A Two-Level Factorial Design for Screening Factors that Influence the Growth of Bacillus sp. Strain UPM2021n isolated from a Mangrove Sediment on Acrylamide

Authors

  • Garba Uba Department of Science Laboratory Technology, College of Science and Technology, Jigawa State Polytechnic, Dutse. P.M.B 7040, Nigeria.
  • Motharasan Manogaran Malaysia Genome and Vaccine Institute (MGVI) National Institute of Biotechnolgy Malaysia (NIBM) Jalan Bangi, 43000 Kajang, Selangor, Malaysia.
  • Sanusi Magaji Department of science laboratory technology, School of sciences and technology, Abubakar Tatari Ali polytechnic, Bauchi, PMB 0092, Nigeria.
  • Nur Adeela Yasid Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, UPM 43400 Serdang, Selangor, Malaysia.
  • Mohd Yunus Shukor Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, UPM 43400 Serdang, Selangor, Malaysia.

DOI:

https://doi.org/10.54987/ajpb.v4i2.783

Keywords:

Acrylamide, Bacillus sp., Bioremediation, Screening, Two-level factorial

Abstract

Acrylamide; a neurotoxicant, is an emerging pollutant of global importance. As a strategy for bioremediation, the breakdown of acrylamide by the action of microbes has seen a gradual but consistent increase in attention all over the world. An acrylamide-degrading bacterium tentatively identified as Bacillus sp. strain UPM2021n was screened for significant parameters contributing to optimized growth on acrylamide using a two-level factorial design. The two-level factorial design was adopted in screening of five independent factors influencing the growth of the bacterium on acrylamide. These factors include pH, temperature, incubation time, acrylamide concentration and glucose concentration.  A total of 32 experiments with three replications of the centre points were carried out. The two-level factorial design was successful in finding important contributing parameters in the  growth of this bacterium on acrylamide, which were pH and incubation time (p<0.05) that can be further optimized using RSM in future works. The important contributing factors or parameters were analysed using ANOVA, Pareto’s chart and pertubation’s plot and other diagnostic plots. The diagnostic plots such as half-normal, Cook’s distance, residual vs runs, leverage vs runs, Box-Cox, DFFITS, DFBETAS all supported the two-level factorial conclusion with the exception of potentially two outliers that meant the experiment should either be repeated again using blocks or the potential outliers removed from analysis. This significant factors in this study are well within the range reported in many acrylamide-degrading microorganisms. The significant factors obtained in this study will be further processed using Response Surface Method (RSM).

References

Mottram, DS, Wedzicha BL, Dobson AT. Acrylamide is formed in the Maillard reaction. Nature. 2002;419:448-9.

Zamora R, Delgado RM, Hidalgo FJ. Strecker aldehydes and ?-keto acids, produced by carbonyl-amine reactions, contribute to the formation of acrylamide. Food Chem. 2011;128(2):465-70.

Shukor MY, Gusmanizar N, Azmi NA, Hamid M, Ramli J, Shamaan NA, et al. Isolation and characterization of an acrylamide-degrading Bacillus cereus. J Enviromental Biol. 2009;30(1):57-64.

Hagmar L, Törnqvist M, Nordander C, Rosén I, Bruze M, Kautiainen A, et al. Health effects of occupational exposure to acrylamide using hemoglobin adducts as biomarkers of internal dose. Scand J Work Environ Health. 2001;27(4):219-26.

Igisu H, Goto I, Kawamura Y, Kato M, Izumi K. Acrylamide encephaloneuropathy due to well water pollution. J Neurol Neurosurg Psychiatry. 1975;38(6):581-4.

Eikmann T, Herr C. How dangerous is actually acrylamide exposure for the population. Umweltmed Forsch Prax. 2002;7(6):307-8.

Pruser KN, Flynn NE. Acrylamide in health and disease. Front Biosci - Sch. 2011;3 S(1):41-51.

Pennisi M, Malaguarnera G, Puglisi V, Vinciguerra L, Vacante M, Malaguarnera M. Neurotoxicity of acrylamide in exposed workers. Int J Environ Res Public Health. 2013;10(9):3843-54.

Rahim MBH, Syed MA, Shukor MY. Isolation and characterization of an acrylamide-degrading yeast Rhodotorula sp . strain MBH23 KCTC 11960BP. J Basic Microbiol. 2012;52(5):573-81.

Wakaizumi M, Yamamoto H, Fujimoto N, Ozeki K. Acrylamide degradation by filamentous fungi used in food and beverage industries. J Biosci Bioeng. 2009;108(5):391-3.

Wampler DA, Ensign SA. Photoheterotrophic metabolism of acrylamide by a newly isolated strain of Rhodopseudomonas palustris. Appl Environ Microbiol. 2005;71(10):5850-7.

Buranasilp K, Charoenpanich J. Biodegradation of acrylamide by Enterobacter aerogenes isolated from wastewater in Thailand. J Environ Sci. 2011;23(3):396-403.

Charoenpanich J, Tani A. Proteome analysis of acrylamide-induced proteins in a novel acrylamide-degrader Enterobacter aerogenes by 2D electrophoresis and MALDI-TOF-MS. Chiang Mai Univ J Nat Sci. 2014;13(1):11-22.

Gusmanizar N, Shukor Y, Ramli J, Syed MA. Isolation and characterization of an acrylamide-degrading Burkholderia sp. strain DR.Y27. J Ris Kim. 2015 Feb 11;2(1):34.

Yu F, Fu R, Xie Y, Chen W. Isolation and characterization of polyacrylamide-degrading bacteria from dewatered sludge. Int J Environ Res Public Health. 2015;12(4):4214-30.

Bedade DK, Singhal RS. Biodegradation of acrylamide by a novel isolate, Cupriavidus oxalaticus ICTDB921: Identification and characterization of the acrylamidase produced. Bioresour Technol. 2018 Aug 1;261:122-32.

Aisami A, Gusmanizar N. Characterization of an acrylamide-degrading bacterium isolated from hydrocarbon sludge. Bioremediation Sci Technol Res. 2019 Dec 28;7(2):15-9.

Othman AR, Rahim MBHA. Modelling the Growth Inhibition Kinetics of Rhodotorula sp. strain MBH23 (KCTC 11960BP) on Acrylamide. Bioremediation Sci Technol Res. 2019 Dec 28;7(2):20-5.

Rusnam, Gusmanizar N. An Acrylamide-degrading Bacterial Consortium Isolated from Volcanic Soil. J Biochem Microbiol Biotechnol. 2021 Dec 31;9(2):19-24.

Rusnam, Gusmanizar N. Characterization of An Acrylamide-degrading Bacterium Isolated from Volcanic Soil. J Environ Bioremediation Toxicol. 2022 Aug 5;5(1):32-7.

Hedayat AS, Pesotan H. Designs for two-level factorial experiments with linear models containing main effects and selected two-factor interactions. J Stat Plan Inference. 1997;64(1):109-24.

Leitnaker MG, Mee RW. Analytic use of two-level factorials in incomplete blocks to examine the stability of factor effects. Qual Eng. 2001;14(1):49-58+xii.

Chang FK, Ting CP. Optimal two-level fractional factorial designs for location main effects with dispersion factors. Commun Stat - Theory Methods. 2011;40(11):2035-43.

Besseris GJ. Order statistics for the two-level eight-run saturated-unreplicated fractional-factorial screening: Corrections for asymmetry in the three-and four-factor multi-contrasting. Int J Qual Eng Technol. 2013;3(3):236-42.

Parui S, Parsad R, Mandal BN. Efficient block designs for incomplete factorial experiments for two factors with unequal block sizes. Commun Stat - Theory Methods. 2021;50(11):2531-45.

Haida Z, Ab Ghani S, Juju Nakasha J, Hakiman M. Determination of experimental domain factors of polyphenols, phenolic acids and flavonoids of lemon (Citrus limon) peel using two-level factorial design: Determination of experimental domain factors. Saudi J Biol Sci. 2022;29(1):574-82.

Manogaran M, Manogaran B, Othman AR, Gunasekaran B, Shukor MYA. Decolourisation of Reactive Red 120 by a Heavy Metal-tolerant Bacterium Isolated from Juru River, Malaysia. Bioremediation Sci Technol Res. 2020 Jul 31;8(1):23-6.

Bonate PL. Linear Models and Regression. In: Bonate PL, editor. Pharmacokinetic-Pharmacodynamic Modeling and Simulation [Internet]. Boston, MA: Springer US; 2011 [cited 2022 Dec 24]. p. 61-100. Available from: https://doi.org/10.1007/978-1-4419-9485-1_2

Mundry R. From nonparametric tests to mixed models: A brief overview of statistical tools frequently used in comparative psychology. In: APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior, Vol 1. Washington, DC, US: American Psychological Association; 2017. p. 157-77. (APA handbooks in psychology®).

Fox J. Regression Diagnostics: An Introduction. SAGE Publications; 2019. 138 p.

Shah M. Microbial Degradation of Acrylamide by Enterobacter spp. Am J Water Resour. 2014 Nov 2;2:134-40.

Shimamura Y, Yui T, Horiike H, Masuda S. Toxicity of combined exposure to acrylamide and Staphylococcus aureus. Toxicol Rep. 2022 Jan 1;9:876-82.

Kulkarni NH, Muley AB, Bedade DK, Singhal RS. Cross-linked enzyme aggregates of arylamidase from Cupriavidus oxalaticus ICTDB921: process optimization, characterization, and application for mitigation of acrylamide in industrial wastewater. Bioprocess Biosyst Eng [Internet]. 2019; Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075085765&doi=10.1007%2fs00449-019-02240-4&partnerID=40&md5=12e064000a11176469878181f8642894

Lakshmikandan M, Sivaraman K, Elaiya Raja S, Vasanthakumar P, Rajesh RP, Sowparthani K, et al. Biodegradation of acrylamide by acrylamidase from Stenotrophomonas acidaminiphila MSU12 and analysis of degradation products by MALDI-TOF and HPLC. Int Biodeterior Biodegrad. 2014;94:214-21.

Chandrashekar V, Chandrashekar C, Shivakumar R, Bhattacharya S, Das A, Gouda B, et al. Assessment of acrylamide degradation potential of Pseudomonas aeruginosa BAC-6 isolated from industrial effluent. Appl Biochem Biotechnol. 2014;173(5):1135-44.

Emmanuel Joshua Jebasingh S, Lakshmikandan M, Rajesh RP, Raja P. Biodegradation of acrylamide and purification of acrylamidase from newly isolated bacterium Moraxella osloensis MSU11. Int Biodeterior Biodegrad. 2013;85:120-5.

Ansede JH, Pellechia PJ, Yoch DC. Metabolism of acrylate to beta-hydroxypropionate and its role in dimethylsulfoniopropionate lyase induction by a salt marsh sediment bacterium, Alcaligenes faecalis M3A. Appl Environ Microbiol. 1999 Nov;65(11):5075-81.

Dey A, Suen CY, Das A. Asymmetric fractional factorial plans optimal for main effects and specified two-factor interactions. Stat Sin. 2005;15(3):751-65.

Bailey RA, ?acka A. Nested row-column designs for near-factorial experiments with two treatment factors and one control treatment. J Stat Plan Inference. 2015;165:63-77.

Lawson J. Comparison of conditional main effects analysis to the analysis of follow-up experiments for separating confounded two-factor interaction effects in 2 IVk?p fractional factorial experiments. Qual Reliab Eng Int. 2020;36(4):1454-72.

Chobisa D. Design of Experiments for the Development of Injectable Drug Products. In: Beg S, editor. Design of Experiments for Pharmaceutical Product Development: Volume II?: Applications and Practical Case studies [Internet]. Singapore: Springer; 2021 [cited 2022 Dec 24]. p. 69-96. Available from: https://doi.org/10.1007/978-981-33-4351-1_5

Draper NR, Stoneman DM. Factor Changes and Linear Trends in Eight-Run Two-Level Factorial Designs. Technometrics. 1968;10(2):301-11.

Wei J, Carroll RJ, Harden KK, Wu G. Comparisons of treatment means when factors do not interact in two-factorial studies. Amino Acids. 2012;42(5):2031-5.

Cornell JA. Classical and Modern Regression With Applications. Technometrics. 1987 Aug 1;29(3):377-8.

Aydin D, Alma ÖG. Diagnostics of influential observations in partially linear models. Erzincan Univ J Sci Technol. 2015 Jan 2;8(1):51-68.

Yahaya YA, Don MM. Flavonoid production by T. lactinea: screening of culture conditions via OFAT and optimization using response surface methodology (RSM). J Korean Soc Appl Biol Chem. 2014 Dec;57(6):749-57.

Kumar P, Sudesh, Kumar A, Suneja P. Studies on the physicochemical parameter's optimization for indole-3-acetic acid production by Pantoea agglomerans CPHN2 using one factor at a time (OFAT) and response surface methodology (RSM). Environ Sustain [Internet]. 2022 Dec 13 [cited 2023 Jan 2]; Available from: https://doi.org/10.1007/s42398-022-00254-5

Yap LS, Lee WL, Ting ASY. Optimization of L-asparaginase production from endophytic Fusarium proliferatum using OFAT and RSM and its cytotoxic evaluation. J Microbiol Methods. 2021 Dec 1;191:106358.

Saha SP, Mazumdar D. Optimization of process parameter for alpha-amylase produced by Bacillus cereus amy3 using one factor at a time (OFAT) and central composite rotatable (CCRD) design based response surface methodology (RSM). Biocatal Agric Biotechnol. 2019 May 1;19:101168.

Yousefi V, Kariminia HR. Statistical analysis for enzymatic decolorization of acid orange 7 by Coprinus cinereus peroxidase. Int Biodeterior Biodegrad. 2010;64(3):245-52.

Downloads

Published

31.12.2022

How to Cite

Uba, G., Manogaran, M., Magaji, S., Yasid, N. A., & Shukor, M. Y. (2022). A Two-Level Factorial Design for Screening Factors that Influence the Growth of Bacillus sp. Strain UPM2021n isolated from a Mangrove Sediment on Acrylamide. Asian Journal of Plant Biology, 4(2), 8–15. https://doi.org/10.54987/ajpb.v4i2.783

Issue

Section

Articles