on IAA yield. Similar observations have been reported that over-agitation has been shown to impair IAA yield in a wide range of microbial systems50,51. The tryptophan and glucose showed a significant impact on the intracellular production of IAA yield. Based on the main effect of both intra- and extracellular IAA yield, tryptophan was found to have the major impact on IAA yield. These results are consistent with previous studies that reveal tryptophan is a precursor of IAA42,52. Earlier investigations have highlighted that supplementing the medium with glucose enhances the IAA yield53. The Pareto analysis was employed to evaluate statistically significant factors influencing IAA yield. The Pareto chart (Fig. 6) reveals that, in both intra- and extracellular IAA, tryptophan was observed to be higher in both fractions. The assessment of the Pareto graph indicates significant factors required for regulating bacterial growth and IAA production. The Pareto charts deliver a clear visual ranking of effects, and ANOVA offers a more sensitive, model-based evaluation54. This complementary model enhances the accuracy of the experimental conclusions, consistent with previously reported DOE methodologies54. Furthermore, to identify the significant factor, ANOVA was conducted (Table 4), results highlighted that tryptophan had a statistically significant impact (p < 0.05) on both intra- and extracellular IAA yield. Our finding is consistent with earlier reports describing that supplements of tryptophan enhanced the IAA yield7,42,51,52. Furthermore, to validate these observations and the optimised studies, the validation of the DOE model was conducted. The optimization using DOE and validation are crucial steps to verify the predicted model values and the practical applicability of the developed model53,55. The validation result revealed a 5% deviation between the model-predicted (Table 3, run number 3) value and the experimentally validated data (Fig. 8). The validation results reveal a robust concordance between the experimental and predicted models, attesting to the model’s robustness and predictive accuracy.
Our findings suggest that whole-genome sequencing confirmed the presence of genes associated with the tryptophan-dependent IAA biosynthetic pathway, while also indicating the potential involvement of tryptophan-independent routes, forming the basis for design-of-experiments-guided optimization. Guided by this genome-level insight, statistical optimization identified conditions that maximized IAA production in extracellular production. As demonstrated in earlier reports, extracellular IAA production from microbes confers multiple ecological and biotechnological benefits, such as enhancing plant–microbe interactions44, enabling direct root uptake of auxin56, and minimizing feedback inhibition5. Furthermore, extracellular IAA production also enhanced the efficiency of metabolite extraction in downstream processes, aiding the application of agriculture and pharmaceuticals57. To the best of our knowledge, this is one of the few studies where an association with the elucidated metabolic pathways and the IAA biosynthesis has been deciphered. The study not only provides insight into the role of abiotic factors in modulating IAA biosynthesis in both intracellular and extracellular media, but also paves the way for elucidating the detailed mechanisms quantifying IAA in both intracellular and extracellular fractions. The findings demonstrated that quantifying IAA in both extracellular and intracellular fractions resulted in a higher total IAA yield by the strain SKAM2.
Conclusion
The isolated endophytic bacterial strain SKAM2 has been identified as a potential source of IAA, and, like many other well-explored endophytes, exhibits evidence of tryptophan-dependent pathways. The culture may also be adapted for tryptophan-independent IAA production, as analyzed in the DOE, where the absence of tryptophan was shown to affect IAA production. The results further suggest that interactions among abiotic factors modulate IAA yield. However, the role of interaction in the transcriptional regulation of IAA biosynthesis requires an in-depth analysis. The cumulative production of IAA in both intracellular and extracellular environments synergistically improves the overall yield. However, an interesting aspect of exploration will be the underlying mechanism responsible for the regulated release of IAA into the extracellular media. The study may be further extended to understand the molecular regulation of IAA biosynthesis and optimized production for designing a scale-up process.
Materials and methods
Collection of microorganisms
In our previous studies, our lab isolated a endophytic bacterial strain, Bacillus cereus SKAM2, from Humulus lupulus. The isolation and characterization have been done in our previously published work58. The biochemical and molecular techniques were employed for the identification of bacteria58. and their 16 S rRNA sequence has been submitted to GenBank under the accession number PQ305264. The isolated strain was stored at 4 °C for future use.
Whole genome sequencing of endophytic strain SKAM2
Library preparation and quality assessment
The whole genome sequencing of Bacillus cereus SKAM2 was performed at BioKart India Pvt. Ltd, Bengaluru, India. The Genomic DNA was quantified using the Qubit 3 Fluorometer with the dsDNA High Sensitivity (HS) assay. A total of 100 ng of intact DNA was enzymatically fragmented to generate 200–300 bp fragments. These fragments underwent end repair to convert overhangs into blunt ends. The 3′ to 5′ exonuclease activity removed 3′ overhangs, while polymerase activity filled in 5′ overhangs. Following end repair, a single adenine (A) nucleotide was added to the 3′ ends (adenylation), facilitating the ligation of loop adapters. The adapter-ligated DNA was treated with the uracil-specific excision reagent (USER) enzyme to cleave uracil-containing sites and purified using AMPure XP beads. A paired-end sequencing library was constructed26. The resulting library was then PCR-amplified for 6 cycles using the NEBNext Ultra II Q5 Master Mix with Illumina universal primers and sample-specific indexed (octamer) primers. Post-PCR cleanup was performed again with AMPure XP beads, and the final DNA library was eluted in 15 µL of 0.1× TE buffer. Library quantification was performed using a Qubit 3 Fluorometer with the dsDNA HS reagent. Fragment size distribution and quality were assessed by loading 1 µL of the library onto an Agilent DNA 7500 chip and analyzing it using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, California, United States)59. The quality control of raw reads was performed using the “FastQC quality control” tool of Galaxy v.0.7260. The genome of Bacillus cereus ATCC 10,987 was utilized as the reference61. Furthermore, A phylogenetic tree (Figure S2) was constructed using the Molecular Evolutionary Genetics Analysis software (MEGA, version 11)62 using the Neighbor-Joining algorithm with the Maximum Composite Likelihood model. To examine the robustness of each node, 1,000 bootstrap samples were performed63.
Genome component analysis, comparative genomics analysis, and functional annotation of strain SKAM2
The Genomic component analysis was done using PROKKA version 1.14.6 (rapid prokaryotic genome annotation)64. The JSpecies is one of the most popular, utilized, and recognized tool in microbial genomics65. The closely related genomes were obtained from the NCBI database. Genomic ANI was calculated using the NUCmer algorithm via JSpecies v1.5 with default settings47. The prediction and analysis of secondary metabolite biosynthetic gene clusters (BGCs) in the bacterial genome sequences were carried out using the antiSMASH software version 8.0.166. Gene function was studied through the cluster of orthologous groups (COG)67 from the EggNOG mapper Galaxy with default parameters68. Furthermore, the sequencing results were compared with the Kyoto Encyclopedia of Genes and Genomes (KEGG)47. Using the predicted genomic data, a genome map of strain SKAM2 was created using GC Viewer69.
Optimization of the production of IAA by the full factorial DOE
A full factorial DOE was employed to evaluate factor interactions. The analysis was performed using the MINITAB® statistical software to optimize different factors: incubation time, rotation speed, tryptophan, and glucose concentration. A total of 32 replicated experiments were conducted using a two-level factorial design (−1, + 1), defining the minimum and maximum levels of different factors, as presented in Table 5. The experimental run was carried out to assess changes in IAA production in both extracellular and intracellular fractions.
Preparation of the extract for IAA production
The extracellular IAA production was carried out using the strain SKAM2, which was grown in M9 minimal salt medium (1X) (HiMedia, Mumbai, India)58, incubated at 37 °C74, with different culture conditions mentioned in Table 5. The biomass of the culture was extracted by centrifugation, and the resulting supernatant was dried at room temperature. The intracellular IAA production was conducted using the bacterial biomass, which was subjected to sonication using the Sonics Vibra-Cell ultrasonic processor VCX 130 (Sonics & Materials, Inc., CT, USA) at an amplitude of 80 Å for 2 min, employing 10-second on-and-off cycles, using the protocol with modification established by Singh75. The lysate was centrifuged for 10 min at 4 °C to obtain the intracellular supernatant.
Assessment of IAA by ultra-performance liquid chromatography (UPLC)
The quantitative assessment of IAA was conducted using the method with modification described by Szkop and Bielawski76. The extract was dissolved in HPLC-grade methanol and subjected to chromatographic separation at 37 °C. UPLC was performed using a Waters Acquity UPLC (Waters Corporation, Milford, MA, USA) system equipped with a BEH C18 column (100 mm × 2.1 mm, 1.7 μm particle size). The mobile phase consisted of solvent A: B in a 40:60 ratio (0.01% glacial acetic acid in water: acetonitrile). The column temperature was maintained at 35 °C, with a detection wavelength of 265 nm using a PDA eλ detector. The total run time was 5 min, with a 1 µL injection volume and a flow rate of the mobile phase of 01 mL/min. Furthermore, five different solutions of IAA (Central Drug House (P) Ltd) with concentrations from 50 µg/ml to 250 µg/ml were prepared from UPLC to establish the calibration curve. The representative chromatograms and the standard calibration curve are provided in the supplementary file (Figure S3). The resulting chromatographic peak was analyzed and compared with the retention time of the standard IAA obtained from Central Drug House (P) Ltd.
Statistical analysis
All experiments were conducted in duplicate, and the reported data represent the average of the observations.
Data availability
The whole-genome sequencing data of strain *Bacillus cereus* SKAM2 generated in this study have been deposited in the National Center for Biotechnology Information (NCBI) GenBank database under accession number JBMFCI000000000.1 and the BioProject accession number PRJNA1237547.
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The authors acknowledge the Department of Biotechnology, Jaypee Institute of Information Technology, Noida, for providing all necessary support for the successful execution of the study.
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Khan, S., Mathur, A. Genome Insight and factorial design to elucidate the regulation of the tryptophan-mediated IAA biosynthetic pathway in an endophyte. Sci Rep 16, 10376 (2026). https://doi.org/10.1038/s41598-026-40546-y
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DOI: https://doi.org/10.1038/s41598-026-40546-y
