Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Early Access

Inoculation of indole acetic acid-producing bacteria modulates growth and biochemical response of aromatic rice

DOI
https://doi.org/10.14719/pst.7793
Submitted
18 February 2025
Published
23-07-2025
Versions

Abstract

 

Indole-3-acetic acid (IAA) represents a pivotal phytohormone amongst the essential compounds involved in fostering plant growth and development, exerting its influence by provoking cell elongation, cellular enlargement and cellular division. Here, we aimed to optimize the IAA production by this selected strain and investigated its effect on the growth and biochemical status of two local aromatic rice cultivars Gobinda Bhog (GB) and Badshah Bhog (BB) as well as the soil nutrient status and their bioavailability were analyzed. The experiment was conducted in Molecular Plant Pathology and Fungal Biotechnology Laboratory, University of Burdwan, from June to December 2024. Our results indicated that fortification of rice plants with the microbial inoculant Bacillus cereus enhanced growth and biochemical characteristics as well as improved soil nutrient status. Culture conditions like incubation time, tryptophan concentration, carbon and nitrogen sources and their concentrations were optimized to get auxin-enriched postbiotics using the selected bacteria. Results showed maximum IAA (8.23 µM/mL) synthesis at 18 hrs of growth in 0.5 % tryptophan supplementation. Cellulose and sodium nitrate were the carbon and nitrogen sources respectively chosen by the isolate as suitable ones for the highest IAA production. Bio-priming as seed coating, seedling root inoculation and soil application, showed enhanced germination percentage, seedling height, dry biomass and tiller numbers. Further, the inoculated plants showed higher pigments, primary metabolites like soluble sugars and proteins, secondary metabolites like flavonoids and polyphenols and proline content compared to uninoculated plants. In conclusion, using this strain (Bacillus cereus MCC4850) has a high potency of implementing environmentally benign, economically viable and management techniques for sustainable crop production.

References

  1. 1. Verma DK, Srivastav PP. Extraction, identification and quantification methods of rice aroma compounds with emphasis on 2-acetyl-1-pyrroline (2-AP) and its relationship with rice quality: A comprehensive review. Food Rev Int. 2022;38(2):111-62. https://doi.org/10.1080/87559129.2020.1720231
  2. 2. Abbas R, Rasul S, Aslam K, Baber M, Shahid M, Mubeen F, et al. Halotolerant PGPR: A hope for cultivation of saline soils. J King Saud Univ Sci. 2019;31(4):1195-201. https://doi.org/10.1016/j.jksus.2019.02.019
  3. 3. Prodhan ZH, Shu Q. Rice aroma: A natural gift comes with price and the way forward. Rice Sci. 2020;27(2):86-100. https://doi.org/10.1016/j.rsci.2020.01.001
  4. 4. Verma DK, Thakur M, Srivastav PP. Biochemistry and molecular aspects of 2-acetyl-1-pyrroline biosynthesis in rice (Oryza sativa L.): A review. Isr J Plant Sci. 2020;67(3-4):129-43. https://doi.org/10.1163/22238980-bja10012
  5. 5. Salvadi N, Mir MI, Bee H. Plant growth promoting and biosurfactant activity of rice rhizosphere bacteria. Biochem Cell Arch. 2023;23(1):463. https://doi.org/10.51470/bca.2023.23.1.463
  6. 6. Basu A, Prasad P, Das SN, Kalam S, Sayyed RZ, Reddy MS, El Enshasy H. Plant growth promoting rhizobacteria (PGPR) as green bioinoculants: recent developments, constraints and prospects. Sustainability. 2021;13(3):1140. https://doi.org/10.3390/su13031140
  7. 7. Saxena AK, Kumar M, Chakdar H, Anuroopa N, Bagyaraj DJ. Bacillus species in soil as a natural resource for plant health and nutrition. J Appl Microbiol. 2020;128(6):1583-94. https://doi.org/10.1111/jam.14506
  8. 8. Wang Y, Zhang H, Zhang Y, Fei J, Xiangmin R, Peng J, et al. Crop rotation-driven changes in rhizosphere metabolite profiles regulate soil microbial diversity and functional capacity. Agric Ecosyst Environ. 2023;358:108716. https://doi.org/10.1016/j.agee.2023.108716
  9. 9. Kumar P, Sharma S, Tripathi VN. Quorum sensing in bacteria of rice rhizospheres from Chhattisgarh, India. Bioinformation. 2023;19(2):199-205. https://doi.org/10.6026/97320630019199
  10. 10. Zhang F, Xu N, Zhang Z, Zhang Q, Yang Y, Yu Z, et al. Shaping effects of rice, wheat, maize and soybean seedlings on their rhizosphere microbial community. Environ Sci Pollut Res. 2023;30(13):35972-84. https://doi.org/10.1007/s11356-022-24835-3
  11. 11. Fierer N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat Rev Microbiol. 2017;15(10):579-90. https://doi.org/10.1038/nrmicro.2017.87
  12. 12. Shah S, Wu T, Xu D, Li L, Liu Y, Yang X, et al. Nitrogen application and water regime affects archaeal community structure and functional genes for nitrification and denitrification in a paddy soil. Agric Ecosyst Environ. 2021;310:107300. https://doi.org/10.1016/j.agee.2021.107300
  13. 13. Arora P, Dixit S, Gupta A, Verma M, Dubey A. Co-cultivation with other PGPR or phytopathogen improves the 2-acetyl-1-pyrroline production and biofilm formation in Bacillus subtilis HAK7 isolated from aromatic rice (Oryza sativa L.). Arch Microbiol. 2020;202(3):549-58. https://doi.org/10.1007/s00203-019-01759-6
  14. 14. Vaishnav A, Shukla AK, Sharma A, Kumar R, Choudhary DK. Endophytic bacteria in plant salt stress tolerance: Current and future prospects. J Plant Growth Regul. 2019;38(2):579-94. https://doi.org/10.1007/s00344-018-9860-2
  15. 15. Kumar A, Verma JP, Sharma S, Maheshwari DK. Reduction in dose of chemical fertilizers and growth enhancement of rice (Oryza sativa L.) by PGPR under the system of rice intensification (SRI). Commun Soil Sci Plant Anal. 2011;42(5):593-610. https://doi.org/10.1080/00103624.2011.549059
  16. 16. Thapa S, Kumar A. Impacts of inoculation of plant growth promoting rhizobacteria (Bacillus amyloliquefaciens) on growth and productivity of rice in Nepal. Arch Agron Soil Sci. 2020;66(9):1266-79. https://doi.org/10.1080/03650340.2019.1673549
  17. 17. Meena KK, Sorty AM, Bitla UM, Choudhary K, Gupta P, Pareek A, et al. Abiotic stress responses and microbe-mediated mitigation in plants: the omics strategies. Front Plant Sci. 2017;8:172. https://doi.org/10.3389/fpls.2017.00172
  18. 18. Egamberdieva D, Wirth SJ, Shurigin VV, Hashem A, Abd_Allah EF. Endophytic bacteria improve plant growth, symbiotic performance of chickpea (Cicer arietinum L.) and survival under stress conditions. PLoS One. 2017;12(5):e0180887. https://doi.org/10.1371/journal.pone.0180887
  19. 19. Radhakrishnan R, Hashem A, Abd-Allah EF. Bacillus: A biological tool for crop improvement through bio-molecular changes in adverse environments. Front Physiol. 2017;8:667. https://doi.org/10.3389/fphys.2017.00667
  20. 20. Zhang N, Yang D, Kendall J, Borrás-Hidalgo O, Fan X, Wang Q, et al. Bacillus subtilis Ydj3 upregulates ascorbate peroxidase and catalase to enhance rice tolerance to salinity and oxidative stress. Plant Cell Rep. 2022;41(2):487-504. https://doi.org/10.1007/s00299-021-02799-7
  21. 21. De Vrieze M, Pandey P, Bucheli TD, Varadarajan AR, Ahrens CH, Weisskopf L. The impact of 2,4-diacetylphloroglucinol on the wheat microbiome under laboratory and greenhouse conditions. ISME J. 2019;13(3):509-20. https://doi.org/10.1038/s41396-018-0280-4
  22. 22. Suyal DC, Yadav A, Shukla P, Goel R. PGPR mediated regulation of gene expression and antioxidant enzyme activities in plants for alleviation of abiotic stresses. In: Meena VS, editor. Role of rhizospheric microbes in soil. Singapore: Springer. 2018:145-68. https://doi.org/10.1007/978-981-10-8402-7_7
  23. 23. Ngoma L, Ahmad F. Ecophysiology of plant growth promoting bacteria. Sci Hortic. 2012;136:1-14. https://doi.org/10.1016/j.scienta.2011.12.006
  24. 24. Seneviratne G, Rajakaruna RMJJK, Seneviratne KA, Madawala HMJS, Kulasooriya SA. Soil microbial communities in organic and conventional farming systems in tropical conditions: a case study. Appl Soil Ecol. 2010;46(3):210-6. https://doi.org/10.1016/j.apsoil.2010.08.002
  25. 25. Goswami D, Dhandhukia P, Patel P, Thakker JN. Screening of PGPR from saline desert of Kutch: growth promotion in Arachis hypogaea by Bacillus licheniformis A2. Microbiol Res. 2014;169(1):66-75. https://doi.org/10.1016/j.micres.2013.06.003
  26. 26. Radhakrishnan R, Khan AL, Lee IJ. Endophytic fungal interactions with plants and their contribution to salt tolerance. In: Ahmad P, Azooz MM, Prasad MNV, editors. Ecophysiology and responses of plants under salt stress. New York: Springer. 2013:153-69. https://doi.org/10.1007/978-1-4614-4747-4_7
  27. 27. Vessey JK. Plant growth promoting rhizobacteria as biofertilizers. Plant Soil. 2003;255(2):571-86. https://doi.org/10.1023/A:1026037216893
  28. 28. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73(16):5261-7. https://doi.org/10.1128/AEM.00062-07
  29. 29. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:590-6. https://doi.org/10.1093/nar/gks1219
  30. 30. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37(8):852-7. https://doi.org/10.1038/s41587-019-0209-9
  31. 31. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581-3. https://doi.org/10.1038/nmeth.3869
  32. 32. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. https://doi.org/10.1186/s13059-014-0550-8
  33. 33. Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14(6):927-30. https://doi.org/10.1111/j.1654-1103.2003.tb02228.x
  34. 34. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: Community Ecology Package. R package version 2.5-7;2020. https://CRAN.R-project.org/package=vegan
  35. 35. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2021. https://www.R-project.org/
  36. 36. Wickham H, Averick M, Bryan J, Chang W, McGowan LDA, François R, et al. Welcome to the tidyverse. J Open Source Softw. 2019;4(43):1686. https://doi.org/10.21105/joss.01686
  37. 37. Liaw A, Wiener M. Classification and regression by random Forest. R News. 2002;2(3):18-22. https://CRAN.R-project.org/doc/Rnews/
  38. 38. Breiman L. Random forests. Mach Learn. 2001;45(1):5-32. https://doi.org/10.1023/A:1010933404324
  39. 39. Aitchison J. The statistical analysis of compositional data. London: Chapman & Hall; 1986.
  40. 40. Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome datasets are compositional: and this is not optional. Front Microbiol. 2017;8:2224. https://doi.org/10.3389/fmicb.2017.02224
  41. 41. Gloor GB, Macklaim JM, Fernandes AD. Displaying variation in large microbiome data sets: a plot of log-ratios. Microbiome. 2016;4(1):68. https://doi.org/10.1186/s40168-016-0208-3
  42. 42. Fernandes AD, Macklaim JM, Linn TG, Reid G, Gloor GB. ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq. PLoS One. 2013;8(7):e67019. https://doi.org/10.1371/journal.pone.0067019
  43. 43. Nearing JT, Douglas GM, Comeau AM, Langille MGI. Denoising the denoisers: an independent evaluation of microbiome sequence error-correction approaches. Peer J. 2018;6:e5364. https://doi.org/10.7717/peerj.5364
  44. 44. Callahan BJ, Wong J, Heiner C, Oh S, Theriot CM, Gulati AS, et al. High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res. 2019;47(18):e103. https://doi.org/10.1093/nar/gkz569
  45. 45. Navas-Molina JA, Peralta-Sánchez JM, González A, McMurdie PJ, Vázquez-Baeza Y, Xu Z, et al. Advancing our understanding of the human microbiome using QIIME. Methods Enzymol. 2013;531:371-444. https://doi.org/10.1016/B978-0-12-407863-5.00019-8
  46. 46. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018;6(1):90. https://doi.org/10.1186/s40168-018-0470-z
  47. 47. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37(8):852-7. https://doi.org/10.1038/s41587-019-0209-9
  48. 48. Gloor GB, Reid G. Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data. Can J Microbiol. 2016;62(8):692-703. https://doi.org/10.1139/cjm-2015-0821
  49. 49. Egozcue JJ, Pawlowsky-Glahn V. Groups of parts and their balances in compositional data analysis. Math Geol. 2005;37(7):795-828. https://doi.org/10.1007/s11004-005-7381-9
  50. 50. Aitchison J, Egozcue JJ. Compositional data analysis: where are we and where should we be heading? Math Geol. 2005;37(7):829-50. https://doi.org/10.1007/s11004-005-7383-7

Downloads

Download data is not yet available.