Multilevel algorithms and evolutionary hybrid tools for enhanced production of arginine deiminase from Pseudomonas furukawaii RS3

Dhankhar, Rakhi; Kumar, Ashwani; Kumar, Sanjay; Chhabra, Deepak; Shukla, Pratyoosh; Gulati, Pooja

doi:10.1016/j.biortech.2019.121789

Cited by 25 publications

(13 citation statements)

References 26 publications

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“…The ANFIS is a statistical approach for data handling, which gets its origin from biological neurons and the gene theory of evolution, providing an efficient convergence criterion of hiding nodes that results in fitting of a realistic function. The prediction model in current study was highly authentic and best fit, with the appreciable RMSE (2.5258 and 2.4718) and R values of 0.9995 and 0.9986 for L. reuteri F2 and L. rhamnosus F5, respectively, as suggested by others ( Dhankhar et al, 2019 ). The ANFIS training and testing performance FIS plots and structure plots can be seen in Fig.…”

Section: Resultssupporting

confidence: 80%

“…4 . Other researchers have also reported ANFIS prediction alone (or in combination with GSD designing) as accurate tool for optimization, prediction and validation of biological processes with high R values of 0.957 ( Pérez et al, 2018 ), 0.99 ( Dhankhar et al, 2019 ) and 0.9951 ( Karri et al, 2021 ). With promising results on bioproduction and sensory (data not shown), the optimized B12 biofortification process may be considered viable on industrial, economic and environmental scales ( Pérez et al, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

“…For a complex biological system like food fermentation, the optimal design of experiments becomes a tedious proposition to ascertain invariability and to improve effectiveness, especially while negotiating with multilevel factors ( Surowiec et al, 2017 ; Bhushan et al, 2021 ). Besides the traditional and versatile use of one factor at a time (OFAT) approach due to its simplicity ( Dhankhar et al, 2019 ), the use of generalized subset designs (GSD) has been suggested as a powerful tool to customize the experimental combinations ( Surowiec et al, 2017 ). Further, the Adaptive Neuro Fuzzy Inference System (ANFIS), a combination of a learning tool (Artificial Neural Network) and a robust system (Fuzzy Logic), may predict the effectiveness of statistical experimental designing, the maximal production levels of targeted biomolecule and the interrelationships among fermentation variables.…”

Section: Introductionmentioning

confidence: 99%

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Vitamin B12 biofortification of soymilk through optimized fermentation with extracellular B12 producing Lactobacillus isolates of human fecal origin

Kumari

Bhushan

Kokkiligadda

et al. 2021

Current Research in Food Science

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The present study was designed to bio-fortify the soymilk ( per se a B12-free plant food matrix). The PCR-based screening characterized the human fecal samples (4 out of 15 tested) and correspondingly identified novel lactobacilli isolates (n = 4) for their B12 production potential and rest (n = 62) as negative for this attribute. Further, 3 out of the 4 selected strains showed ability for extracellular vitamin production. The most prolific strain, Lactobacillus reuteri F2, secreted B12 (132.2 ± 1.9 μg/L) in cobalamin-free-medium with the highest ratio ever reported (0.97:1.00; extra-: intra-cellular). In next stage, the soymilk was biofortified in situ with B12 during un-optimized (2.8 ± 0.3 μg/L) and optimized (156.2 ± 3.6 μg/L) fermentations with a ∼54-fold increase at Artificial Neuro Fuzzy Inference System based R value of >0.99. The added-nutrients, temperature and initial-pH were observed to be the most important fermentation variables for maximal B12 biofortification. We report Lactobacillus rhamnosus F5 as the first B12 producing (101.7 ± 3.4 μg/L) strain from this species. The cyanocobalamin was extracted, purified and separated on UFLC as nutritionally-relevant B12. Besides, the vitamin was bioavailable in an auxotrophic-mutant. The lactobacilli fermentation is suggested, therefore, as an effective approach for B12 biofortification of soymilk.

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Section: Resultssupporting

confidence: 80%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vitamin B12 biofortification of soymilk through optimized fermentation with extracellular B12 producing Lactobacillus isolates of human fecal origin

Kumari

Bhushan

Kokkiligadda

et al. 2021

Current Research in Food Science

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“…Both of these artificial learning tools, namely ANN and ANFIS, have been successfully applied to biological systems as well as optimization of bioprocesses [21]. Several studies have reported process optimization by either ANN or ANFIS tools for the production of enzymes, explicitly protease [22], laccase [23], polygalactonase [24], arginine deaminase [25], and hydantoinase [19]. A limited number of studies has explored the feasibility of hybrid, non-linear modeling techniques with fermentation processes.…”

Section: Introductionmentioning

confidence: 99%

Improved Pullulan Production and Process Optimization Using Novel GA–ANN and GA–ANFIS Hybrid Statistical Tools

et al. 2020

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Pullulan production from Aureobasidium pullulans was explored to increase yield. Non-linear hybrid mathematical tools for optimization of process variables as well as the pullulan yield were analyzed. The one variable at a time (OVAT) approach was used to optimize the maximum pullulan yield of 35.16 ± 0.29 g/L. The tools predicted maximum pullulan yields of 39.4918 g/L (genetic algorithm coupled with artificial neural network (GA–ANN)) and 36.0788 g/L (GA coupled with adaptive network based fuzzy inference system (GA–ANFIS)). The best regression value (0.94799) of the Levenberg–Marquardt (LM) algorithm for ANN and the epoch error (6.1055 × 10−5) for GA–ANFIS point towards prediction precision and potentiality of data training models. The process parameters provided by both the tools corresponding to their predicted yield were revalidated by experiments. Among the two of them GA–ANFIS results were replicated with 98.82% accuracy. Thus GA–ANFIS predicted an optimum pullulan yield of 36.0788 g/L with a substrate concentration of 49.94 g/L, incubation period of 182.39 h, temperature of 27.41 °C, pH of 6.99, and agitation speed of 190.08 rpm.

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“…With the purpose of identifying potent anticancer ADI, in our previous work, we have screened bacterial isolates from environmental samples and identi ed Pseudomonas furukawaii as an alternate source of ADI with optimum activity at human physiological conditions [14]. In this study, the arcA gene (gene coding ADI) of P. furukawaii was cloned and expressed in Escherichia coli.…”

Section: Introductionmentioning

confidence: 99%

In Vitro and in Silico Analysis of Recombinant Arginine Deiminase from Pseudomonas Furukawaii as a Potential Anticancer Enzyme

Dhankhar

Gupta

Mohanty

et al. 2021

Preprint

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Arginine deiminase (ADI) is a promising anti-tumor enzyme that can be employed in amino acid deprivation therapy for the treatment of various arginine auxotrophic tumors. In our previous work, Pseudomonas furukawaii was identified as a potent producer of ADI with optimum activity at physiological pH and temperature. In this study ADI coding arcA gene was cloned and expressed in E. coli BL21. Recombinant ADI of P. furukawaii (PfADI) was purified using affinity chromatography and its molecular mass was estimated to be ~46KDa. PfADI was found to effectively inhibit the HepG2 cells with an IC50 value of 0.1950 IU/ml which is lower than the IC50 value of Mycoplasma hominis ADI (MhADI) which is in phase III clinical trials. The 3D structure of PfADI was modeled. Immunoinformatics analysis was also carried out to compare the immunogenicity of PfADI with MhADI. The PfADI was found to be less immunogenic in terms of number of linear and conformational B cell epitopes and T cell epitope density. The overall antigenicity and allergenicity of PfADI was also lower as compared to MhADI. Thus the present in vitro and in silico studies establish PfADI as a potential anticancer drug candidate with improved efficacy and low immunogenicity.

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Multilevel algorithms and evolutionary hybrid tools for enhanced production of arginine deiminase from Pseudomonas furukawaii RS3

Cited by 25 publications

References 26 publications

Vitamin B12 biofortification of soymilk through optimized fermentation with extracellular B12 producing Lactobacillus isolates of human fecal origin

Vitamin B12 biofortification of soymilk through optimized fermentation with extracellular B12 producing Lactobacillus isolates of human fecal origin

Improved Pullulan Production and Process Optimization Using Novel GA–ANN and GA–ANFIS Hybrid Statistical Tools

In Vitro and in Silico Analysis of Recombinant Arginine Deiminase from Pseudomonas Furukawaii as a Potential Anticancer Enzyme

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