2.1. Collection of Roots and Soil Samples

The feeder roots of H. brunonis Wall. collected from three sites (13°04’20.7”N 75°19’18.0”E, 13°10’22.8”N 75°20’44.3”E, and 12°43’55.0”N 75°39’39.9”E) belonging to Western Ghats regions of Karnataka state.

2.2. Surface Sterilization of Roots

Collected feeder roots washed with running tap water to remove soil particles. Then, the roots dipped in 2% sodium hypochlorite solution for 2 min. Transferred treated root segments to sterile distilled water, then cut into 1 cm long pieces with a sterile blade and stored in distilled water to get inoculated into the selective media [10].

2.3. Growing the Bacteria in Selective Media

Pikovskaya’s selective medium for screening the phosphate solubilizing bacteria employed in the present study [11,12]. Plates were inoculated with sterile root segments and incubated at 28°C for 7 days. The cut root ends are checked regularly for bacterial growth. The appearance of a colony surrounded by a halo-zone in the media indicated the organism’s growth and phosphate solubilizing ability [13,14]. The organism was subcultured into slants. Furthermore, a pure culture of bacteria got stored in nutrient agar slants for further analysis.

2.4. Determination of Phosphate Solubilizing Ability

The halo-zone formation surrounding the colony in Pikovskaya’s medium determines the phosphate solubilizing ability of the pure bacterial cultures qualitatively. For quantitative analysis, freshly inoculated pure culture in the Pikovskaya’s medium was observed once in 2 days. Then, the colony diameter and halo-zone diameter were measured to incorporate into the formula used to determine the solubilization index [15-17].

2.5. Identification of Bacteria

Biochemical protocols for bacterial identification for Gram’s staining, motility, starch hydrolysis, lipid hydrolysis, casein hydrolysis, gelatin hydrolysis, carbohydrate fermentation, H₂S, nitrate reduction, catalase, urease, oxidase, indole production, methyl red, Voges–Proskauer, citrate utilization, and phenylalanine deaminase tests performed following standard protocols [18]. For amplification of the 16S rRNA gene, a reaction mixture of 25 μL, containing 15 ng of template DNA, 0.12 μL of 5U μL⁻¹ Taq DNA polymerase, 2.5 μL of 10× Taq polymerase buffer, 1 μL of 5 mM dNTPs, 2 μL of 25 mM MgCl₂, and 1 μL of each 10 μM forward and reverse primers 27F/1492R (27F 5’-AGAGTTTGATCCTGGCTCAG-3’; 1492R 5’-GGTTACCTTGTTACGACTT-3’), were prepared. The PCR amplification of 16S rDNA included the following steps: Initial denaturation at 94°C for 5 min, followed by 30 cycles at 94°C for 1 min, 54°C for 1 min, and 72°C for 2 min, and final extension for 10 min at 72°C [19,20].

2.6. Identification of Isolates by 16S rRNA Sequence Analysis

Agarose gel eluted PCR products of the 16S rRNA gene are purified and sequenced according to Applied Biosystems’ 16S direct workflow protocol. The SeqStudio Genetic Analyzer capillary electrophoresis system performed both high-precision sizing and analysis of multicolor fluorescent DNA fragments and automated Sanger DNA sequencing [21]. Performed sequence similarity searches using the Basic Local Alignment Search Tool by comparing the sequences obtained to other microbial sequences in the National Center for Biotechnology Information (NCBI) database [22]. MEGA-X constructed the phylogenetic tree for our query sequence by obtaining closely related 16S rRNA gene sequences of other strains from the NCBI database through the Clustal W program, which performed multiple sequence alignments by the maximum-likelihood method based on the Jukes-Cantor model [23].

2.7. Metagenomics of V3-V4 Region

Metagenomic studies analyze the prokaryotic 16S ribosomal RNA gene (16S rRNA), approximately 1500 bp long and containing nine variable regions interspersed between conserved regions. This study used V3-V4 variable regions of 16S rRNA in phylogenetic classifications of the genus present in the plant-associated microbial population obtained through the 16S Metagenomic Sequencing Library Preparation protocol workflow [24]. High-quality DNA was extracted by following the manufacturer’s recommendation of QIAamp^® DNA Mini Kit. From the extracted DNA, 40 ng⁻¹ μl of DNA got utilized for the 16S Metagenomic Sequencing Library Preparation of V3-V4 region of 16S RNA gene as per the designated workflow. V13F/V13R (V13F – AGAGTTTGATGMTGGCTCAG and V13R –TTACCGCGGCMGCSGGCAC) are the primers used in this library preparation protocol. AMPure beads and components utilized from the Qubit dsDNA high sensitivity assay kit purified the amplicons. Illumina MiSeq with a 2x300PE v3 sequencing kit used for sequencing.

2.8. Bioinformatics and Statistical Analysis

The GAIA 2.0 analysis workflow, which provides an integrated metagenomic analysis suite, makes till genus-level taxa identification. The overall workflow involves GAIA consisting of different Python, Java, Bash, and R scripts that perform the following five steps: The first step is the quality check and trimming, in that GAIA calls BBDuk to remove both adapter sequences and bad quality portions from the reads. In the second step, BWA is used to map the high-quality reads from Illumina against custom-made databases created from NCBI sequences. Next, an in-house built Lowest Common Ancestor algorithm reads performs specific taxonomy level classification. Minimum identity thresholds are applied to classify reads into strains, species, genus, family, order, class, phylum, and domain levels; finally, phyloseq calculates alpha and beta diversities [25]. Interpreting the taxonomic and phenotypic profiles of microorganisms obtained from the metagenomic workflow conducted by inbuilt statistical functions of METAGENassist. METAGENassist (http://www.metagenassist.ca.) performs an automated taxonomic-to-phenotypic mapping. The taxonomic input data automatically generate phenotypic information covering nearly 20 functional categories such as GC content, genome size, oxygen requirements, energy sources, and preferred temperature range. Univariate data analyses, including clustering and classification, have been done using this phenotypically enriched data. This paper also uses METAGENassist generated graphs [26]. Further, the online database KEGG module to predict plant growth-promoting activities explored the possible plant-microbe interactions [27].

3. RESULTS

Surface disinfected root samples of H. brunonis Wall. were grown on Pikovskaya’s medium to obtain the phosphate solubilizing endophytic bacteria culture. Subculturing isolates producing the halo-zone in this medium gave its pure culture. These steps resulted in one pure culturable, phosphate solubilizing bacterium is identified and assigned to the taxonomy using both molecular method (16sRNA gene sequencing) and biochemical characterization. Result summary of phenotypic characterization of the bacterium is shown in Table 1 and the 16S rRNA sequencing method assigned the bacteria as Brevibacillus brevis (Supplementary data). This phosphate solubilizer produced a halo-zone around the colony to qualitatively determine its phosphate solubilization property [Figure 1]. Quantitative estimation of the phosphate solubility of B. brevis species measured on days 1, 3, 5, and 7, and the average phosphate solubility index obtained was 2.67 [Table 2].

Table 1: Morphological and biochemical test results.

Figure 1: (a) Humboldtia brunonis Wall. (b) Phosphate solubilization; exhibited by cultured Brevibacillus brevis in Pikovskaya’s medium. [Click here to view]

Table 2: Phosphate solubilizing ability of bacteria measured qualitatively.

The metagenomics studies have been done directly from root samples targeting the V3-V4 region of 16S rRNA and identified up to 43 endophytes, as shown in Figure 2 (supplementary data). Domain to genus taxonomic profile in Figure 3 shows the bacteria as dominant domain (99.8%) than Archea. Phylum Proteobacteria shares 98.9%, where Pseudomonas is the dominant genus. The members screened belong to Rhizobiales (3.3%), Burkholderiales (1.8%), and other orders. METAGENassist is uploaded in the form of data input with the Bacterial OTUs generated from metagenomic analysis obtained from the samples are summarised in [Table 3]. It is also provided with metadata of these samples in [Table 4] with discrete, qualitative labeled data values to generate well-annotated tables and colorful, labeled graphs. METAGENassist generated [Figure 4] statistically shows the role of the bacteria as dinitrogen and nitrogen fixers, carbon fixers, ammonia oxidizers, and nitrite reducers. The figure also emphasizes their energy sources, oxygen requirement, sporulation, and their nature of interaction with the plant.

Figure 2: Taxonomy plot analysis at genus level as obtained in V3–V4 metagenomics. [Click here to view]

Figure 3: Taxonomic profile from 16S metagenomic sequencing method. [View full-size image] https://jabonline.in/admin/php/uploadss/738_pdf.pdf [Click here to view]

Table 3: Bacterial OTUs from metagenomic analysis used in METAGENassist studies.

Table 4: Metadata file used for METAGENassist studies.

Figure 4: Phenotypic functional profile of endophytic bacteria present in Humboldtia brunonis Wall. [Click here to view]

4. DISCUSSION

The identified B. brevis, which belongs to the phylum Firmicutes, act as a phosphorus solubilizing endophyte in the endosphere region of H. brunonis Wall. This endophytic nature may be a fact due to its adaptability to extreme environments. This understory plant experience floods during monsoon and drought during hot summer in its confined distributed area. The association of B. brevis appeared in culture-based studies, and other endophytes reported from metagenomic analysis of 16S RNA play an essential role in plant adaptation. The genus-level plot analysis obtained from the metagenomic studies, which then combined with the KEGG module data (M00579, M00175, M00529, and M00116) resultant phosphate solubilizers are Acidobacterium, Bradyrhizobium, Brevundimonas, Burkholderia, Candidatus Solibacter, Duganella, Ensifer, Enterobacter, Escherichia, Fusobacterium, Geobacter, Herbaspirillum, Hyphomicrobium, Janthinobacterium, Klebsiella, Labrys, Leptothrix, Leptotrichia, Massilia, Mesorhizobium, Methylobacterium, Ochrobactrum, Pantoea, Paraburkholderia, Paracoccus, Pectobacterium, Pseudomonas, Psychrobacter, Rhizobium, Roseomonas, Salmonella, Serratia, Shinella, Sphingomonas, Stenotrophomonas, Streptobacillus, and Variovorax, but are non-responsive to culture-based techniques. Metagenomic report-based prediction of plant growth-promoting traits of these obtained genera in this plant endosphere zone suggests their role as biocontrol agents, biofertilizers, and phytostimulants. Biofertilization by the obtained taxa is quite evident as it confirms the presence of bacteria belonging to Acinetobacter, Burkholderia, Caulobacter, Devosia, Rhizobium, Herbaspirillum, and Bradyrhizobium as these genera can contribute to nitrogen, phosphorus, and potassium bioavailability. Bradyrhizobium, Burkholderia, Ensifer, Mesorhizobium, Methylobacterium, Paraburkholderia, and Rhizobium are capable of nodule formation here appear as endophytes of this non-nodulating legume. Enterobacter, Geobacter, Herbaspirillum, Hyphomicrobium, Klebsiella, Leptothrix, Magnetospirillum, Methylocystis, Pantoea, Pectobacterium, Pseudomonas, Rhodomicrobium, Serratia, Sphingomonas, and Vibrio are free-living diazotrophs taking shelter of this plant. Many of these bacteria are also known for their biocontrol abilities.

The overall results show a great diversity of bacterial species, and their statistical analysis shows that nearly 10% of these species [Figure 4] live in a symbiotic regime within plants. Moreover, other organisms can be opportunistic. The presence of about 72% aerobic bacteria suggests that they live inside the roots using the plant’s oxygen supply and are involved in recycling nitrogen and carbon, which are related to different pathways involved in phosphate solubilization, such as the pentose phosphate pathway [28]. Analysis of genomic diversity revealed that endophytes not only exhibit P solubility but also participate in other PGP traits; namely, biological nitrogen fixation (14%) and carbon fixation (3%) through the production of growth promoters such as IAA (+ for indole test); biological control functions such as subcellular production and antagonistic interactions were also evident.

5. CONCLUSION

H. brunonis Wall., a non-nodulating endemic legume, is belonging to the subfamily Detarioideae, seems to establish plant-microbe interactions in its endosphere with many groups of bacteria in various manners to utilize their services. This microbial ecology contributes significantly to the survival of this endemic plant. Detritus-driven Western Ghats forest floor dynamics create unique microbial ecology. Higher endemic taxa keep unique microbial associations to fulfill their survival requirements, as shown by this plant. The current research has shown that complex interactions between plants and microorganisms are necessary for coexistence. It is imperative to understand the local microbiota’s remarkable ability in exhibiting bio fertilization, biocontrol, and phytostimulation traits as endophytes of these endemic plants. The dynamics of endophytic biomes also remain an important area for future studies. Further studies examining the performance of these bacteria and their mutants on plant growth will help explore the mechanism and potential of these plant growth-promoting traits.