Structural And Functional Changes In Soil Microbes By Foliar Drift Spray of Seaweed Extract As Revealed By Metagenomics

Kappaphycus alvarezii seaweed extract (KSWE) is known to enhance crop productivity and impart stress tolerance and our preliminary studies showed their biostimulatory effect on soil bacteria also. Close to one quarter of the foliar spray carried out on maize falls on soil either as drift or from leaf as drip. Hence it was hypothesized, it would profoundly inuence soil microbes under stress. An experiment was conducted with ve treatments, with or without KSWE application at critical stages of maize under soil moisture stress and compared with an irrigated control. Illumina platform was employed for analysis of V3-V4 region of 16S rRNA gene from the soil metagenome. Total of 345,552 operational taxonomic units were generated which were classied into 55 phyla, 152 classes, 240 orders, 305 families and 593 genera. Shannon’s index and Shannon’s equitability indicated increased soil bacterial diversity by multiple KSWE applications under duress. The abundance of Steroidobacter, Balneimonas, Rubrobacter, Bacillus, Alicyclobacillus, Anaerolinea and Nitrospira genera decreased (49-79%) in drought imposed at V5,10, and 15 stages of maize over the irrigated control, while it signicantly improved when followed by KSWE application under drought. Nitrosomonas, Nitrosovibrio, Rubrobacter, Flavobacterium genera and several other taxa which are important for plant growth promotion and nutrient cycling were found to be enriched by KSWE application under drought. Treatments having enriched microbial abundance due to KSWE application under stress recorded higher soil enzymatic activities and cob yield, suggesting the contribution of altered soil ecology mediated by KSWE as one of the reasons for yield improvement. Further, the normally irrigated treatment (T5) was at par with the treatment receiving stress three times along with KSWE (T4) with respect to a relative abundance of all the aforesaid genera. The relative abundance of other important soil bacterial genera having known or potential role for nitrogen xation (Anaeromyxobacter, and Methanobacterium) and P solubilization (Flavobacterium) were also assessed. It was found that the KSWE application increased the relative abundance of all of these bacterial genera to that of the normally irrigated treatment. In all the aforesaid genera, the relative abundance in T4 was signicantly higher compared to T3 (Appendix S7).

It was also reported that KSWE application partly alleviated soil moisture stress in maize by modulating antioxidant enzymes and differential expression of certain genes (Trivedi et al. 2018a; Trivedi et al. 2018b). However, the effect of foliar spray of KSWE, or rather any seaweed based biostimulant on soil micro ora has never been reported. This has been probably neglected because the drift spray and drip from leaves falling onto the soil is seemingly miniscule. However, a careful quanti cation revealed that on average a quarter of biostimulants applied as foliar spray reaches the soil over the crop cycle (Table 1) and such a signi cant amount of it may have a direct effect on soil micro ora and related soil biochemical processes, which formed the hypothesis of the present work. The study assumes, maintenance of soil fertility and structure is controlled by interactions of a highly assorted and complex web of soil micro ora and fauna (Davet 2004). Enzymes released/produced by soil microbes are responsible for organic matter decomposition and nutrient cycling (Quan and Liang 2017). It was also hypothesized that the in uence of seaweed based biostimulants on soil bacteria would be manifested more under soil moisture stressed condition as drought profoundly in uences the dynamics of the microbial communities of soil (Quan and Liang 2017).
Whether or not the seaweed biostimulant in uences the soil bacteria positively under abiotic stress condition also formed the basis of present work. Accordingly, the study was conducted with the objective of assessing whether management practice involving the foliar application of KSWE in uences the soil culturable and unculturable bacterial community composition bene cially. This was carried out through the amplicon-based sequencing of 16S rRNA genes through nextgen Illumina sequencing. In addition, its effect on the yield of maize crop under normal as well as drought stress conditions was also evaluated.

Preparation of KSWE
The extract was prepared in bulk quantity as per the procedure described in Trivedi et al. (2017), stored at 4°C and used as and when required. Details of the composition of KSWE have been described earlier in Singh et al. (2016) and the same batch of the seaweed extract was also used in the present experiment.
The total soluble solids (TSS) of the KSWE was in the range of 3-4 %.

Ethics Statement
There was no speci c permission required for sampling in the experimental area of this study. The location is not protected or privately owned in any way, and it is con rmed that our experiment did not involve endangered or protected species. In addition to this, one normally irrigated treatment was kept where KSWE was sprayed daily in between V5 to grain lling stage just to know the detrimental effect of seaweed extract on soil microbes, if at all, when sprayed daily (T6; sample code: K16). However, this treatment was in single replication and not included in any statistical comparison.

Experimental site and design
All the pots were lled with 32 kg of soil to which chemical fertilizers at the recommended rate of 120:60:40 kg ha − 1 of N/P 2 O 5 /K 2 O were applied uniformly to all the treatments through urea, single super phosphate, and sulfate of potash, respectively. The initial soil of the experiments was sandy loam in texture, having pH 7.80 and electric conductivity of 0.20 dS m − 1 . Available N, P, and K were 103, 14 and 161 kg ha − 1 , respectively. Organic carbon in soil was 0.51%.
Four seeds were sown in each pot, which after successful germination was thinned to single plant per pot. The meteorological data of the experimental site is given in the Appendix S1.

Soil sampling
Core soil samples from around 30 cm depth were taken on 12th day after treatment in preliminary experiment 2 and at the time of plant harvesting for metagenomic and biochemical studies. All samples were collected in sterile 50ml acon tubes and transported immediately to the laboratory in ice. Later they were sieved (< 2 mm) and stored at 4°C until processing. The metagenomic study was carried out from all the treatments, while soil enzyme analysis was carried out only in the two most signi cant treatments found in the metagenomic study (viz. T3 and T4) from the samples collected at harvest.
Electric conductivity (EC) and pH of the initial soil samples were determined in 1:2.5 slurry of soil: water. Organic carbon was determined by Walkley and Black procedure as described in Nelson and Sommers (1982). Available N and available P were determined according to the procedure described by Maynard  For index PCR, each 50 µl of PCR reaction contained 5 µl of DNA, 5 µl of each Nextera XT Index Primers, 25 µl of 2x KAPA HiFi HotStart ReadyMix and 10 µl of PCR grade water. PCR reactions were performed in a thermal cycler with an initial denaturation step at 95°C for 3 min followed by 8 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s and ended with an extension step at 72°C for 5 min. One microlitre of a 1:50 dilution of the nal library was run on a Bioanalyzer DNA 1000 chip to verify the size.

Illumina sequencing
All samples were subjected to paired-end (250 bp) sequencing (V3-V4 region) using Illumina MiSeq sequencer and analyzed into the MiSeq Reporter onsystem software at SciGenom Labs Private Limited, Cochin, Kerala, India. Base quality checking of each cycle for all the samples was carried out and lowquality bases were removed so as to ensure that the majority of the reads with a high-quality score above 30 (Q > 30) were used for further downstream processing. It was found that nearly 75% of the total reads have a Phred score greater than 30 (> Q30, error-probability ≥ 0.001). Base composition and GC content distribution are also summarized in gures but not included in the paper.
All the sample reads were converted to FASTA les and were pooled together. The FASTA were pre-processed using the bioinformatics analysis pipeline. Chimeric sequences were removed using the program UCHIME and all non-chimeric sequences were taken for picking OTUs using the program UCLUST with a threshold of 97% of similarity ( ). Further alignment was done of these representative sequences against reference chimeric data sets. The read based taxonomy classi cation was performed using the RDP classi er against Greengenes OTUs database.
Further, heat maps were generated using the QIIME program. The phylum, class, order, family, genus and species distribution for each sample, based on OTUs, were shown as heat maps in the Appendix S2. The taxa other than the top 10 were categorized as "Others" and the sequences that did not have any alignment against the taxonomic database were categorized as "Unknown". Rare and abundant taxa from the samples were also identi ed. Rare taxonomy was de ned as having frequency < 0.01% and abundant taxonomy as OTUs having > 1% frequency (Galand et al. 2009; Aravindraja et al. 2013).
In order to assess the microbial diversity and distribution within and between the treatments, both α -diversity, and β -diversity were measured.

Alpha diversity and rarefaction curves
Microbial diversity within the samples was measured using Chao1, Shannon and observed species metrics. The Chao1 metric estimates the species richness while Shannon metric is the measure to estimate observed OTU abundances, and accounts for both richness and evenness. The observed species metric is the count of unique OTUs identi ed in the sample. The rarefaction curves for each of the metric have been provided in Appendix S3. The metric calculation was performed using QIIME software.

Beta diversity between samples
Explicit comparisons of bacterial communities between the samples were also performed. The distance matrix was generated using a weighted and unweighted UniFrac approach. Sequence abundances were taken into account in weighted UniFrac for comparing microbial diversity. A jackknife test was performed to construct a consensus UPGMA (Un-weighted Pair Group Method with Arithmetic Mean) tree for all samples in this set. The resulting consensus was taken for UPGMA trees built using a weighted UniFrac distance matrix.

Accession numbers
Sequencing data of all the 16 samples were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP180107) under the study SRP180107.

Soil enzyme estimation
Aryl sulphatase, acid-, alkaline-phosphomonoesterase and glucosidase activities in the eld moist soil were assayed according to Tabatabai (1982) using 4nitrophenol as standard. FDA activity was measured according to Schnürer and Rosswall (1982).

Statistical analysis
All statistical analyse were carried out using MSTAT C software. In the preliminary experiment 1, two-factor Completely Randomized Design was employed for ANOVA, while in the preliminary experiment 2 and metagenomic study one way ANOVA was used. The results were expressed in mean ± standard deviation of three independent replicates. Post hoc comparison of means was carried out using Tukey's honestly signi cant differences, Student-Neuman-Keul's test and Least signi cant different test at p < 0.05. The principal component analysis (PCA) was conducted using Minitab statistical software to assess the variation among treatments at different taxonomic levels. A Venn diagram was prepared using Ugent tool available on http://bioinformatics.psb.
ugent.be/webtools/Venn/ to observe the identi ed number of unique and shared species present among all the ve treatments.

Bacterial colony counts
In the preliminary experiment 1, It was found that the counts of Bacillus subtilis, Bacillus licheniformis and Pseudomonas uorescens increased signi cantly with concomitant increase in the KSWE concentration (5 and 10%) and both the doses recorded higher counts over control (Fig. 1a). Subsequently in preliminary experiment 2, drought signi cantly reduced the total CFUs in soil while KSWE brought out a signi cant increase in total bacterial count under both the soil moisture regimes at 10% level (Fig. 1b). Interestingly, the total bacterial CFUs in soil under drought conditions with 10% KSWE applied was similar to that under normally irrigated soil (without KSWE). These results were a prelude to the bacterial metagenomic study for in-depth information on the diversity and ecology of soil due to the in uence of KSWE.

Alpha diversity with rarefaction curves of Chao1, Shannon and Observed species
Rarefaction curves depicting alpha diversity (Appendix S3) reached near the plateau, indicating that the sampling depth and sequencing coverage were good. In addition, Shannon's index (H) and Shannon's equitability or evenness (E H ) were calculated at phylum level (Table 2) to show the relative bacterial diversity.
Shannon's index revealed that there was maximum bacterial diversity when the soil was subjected to stress with concomitant KSWE application three times (T4) during the growth cycle. This was followed by that in normally irrigated soil (T5), while it was lesser in soil that was subjected to stress thrice but not treated with KSWE (T3). Further, the bacterial communities in soil were found to be more evenly distributed in T4 (E H = 0.5787) and T5 (E H = 0.5624) as compared to those in other treatments.

Beta diversity with a phylogenetic tree
The bacterial community similarity, as revealed by the weighted UniFrac phylogenetic tree, is depicted in Appendix S4. It revealed that the bacterial community in the T5 (K13, K14, and K15) and T4 (K10, K11, K12) treatments were different from the T1 and T3 (K1, K2, K3, K7, K8), except K9 which clustered with the former group. The samples in these clusters (T1 and T3 vs T4 and T5) were also not close and grouped loosely indicating the difference in bacterial community composition in soil samples due to treatment effect.
3.5. Pairwise multiple comparisons of total OTU means Signi cant changes (P ≤ 0.001) in abundance of the 16S bacterial rRNA gene expressed as the number of total OTUs were detected among different treatments (T1-T5) using ANOVA and Tukey's test ( Table 3). The least number of OTUs was observed in soil collected from the treatment receiving moisture stress three times during the life cycle of the crop (T3, 100157). Variation in bacterial abundance due to KSWE was evident by a signi cant increase in the number of OTUs in soil samples of treatment that was subjected to stress three times and also with KSWE applied (T4, 232029) over the corresponding treatment (T3) where KSWE was not applied (P ≤ 0.001) ( Table 3). Moisture stress at one or more stages signi cantly reduced the OTU abundance in the soil as compared to that of irrigated soil (T5, 254041), except that in case of treatment receiving KSWE three times in which case it was at par.  were Chloro exi, followed by Proteobacteria, Actinobacteria, Firmicutes, Acidobacteria, Bacteroidetes, Gemmatimonadetes, Planctomycetes, TM7, Nitrospirae, Verrucomicrobia and others (which was a sum of all the rest) having individual abundance less than 0.5%.
There was a striking diversity shift with respect to the relative abundance of phyla Proteobacteria, Chloro exi and Firmicutes among the treatments T3, T4 and T5 (Fig. 3). Whereas the percentage of OTUs belonging to the Proteobacteria decreased from 26.06% in normal irrigated treatment (T5) to 17.23% due to stress applied three times (T3), application of KSWE increased its corresponding proportion to 24.87 in the stress treatment (T4). Similarly, the proportion of the abundance (OTUs) of microbes in Firmicutes phylum was reduced to 9.99% when subjected to moisture stress three times compared to normally irrigated condition, but upon KSWE application three times under duress, its proportion increased to 19.42%, which was even more than that under normal irrigated treatment (15.88%). It was found that KSWE under moisture stress could bring down the relative proportion of Chloro exi to an identical level (14.77%) as that under normal irrigated condition (15.9%) from the elevated level of 38.72% due to stress (T3).
The comparison of the relative abundance means of the top 12 enriched bacterial phylum categories (P ≤ 0.01) associated with soil samples collected from T1-T5 is shown in Fig. 4. The soil samples collected from the treatments subjected to stress once or thrice and not sprayed with KSWE (T1, T3) and those subjected to stress and KSWE spray only at V5 stage (T2) had signi cantly decreased populations of phyla Proteobacteria, Firmicutes, Bacteroidetes, Planctomycetes, and Verrucomicrobia, over the treatment that received stress and KSWE thrice (T4). KSWE applied thrice under stress (T4) showed an increase in the population of Proteobacteria, Firmicutes, Bacteroidetes, Planctomycetes, and Verrucomicrobia in soil samples by 107%, 179%, 162%, 409%, and 408% respectively, over its respective control (T3) (Fig. 4). Notably, the relative abundance of all these soil bacterial phyla in the T4 was found to be statistically similar to that under untreated normal irrigated control soil (T5). The populations of Acidobacteria, TM7, and Nitrospirae were not affected by any of the treatments. The abundance of OTUs belonging to Chloro exi was not signi cantly affected by any of the treatments, however, its relative proportion visà-vis other phyla within a given treatment varied considerably with its proportion increasing under moisture stress. Compared to the control (T1), mere application of KSWE once in early-stage under stress at the V5 stage (T2) of the crop had no noticeable change in the abundance of any of these top 12 phyla in the soil at harvest (Fig. 4 and Table 3).
The PCA was performed to assess the variation considering 55 known and 1 unknown phylum categories. Based on the factor loadings of these phyla, the four components of PCA explained the total variations as shown in Appendix S5.
The rst (PC1) and second (PC2) principal components contributed 73.9% and 10.8% of the total variation, respectively. The members of the dominant phyla including Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes had high loading on PC1 indicating that these vary together in the same direction. In contrast, Chloro exi had substantial negative loading on PC1.
A biplot of the component scores has been produced indicating the second component plotted against the rst component in Appendix S6. Looking at the treatment out by itself to the right, it may be inferred that the KSWE applied thrice under stress (T4) and the normally irrigated control (T5) had very high values for the rst component and it is expected that these treatments would have high values for the relative abundance of the bacterial community with which they are strongly correlated, i.e., they move in a similar direction. In agreement, both these treatments had higher values for most of the enriched phylum categories. Both the water sprayed controls as well as the KSWE sprayed once (T1, T2, and T3 respectively) were located extremely left on the spectrum and thus had lower values for the relative abundance of the respective phyla.

Distribution of bacterial community at class, order and family level
Biplots of the distribution of bacterial communities (top ten) at the higher taxonomic levels of class, order and family also exhibited the same pattern wherein the treatments T1, T2 and T3 were distantly located compared to T4 and T5 on the rst component (Appendix S6).
With respect to the top 10 enriched classes, KSWE treatment and stress applied thrice (T4) signi cantly improved the relative abundance of the Alpha-, Beta-, Gammaand Delta-proteobacteria along with Actinobacteria and Bacilli, when compared to their respective water sprayed stress control (T3). Moreover, the abundance levels of these classes were brought at par to the normally irrigated treatment (T5). Among the top 10 enriched orders, relative abundance of the Actinomycetales, Bacillales, Cytophagales, Myxococcales, Rhizobiales, and Xanthomonadales followed the same trend, while, within the top 10 dominant families, a similar trend was found in Anaerolinaceae, Bacillaceae, Cytophagaceae, Pseudonocardiaceae and Planococcaceae (Table 4). Further, the normally irrigated treatment (T5) was at par with the treatment receiving stress three times along with KSWE (T4) with respect to a relative abundance of all the aforesaid genera. The relative abundance of other important soil bacterial genera having known or potential role for nitrogen xation (Anaeromyxobacter, and Methanobacterium) and P solubilization (Flavobacterium) were also assessed. It was found that the KSWE application increased the relative abundance of all of these bacterial genera to that of the normally irrigated treatment. In all the aforesaid genera, the relative abundance in T4 was signi cantly higher compared to T3 (Appendix S7).
Principal component analysis at genus level of the top 10 and some others involved in N and P cycling also revealed that T1, T2 and T3 have similar associated abundance pattern clustered together towards the left side, while T4 and T5 clustered towards the right of the PC1, which explained 91.3% of the total variation (Appendix S5). The genera which helped distinguish the normally irrigated treatment (T5) from the treatment where KSWE and stress were applied thrice (T4) could be gauged by the in uence scores in the PC2, although this component explained 6.1% of the total variation (Appendix S5).

Distribution of bacterial communities at species level
A Venn diagram (Fig. 6) was also prepared to observe the identi ed number of unique and shared species present among all the ve treatments. The total number of different species identi ed in T1, T2, T3, T4, and T5 was 233, 260, 250, 268 and 248, respectively. The number of species unshared in these treatments were 10, 14, 9, 14 and 17, respectively. The number of species shared between all ve treatments was 135. Interestingly, the number of species shared between T4 and T5 was 30, which was the highest among any other paired comparisons.

Abundant and rare species diversity
Both rare (frequency of species with < 0.01% of the total population) and abundant species contributed to the overall bacterial population in all the 5 treatments. Total reads for rare species and abundant species were in the range of 300 to 1000 and 97 thousand to 250,000, respectively in the treatments.
Signi cantly higher rare and abundant species were found in T4 and T5. These treatments were at par for rare species while species abundance was more in T5 (Table 2). T1, T2, and T3 also followed a similar trend as in phylum and genus. They were signi cantly lower than T4 and T5 and at par with each other except T3 in the case of abundant species which was signi cantly lower than T2.
3.6.6. Functionally important species Fourteen unique species found in the treatment T4 (V5,10,15 KSWE) and the top 25 most abundant species that signi cantly varied with the treatments were classi ed for their functional roles (Tables 5 and 6). The unique species found in T4 treatment are speci cally known for their involvement in the processes like nitri cation, denitri cation, mineralization of organic compounds and production of enzymatic and non-enzymatic anti-oxidants. T4 showed signi cantly higher number of OTUs compared to T3 in all the 25 most abundant species shown in Table 6. Most of them were also at par with T5, a normally irrigated treatment. They were also involved in processes such as bioremediation of heavy metals, pollutants, production of antibiotic, antifungal and nematicidal compounds.

Effect of KSWE on soil enzymes
The in uence of KSWE on ve different soil enzymes at the harvest of maize crop is shown in Table 7. Compared to the control (T3), alkaline and acid phosphomonoesterases, aryl sulphatase, glycosidase, and FDA hydrolysis had signi cantly higher activities due to the application of KSWE (T4). The cob yield of maize plants was signi cantly altered due to the treatments ( Table 2). Signi cantly higher cob yield was observed in the treatments where KSWE was applied once or thrice along with drought stress compared to their respective controls. The highest cob yield was observed under the treatment receiving normal irrigation along with the KSWE application on a daily basis.

Discussion
From the results of the initial studies on a few PGPRs and total soil bacterial CFUs under different soil moisture regimes, it was apparent that KSWE is likely to have a positive in uence on soil bacteria under drought conditions. Further, our study showed that on an average, 23% of the spray volume of KSWE falls to the ground either as a drift or from the leaves as a drip (excess spray accumulating on the leaf surface drips to the ground), considering foliar spraying at V5, V10 and V15 stages of maize (Table 1). Hence KSWE was conjectured to have a considerable effect on soil bacterial community structure and function. In addition to direct effect, KSWE may also be indirectly contributing to growth and productivity of crop by modulating the soil ecology by effecting a desirable bacterial shift under stress conditions, which formed the hypothesis of this study. The study showed that KSWE helps the soil bacteria to recover from the negative impact of drought by rebuilding the affected soil microbial population, especially the species having functional importance in soil nutrient transformation and cycling.
This study characterized the effect of week-long drought stress subjected once or thrice during the critical stages of maize crop with or without the use of KSWE on soil bacterial community and compared it with the bacterial community present in normally irrigated soil. A detailed investigation carried out on soil collected at harvest revealed propensity towards a major shift in soil bacterial communities due to drought when compared to normally irrigated soil. This tendency to restructure the microbiome by drought was thwarted by KSWE application when applied three times at the critical crop stages.  (Kleber 1997  and would be in a greater proportion under moisture stressed soils as was also observed in this study. The observation that the nearly doubled relative abundance of Chloro exi in soil subjected to stress (T3) was brought down to the level present in the normal irrigated soil by KSWE application, supported the role of KSWE in eliciting stress response (Fig. 3).
The overall response of the bacterial community to soil moisture stress and KSWE was more or less consistent across all the taxonomic levels. At phylum level, the response to KSWE under stress (T4), when compared to its corresponding control (T3) was primarily driven by a signi cant enrichment of multiple phyla such as Actinobacteria, Proteobacteria, Firmicutes, Planctomycetes, Bacteroidetes and Verrucomicrobia (Fig. 4), all of whose abundances were diminished under stress when compared to normally irrigated conditions. The enriched relative abundance of these phyla brought about by KSWE under stress was at par to that under the normal irrigated condition and this observation was con rmed by beta diversity analysis depicted by a phylogenetic tree and PCA analysis, wherein T4 and T5 clustered more or less together, while T3 clustered separately from these two treatments. Within the Firmicutes, the most enriched OTUs in T4 compared to its control (T3) were mainly from the genera Clostridium, Bacillus, and Alicyclobacillus, all of which were endospore-forming bacteria.
The higher relative abundance of several OTUs classi ed as Proteobacteria due to T4 treatment (compared to T3) was mainly due to the genus Steriodobacter and Balneimonas falling under Gammaand Alpha -proteobacteria classes, respectively. The genera most affected by soil moisture stress were Anaerolinea and Nitrospira falling under the phylum Chloro exi and Nitrospirae, respectively. The relative abundance of both these genera under drought was increased due to KSWE when applied three times. Many other genera playing an important role in nutrient cycling in soil were also found to be bene cially in uenced by KSWE when applied three times under stress. For example, compared to T3, the relative abundance of the genus Rubrobacter under the phylum Actinobacteria -a thermophilic bacteria capable of degrading xylan, chitin, cellulose and hemicellulose and having an important role in organic matter turnover and C cycling -was signi cantly higher and may thus in uence nutrient availability to plants for better growth and yield. The phylum Actinobacteria is also associated with the production of bioactive compounds and plant growth promoters which might in uence the growth and yield of crops. Similarly, various genera instrumental in ammonia oxidation (Nitrosomonas, Nitrosovibrio, and Nitrospira) also were bene cially increased by KSWE under severe stress conditions compared to its respective control and their abundance levels were raised at par to that under normal irrigated condition (Appendix S7). The other taxons important for N cycling such as the phyla Chlorobi and those important for potassium solubilization such as Paenibacillus genus also followed the same trend (data not shown). The microbial communities are expected to play a crucial role in biochemical activities in the soil and thus the soil enzymes are crucial in C, P and S cycling. They can be used as soil quality indicators since they have more sensitivity to the changes in soil properties . The enrichment of species having functional roles such as in nutrient transformation and heavy metal tolerance (table 5 and 6) clearly brings out the bene cial role KSWE plays in soil for the bene t of crop growth and productivity. In agreement, the activities of various soil enzymes involved in P (acid and alkaline phosphatases), S (aryl sulphatase) and C (glycosidase) cycling were higher in T4 compared to the T3 treatment.
The observed KSWE-mediated changes in the soil bacterial communities and soil enzyme activities were also associated with higher crop yields under soil moisture stress conditions. Thus, this study provides a comprehensive understanding of how the KSWE could impart stress tolerance not only to the host plants but also was bene cial in providing a conducive soil bacterial microbiome. Further elaborate eld studies are warranted to understand soil-plantmicrobe interactions.

Conclusion
This study provided a comprehensive understanding of how the KSWE could impart stress tolerance not only to the host plants but also to the extent to which it enriched the soil bacterial microbiome elucidated to species level under stress conditions. The essence of the study was also to show that the KSWE application had no deleterious effect on the soil bacterial community and that the consequential bene cial effects may contribute towards improvement in the crop yields by improving nutrient cycling in soil.     replicates. Bars followed by different alphabets within the treatment are signi cantly different at P < 0.05 using Tukey's HSD.