Mutagenesis enhances gellan gum production by a novel Sphingomonas spp: upstream optimization, kinetic modeling, and structural and physico-functional evaluation / La mutagénesis mejora la producción de goma gellan mediante una nueva especie de Sphingomonas: optimización ascendente, modelado cinético y evaluación estructural y físico-funcional

Gellan gum (GG) has gained tremendous attention owing to its diversified applications. However, its high production and hence market cost are still a bottleneck in its widespread utilization. In the present study, high GG producing mutant of Sphingomonas spp. was developed by random mutagenesis using ethyl methylsulphonate (EMS) for industrial fermentation and identified as Sphingomonas trueperi after 16S rRNA and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF–MS) analysis. The fermentation conditions such as pH, temperature, and inoculum ratio were optimized by one factor at a time (OFAT) followed by screening of medium components by the Plackett–Burman statistical design. The most critical nutrients were further optimized by response surface methodology for maximizing GG production. The effect of dissolved oxygen tension in bioreactor on cell growth, substrate consumption, GG production, and batch productivity was elucidated. The highest GG titer (23 ± 2.4 g/L) was attained in optimized medium at 10% inoculum (6.45 ± 0.5 log cfu/mL) under controlled fermentation conditions of pH (7), temperature (30 °C), agitation (300–600 rpm), and aeration (0.5–2.0 SLPM) at 22 ± 2% dissolved oxygen tension in a 10-L bioreactor. Kinetic modeling of optimized batch process revealed that logistic growth model could best explain biomass accumulation, while GG formation and substrate consumption were best explained by Luedeking-Piret and exponential decay model, respectively. Structural and physico-functional features of GG produced by mutant Sphingomonas spp. were characterized by HPLC, FTIR, NMR, DSC, TGA, GPC, SEM, and rheological analysis. The higher productivity (0.51 g/L/h) under optimized fermentation conditions suggests potential consideration of mutant and process for commercial utilization.(AU)

Mutagenesis enhances gellan gum production by a novel Sphingomonas spp.: upstream optimization, kinetic modeling, and structural and physico-functional evaluation.

Gellan gum (GG) has gained tremendous attention owing to its diversified applications. However, its high production and hence market cost are still a bottleneck in its widespread utilization. In the present study, high GG producing mutant of Sphingomonas spp. was developed by random mutagenesis using ethyl methylsulphonate (EMS) for industrial fermentation and identified as Sphingomonas trueperi after 16S rRNA and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) analysis. The fermentation conditions such as pH, temperature, and inoculum ratio were optimized by one factor at a time (OFAT) followed by screening of medium components by the Plackett-Burman statistical design. The most critical nutrients were further optimized by response surface methodology for maximizing GG production. The effect of dissolved oxygen tension in bioreactor on cell growth, substrate consumption, GG production, and batch productivity was elucidated. The highest GG titer (23 ± 2.4 g/L) was attained in optimized medium at 10% inoculum (6.45 ± 0.5 log cfu/mL) under controlled fermentation conditions of pH (7), temperature (30 °C), agitation (300-600 rpm), and aeration (0.5-2.0 SLPM) at 22 ± 2% dissolved oxygen tension in a 10-L bioreactor. Kinetic modeling of optimized batch process revealed that logistic growth model could best explain biomass accumulation, while GG formation and substrate consumption were best explained by Luedeking-Piret and exponential decay model, respectively. Structural and physico-functional features of GG produced by mutant Sphingomonas spp. were characterized by HPLC, FTIR, NMR, DSC, TGA, GPC, SEM, and rheological analysis. The higher productivity (0.51 g/L/h) under optimized fermentation conditions suggests potential consideration of mutant and process for commercial utilization.

Advances in fermentative production, purification, characterization and applications of gellan gum.

Multiple microbial exopolysaccharides have been reported in recent decade with their structural and functional features. Gellan gum (GG) is among these emerging biopolymers with versatile properties. Low production yield, high downstream cost, and abundant market demand have made GG a high cost material. Hence, an understanding on the various possibilities to develop cost-effective gellan gum bioprocess is desirable. This review focuses on details of upstream and downstream process of GG from an industrial perspective. It emphasizes on GG producing Sphingomonas spp., updates on biosynthesis, strain and media engineering, kinetic modeling, bioreactor design and scale-up considerations. Details of the downstream operations with possible modifications to make it cost-effective and environmentally sustainable have been discussed. The updated regulatory criteria for GG as a food ingredient and analytical tools required to validate the same have been briefly discussed. Derivatives of GG and their applications in various industrial segments have also been highlighted.

Cross-linked ß-Mannanase Aggregates: Preparation, Characterization, and Application for Producing Partially Hydrolyzed Guar Gum.

ß-Mannanase capable of hydrolyzing ß-1,4-linkages in guar gum was immobilized as cross-linked enzyme aggregates (M-CLEAs). The aggregation and cross-linking process was optimized by response surface methodology (RSM) for maximum activity. The resulting M-CLEAs were characterized by FTIR, DSC, SEM, and SDS-PAGE. The M-CLEAs showed higher pH stability, improved thermal and storage stability, and reusability than free ß-mannanase. For example, M-CLEAs were stable over broader pH range (5.5-8.5) with highest relative of activity of 98.17% at pH 6.5 and retained almost double activity than free mannanase at 50 °C after 4 h. Moreover, Km and Vmax of M-CLEAs were altered significantly, with a 1.5-fold increase and 0.98-fold decrease, respectively, than free ß-mannanase. The prepared M-CLEAs could hydrolyze native guar gum (MW = 588,147 Da) to yield partially hydrolyzed guar gum (PHGG) (MW = 8023 Da).

Combined effect of attrition and ultrasound on the disruption of Pseudomonas putida for the efficient release of arginine deiminase.

Disruption of Pseudomonas putida KT2440 by ultrasound treatment in a bath sonicator, in presence of the glass beads, was carried out for the release of arginine deiminase (ADI) and the results were compared with that of by Dyno-mill. The release of ADI depended mainly on the bead size and cellmass concentration being disrupted in bead mill. Nearly 23 U mL-1 ADI was released when slurry with a cell-mass concentration of 250 g L-1 was disintegrated for 9 min with 80% bead loading (0.25 mm) in Dyno-mill. Marginally higher amount of ADI (24.1 U mL-1 ) was released by the bath sonication of 250 g L-1 cellmass slurry for 30 min with the beads (0.1 mm) and a sonication power of 170 W. The glass beads, suspended along with the cellmass slurry in bath sonicator, efficiently disrupted the microbial cells to release ADI. Variation in the kinetic constants for the performance parameters implied that ADI release and cell disruption kinetics is a function of disruption technique used and the process variables thereof. Estimation of location factor suggested that selective release of ADI can be achieved. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 2018 © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1185-1194, 2018.

Ultrasonic disruption of Pseudomonas putida for the release of arginine deiminase: Kinetics and predictive models.

The responses of the ultrasound-mediated disruption of Pseudomonas putida KT2440 were modelled as the function of biomass concentration in the cell suspension; the treatment time of sonication; the duty cycle and the acoustic power of the sonicator. For the experimental data, the response surface (RSM), the artificial neural network (ANN) and the support vector machine (SVM) models were compared for their ability to predict the performance parameters. The satisfactory prediction of the unseen data of the responses implied the proficient generalization capabilities of ANN. The extent of the cell disruption was mainly dependent on the acoustic power and the biomass concentration. The cellmass concentration in the slurry most strongly influenced the ADI and total protein release. Nearly 28U/mL ADI was released when a biomass concentration of 300g/L was sonicated for 6min with an acoustic power of 187.5W at 40% duty cycle. Cell disruption obeyed first-order kinetics.