Improved production of RNA-inhibiting antimicrobial peptide by Bacillus licheniformis MCC 2514 facilitated by a genetic algorithm optimized medium

One of the significant challenges during the purification and characterization of antimicrobial peptides (AMPs) from Bacillus sp. is the interference of unutilized peptides from complex medium components during analytical procedures. In this study, a semi-synthetic medium was devised to overcome this challenge. Using a genetic algorithm, the production medium of AMP is optimized. The parent organism, Bacillus licheniformis MCC2514, produces AMP in very small quantities. This AMP is known to inhibit RNA biosynthesis. The findings revealed that lactose, NH4Cl and NaNO3 were crucial medium constituents for enhanced AMP synthesis. The potency of the AMP produced was studied using bacterium, Kocuria rhizophila ATCC 9341. The AMP produced from the optimized medium was eightfold higher than that produced from the unoptimized medium. Furthermore, activity was increased by 1.5-fold when cultivation conditions were standardized using the optimized medium. Later, AMP was produced in a 5 L bioreactor under controlled conditions, which led to similar results as those of shake-flask production. The mode of action of optimally produced AMP was confirmed to be inhibition of RNA biosynthesis. Here, we demonstrate that improved production of AMP is possible with the developed semi-synthetic medium recipe and could help further AMP production in an industrial setup.

Rapid detection of sunset yellow adulteration in tea powder with variable selection coupled to machine learning tools using spectral data

In the present study sunset yellow (SY), a synthetic colour, which is a common adulterant in tea powders has been analysed using FT-IR spectral data coupled to machine learning tools for efficient classification and quantification of the SY adulteration. Earlier established real coded genetic algorithm (RCGA) was used as variable selection method to predict the key fingerprints of SY in the FT-IR spectra. Here, RCGA was used to select 20, 30, 40, 50 and 60 characteristic wavenumbers for SY. Classification was carried using support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGB) classifiers. SVM classifier using 50 variables could give an accuracy of 0.90 amongst the three. Quantification of SY based on PLS (partial least squares), LS-SVM (least squares-SVM), RF and XGBoost were built on characteristic wavenumbers. Both RF and LS-SVM models were observed to be superior to PLS when coupled to RCGA obtained 20 fingerprint variables. Overall, RCGA-LS-SVM model resulted in lowest RMSECV (0.1956) with regression co-efficient values RC 2 = 0.9989 and RP 2 = 0.9979, when 50 fingerprint variables were used. These results demonstrated that FT-IR combined with RCGA-LS-SVM procedure could be a robust technique for rapid detection of SY in tea powder.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05694-3.

In silico target-based strain engineering of Saccharomyces cerevisiae for terpene precursor improvement

Systems-based metabolic engineering enables cells to enhance product formation by predicting gene knockout and overexpression targets using modeling tools. FOCuS, a novel metaheuristic tool, was used to predict flux improvement targets in terpenoid pathway using the genome-scale model of Saccharomyces cerevisiae, iMM904. Some of the key knockout target predicted includes LYS1, GAP1, AAT1, AAT2, TH17, KGD-m, MET14, PDC1 and ACO1. It was also observed that the knockout reactions belonged either to fatty acid biosynthesis, amino acid synthesis pathways or nucleotide biosynthesis pathways. Similarly, overexpression targets such as PFK1, FBA1, ZWF1, TDH1, PYC1, ALD6, TPI1, PDX1 and ENO1 were established using three different existing gene amplification algorithms. Most of the overexpression targets belonged to glycolytic and pentose phosphate pathways. Each of these targets had plausible role for improving flux toward sterol pathway and were seemingly not artifacts. Moreover, an in vitro study as validation was carried with overexpression of ALD6 and TPI1. It was found that there was an increase in squalene synthesis by 2.23- and 4.24- folds, respectively, when compared with control. In general, the rationale for predicting these in silico targets was attributed to either increasing the acetyl-CoA precursor pool or regeneration of NADPH, which increase the sterol pathway flux.

Alternative splicing regulates the α-glucosidase synthesis in Aspergillus neoniger NCIM 1400

Aspergillus neoniger NCIM 1400 whose cell-free fraction was earlier established for transglycosylation activity conferred by α-glucosidase gene (agdA), was subjected to sequence analysis. Preliminary results revealed certain dynamics in the intron splicing mechanism, and to ascertain these molecular events, a detailed study was carried. The electrophoresis results from the cDNA portion (B-fragment) of agdA showed multiple bands, indicating the amplification of one or more fragments. The sequence results of cDNA cloned vector revealed the retention type of alternative splicing in the agdA. The splicing mechanism of agdA in NCIM 1400 was compared to different A. niger strains, which harbours agdA orthologues, using PCR. It was observed that effective intron splicing leads to higher α-glucosidase activity from these selected Aspergillus spp. To explore the dynamics of intron retention in A. neoniger NCIM 1400, time-course analysis of intron retention, enzyme activity, and sugar consumption were carried over a period of 168 h of fungal growth. RT-qPCR results revealed that introns retention was not detected during the initial growth phase when the maltose and its hydrolysed product, glucose were consumed. Here we demonstrate that exhaustion of maltose causes increase in retention of introns in the mRNA transcripts of agdA gene, and this could be the possible mode of regulating this gene.

Adaptive evolution of engineered yeast for squalene production improvement and its genome-wide analysis

In the present study, the adaptive evolution of a metabolically engineered Saccharomyces cerevisiae strain in the presence of an enzyme inhibitor terbinafine for enhanced squalene accumulation via serial transfer leads to the development of robust strains. After adaptation for nearly 1500 h, a strain with higher squalene production efficiency was identified at a specific growth rate of 0.28 h^-1 with a final squalene titer of 193 mg/L, which is 16.5-fold higher than the BY4741 and 3-fold higher over the metabolically engineered SK22 strain. Whole-genome sequencing comparison between the reference strain and the evolved variant SK23 has led to the identification of 462 single-nucleotide variants (SNVs) between both strains, with 102 SNVs affecting metabolism-related genes. It was also established that F420I mutation of ERG1 in S. cerevisiae improves squalene synthesis. Further, the effect of increased squalene on lipid droplet and neutral lipid pattern in the evolved mutant strains was investigated by fluorescent techniques proving that the neutral lipid content and clustering of lipid droplets increase with an increase in squalene.

Dynamic optimization of fed-batch bioprocesses using flower pollination algorithm

There exist several optimization strategies such as sequential quadratic programming (SQP), iterative dynamic programing (IDP), stochastic-based methods such as differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSA), and ant colony optimization (ACO) for finding optimal feeding profile(s) during fed-batch fermentations. Here in the present study, flower pollination algorithm (FPA) which is inspired by the pollination process in terrestrial flowering plants has been used for the first time to find the optimal feeding profile(s) during fed-batch fermentations. Single control variable, two control variables and state variable bounded problems were chosen to test the robustness of the FPA for optimal control problems. It was observed that FPA is computationally less intensive in comparison with other stochastic strategies. Thus, obtained results were compared to other studies and it has been found that the FPA converged either to newer optima or closer to the established global optimum for the cases studied.

FOCuS: a metaheuristic algorithm for computing knockouts from genome-scale models for strain optimization

Although handful tools are available for constraint-based flux analysis to generate knockout strains, most of these are either based on bilevel-MIP or its modifications. However, metaheuristic approaches that are known for their flexibility and scalability have been less studied. Moreover, in the existing tools, sectioning of search space to find optimal knocks has not been considered. Herein, a novel computational procedure, termed as FOCuS (Flower-pOllination coupled Clonal Selection algorithm), was developed to find the optimal reaction knockouts from a metabolic network to maximize the production of specific metabolites. FOCuS derives its benefits from nature-inspired flower pollination algorithm and artificial immune system-inspired clonal selection algorithm to converge to an optimal solution. To evaluate the performance of FOCuS, reported results obtained from both MIP and other metaheuristic-based tools were compared in selected case studies. The results demonstrated the robustness of FOCuS irrespective of the size of metabolic network and number of knockouts. Moreover, sectioning of search space coupled with pooling of priority reactions based on their contribution to objective function for generating smaller search space significantly reduced the computational time.

Regeneration of NADPH Coupled with HMG-CoA Reductase Activity Increases Squalene Synthesis in Saccharomyces cerevisiae

Although overexpression of the tHMG1 gene is a well-known strategy for terpene synthesis in Saccharomyces cerevisiae, the optimal level for tHMG1p has not been established. In the present study, it was observed that two copies of the tHMG1 gene on a dual gene expression cassette improved squalene synthesis in laboratory strain by 16.8-fold in comparison to single-copy expression. It was also observed that tHMG1p is limited by its cofactor (NADPH), as the overexpression of NADPH regenerating genes', viz., ZWF1 and POS5 (full length and without mitochondrial presequence), has led to its increased enzyme activity. Further, it was demonstrated that overexpression of full-length POS5 has improved squalene synthesis in cytosol. Finally, when tHMG1 and full-length POS5 were co-overexpressed there was a net 27.5-fold increase in squalene when compared to control strain. These results suggest novel strategies to increase squalene accumulation in S. cerevisiae.

Fed-Batch Strategies for Production of PHA Using a Native Isolate of Halomonas venusta KT832796 Strain

In this study, polyhydroxyalkanoates (PHA) accumulation by Halomonas venusta KT832796, a moderate halophilic bacteria isolated from marine source was studied. Both nutritional requirements and process parameters for submerged cultivation of the organism in bioreactor have been standardized. From the shake flask studies, glucose and ammonium citrate as carbon and nitrogen source produced maximum PHA at a ratio 20 with 3.52 g/L of dry cell weight and 70.56% of PHA content. However, ammonium sulfate as the nitrogen source was found to be more suitable for fed-batch cultivation. Several feeding strategies including pH-based fed-batch and variants of pulse feeding were studied to improve the PHA levels. pH-based feeding, although improved PHA level to 26 g/L, most of the carbon flux was diverted towards biomass formation; hence, the percent PHA was only 39.15% of the dry cell weight. Maximum PHA of 33.4 g/L, which corresponded to 88.12% of the dry cell, was obtained from high concentration single pulse method. There was a net 8.65-fold increase in PHA using this feeding strategy when compared to batch studies. According to our knowledge, this is the highest amount of PHA reported for a Halomonas venusta strain.

Modeling of enzymatic production of isomaltooligosaccharides: a mechanistic approach

In the current investigation the production of isomaltooligosaccharides (IMO) by transglucosylation of maltose using α-glucosidase was modeled by a mechanistic approach. Parameters are estimated by a genetic algorithm followed by sensitivity analysis and experimental validation.

Development of a D-xylose fermenting and inhibitor tolerant industrial Saccharomyces cerevisiae strain with high performance in lignocellulose hydrolysates using metabolic and evolutionary engineering

BACKGROUND

The production of bioethanol from lignocellulose hydrolysates requires a robust, D-xylose-fermenting and inhibitor-tolerant microorganism as catalyst. The purpose of the present work was to develop such a strain from a prime industrial yeast strain, Ethanol Red, used for bioethanol production.

RESULTS

An expression cassette containing 13 genes including Clostridium phytofermentans XylA, encoding D-xylose isomerase (XI), and enzymes of the pentose phosphate pathway was inserted in two copies in the genome of Ethanol Red. Subsequent EMS mutagenesis, genome shuffling and selection in D-xylose-enriched lignocellulose hydrolysate, followed by multiple rounds of evolutionary engineering in complex medium with D-xylose, gradually established efficient D-xylose fermentation. The best-performing strain, GS1.11-26, showed a maximum specific D-xylose consumption rate of 1.1 g/g DW/h in synthetic medium, with complete attenuation of 35 g/L D-xylose in about 17 h. In separate hydrolysis and fermentation of lignocellulose hydrolysates of Arundo donax (giant reed), spruce and a wheat straw/hay mixture, the maximum specific D-xylose consumption rate was 0.36, 0.23 and 1.1 g/g DW inoculum/h, and the final ethanol titer was 4.2, 3.9 and 5.8% (v/v), respectively. In simultaneous saccharification and fermentation of Arundo hydrolysate, GS1.11-26 produced 32% more ethanol than the parent strain Ethanol Red, due to efficient D-xylose utilization. The high D-xylose fermentation capacity was stable after extended growth in glucose. Cell extracts of strain GS1.11-26 displayed 17-fold higher XI activity compared to the parent strain, but overexpression of XI alone was not enough to establish D-xylose fermentation. The high D-xylose consumption rate was due to synergistic interaction between the high XI activity and one or more mutations in the genome. The GS1.11-26 had a partial respiratory defect causing a reduced aerobic growth rate.

CONCLUSIONS

An industrial yeast strain for bioethanol production with lignocellulose hydrolysates has been developed in the genetic background of a strain widely used for commercial bioethanol production. The strain uses glucose and D-xylose with high consumption rates and partial cofermentation in various lignocellulose hydrolysates with very high ethanol yield. The GS1.11-26 strain shows highly promising potential for further development of an all-round robust yeast strain for efficient fermentation of various lignocellulose hydrolysates.