Modeling the bioconversion of starch to P(HB-co-HV) optimized by experimental design using Bacillus megaterium BBST4 strain

Abstract

Poly(hydroxybutyrate-co-hydroxyvalerate) (P(HB-co-HV)) is a prominent biopolymer as a potential candidate for use in the biomedical area. Several Bacillus spp. strains show promising characteristics in the use of several carbon sources and are an interesting alternative for the production of P(HB-co-HV). Sewage from the agricultural and food processing industries can be used to obtain abundantly starch as a carbon source for PHA production. The aim of the present study was to optimize by response surface methodology and desirability, the production of PHA by a Bacillus megaterium strain using starch as the sole carbon source. Two optimal conditions were determined without sporulation and were used to perform new experiments to calibrate and validate a mechanistic model, developed to simulate the dynamics of PHA and biomass production. The developed model successfully represents the kinetics of the microorganism. Employing different characterization techniques, it was determined that the PHA produced by the strain is a copolymer composed of different HB:HV proportions. Using starch as the sole carbon source in a minimal salt medium, this work shows the first reports in the literature of: 1) a mathematical model for predicting growth kinetic and PHA production for B. megaterium strain and 2) a Bacillus spp. producing P(HB-co-HV) copolymer.

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

“…Sucrose, diammonium hydrogen phosphate (i) At low carbon concentration, nitrogen was considered a growth-limiting factor r g1 Divyashree et al (2009) substrate concentration term with an N/C ratio (Penloglou et al, 2017). Assumed to be in excess, studies with nitrogen as the sole growth-limiting factor are rare in literature (Porras et al, 2019).…”

“…T A B L E 3 Parameter estimation and quality indicators for dynamic models adopted in PHA production In absence of a unified approach to reporting model fitness, the reliability of parameters from small experimental data without external validation and other quality attributes is questionable (Porras et al, 2019). In some cases, the entire set of model parameters is recurrently recalibrated from separate batch experiments with different substrate concentrations (Elsayed et al, 2019;Makhdum Munawar et al, 2016;Yang et al, 2006;Zafar et al, 2014).…”

“…Single or multiple substrates (carbon and/or nitrogen source) controlled growth with or without consideration of substrate or product inhibition (J. Wang et al, 2021) have widely been adopted in studies. Microkinetic assumptions across literature also vary, that is, whether considering (i) nitrogen inhibition on PHA (Horvat et al, 2013; Xu et al, 2019), (ii) use of nitrogen and oxygen for growth, and maintenance (Diniz et al, 2004; Porras et al, 2019), (iii) growth inhibition by PHA, or (iv) use of PHA for cell maintenance (Basak et al, 2019; Fang et al, 2019). Though structural and operational variabilities in modelling approaches are obvious, the strategy or justification for model selection, parameter identifiability, and mathematical reliability (discontinuity, asymptotic behaviour) is not always evident.…”

Assessing the environmental sustainability of glucose from wheat as a fermentation feedstock

“…Furthermore, data on mass values and market prices were retrieved from databases (Durlinger et al, 2017). The price of glucose was assumed to be twice the price of starch (Porras et al, 2018). Energy-based allocation was disregarded since the product (glucose) and by-products (bran, wheat gluten feed and meal) of this study are not intended to be used for energy production (i.e.…”

Animal fat and glycerol bioconversion to polyhydroxyalkanoate by produced water bacteria

“…Some approaches include use of low cost resources (6,15), use of biomass as feedstock, use of organic wastes as carbon source (18,19), use of genetic manipulation and recombinant methodologies. Use of process control strategies has also been employed to increase PHA production (18,20). Recent studies have also focused on manipulating biosynthetic pathways of production either to increase production (21) or to produce novel product (17,22).…”