Multi-objective optimization of bioethanol production during cold enzyme starch hydrolysis in very high gravity cassava mash

Simultaneous manipulation of transcriptional regulator CxrC and translational elongation factor eEF1A enhances the production of plant-biomass-degrading enzymes of Penicillium oxalicum

Genetic engineering is an efficient approach to improve fungal bioproducts, but the specific targets are limited. In this study, it was found that the key transcription repressor CxrC of Penicillium oxalicum could physically interact with the translational elongation factor eEF1A that positively regulated the production of plant-biomass-degrading enzymes by the fungus under Avicel induction. Simultaneously deletion of the cxrC and overexpression of the eEF1A in the strain Δku70 resulted in 55.4%-314.6% higher production of cellulase, xylanase and raw-starch-degrading enzymes than that of the start strain Δku70. Transcript abundance of the genes encoding predominant cellulases, xylanases and raw-starch-degrading enzymes were significantly upregulated in the mutant ΔcxrC::eEF1A. The ΔcxrC::eEF1A enhanced saccharification efficiency of raw cassava flour by 9.3%-15.5% at early-middle stage of hydrolysis in comparison with Δku70. The obtained knowledges expanded the sources used as effective targets for increased production of plant-biomass-degrading enzymes by fungi.

Characterization of SdGA, a cold-adapted glucoamylase from Saccharophagus degradans

We investigated the structural and functional properties of SdGA, a glucoamylase (GA) from Saccharophagus degradans, a marine bacterium which degrades different complex polysaccharides at high rate. SdGA is composed mainly by a N-terminal GH15_N domain linked to a C-terminal catalytic domain (CD) found in the GH15 family of glycosylhydrolases with an overall structure similar to other bacterial GAs. The protein was expressed in Escherichia coli cells, purified and its biochemical properties were investigated. Although SdGA has a maximum activity at 39 °C and pH 6.0, it also shows high activity in a wide range, from low to mild temperatures, like cold-adapted enzymes. Furthermore, SdGA has a higher content of flexible residues and a larger CD due to various amino acid insertions compared to other thermostable GAs. We propose that this novel SdGA, is a cold-adapted enzyme that might be suitable for use in different industrial processes that require enzymes which act at low or medium temperatures.

Consolidated bioprocessing of raw starch to ethanol by Saccharomyces cerevisiae: Achievements and challenges

Recent advances in amylolytic strain engineering for starch-to-ethanol conversion have provided a platform for the development of raw starch consolidated bioprocessing (CBP) technologies. Several proof-of-concept studies identified improved enzyme combinations, alternative feedstocks and novel host strains for evaluation and application under fermentation conditions. However, further research efforts are required before this technology can be scaled up to an industrial level. In this review, different CBP approaches are defined and discussed, also highlighting the role of auxiliary enzymes for a supplemented CBP process. Various achievements in the development of amylolytic Saccharomyces cerevisiae strains for CBP of raw starch and the remaining challenges that need to be tackled/pursued to bring yeast raw starch CBP to industrial realization, are described. Looking towards the future, it provides potential solutions to develop more cost-effective processes that include cheaper substrates, integration of the 1G and 2G economies and implementing a biorefinery concept where high-value products are also derived from starchy substrates.

Purification and characterization of a novel cold adapted fungal glucoamylase

Background

Amylases are used in various industrial processes and a key requirement for the efficiency of these processes is the use of enzymes with high catalytic activity at ambient temperature. Unfortunately, most amylases isolated from bacteria and filamentous fungi have optimal activity above 45 °C and low pH. For example, the most commonly used industrial glucoamylases, a type of amylase that degrades starch to glucose, are produced by Aspergillus strains displaying optimal activities at 45–60 °C. Thus, isolating new amylases with optimal activity at ambient temperature is essential for improving industrial processes. In this report, a glucoamylase secreted by the cold-adapted yeast Tetracladium sp. was isolated and biochemically characterized.

Results

The effects of physicochemical parameters on enzyme activity were analyzed, and pH and temperature were found to be key factors modulating the glucoamylase activity. The optimal conditions for enzyme activity were 30 °C and pH 6.0, and the K_m and k_cat using soluble starch as substrate were 4.5 g/L and 45 min⁻¹, respectively. Possible amylase or glucoamylase encoding genes were identified, and their transcript levels using glucose or soluble starch as the sole carbon source were analyzed. Transcription levels were highest in medium supplemented with soluble starch for the potential glucoamylase encoding gene. Comparison of the structural model of the identified Tetracladium sp. glucoamylase with the solved structure of the Hypocrea jecorina glucoamylase revealed unique structural features that may explain the thermal lability of the glucoamylase from Tetracladium sp.

Conclusion

The glucoamylase secreted by Tetracladium sp. is a novel cold-adapted enzyme and its properties should render this enzyme suitable for use in industrial processes that require cold-active amylases, such as biofuel production.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-017-0693-x) contains supplementary material, which is available to authorized users.

Screening and characterization of amylase and cellulase activities in psychrotolerant yeasts

Background

Amylases and cellulases have great potential for application in industries such as food, detergent, laundry, textile, baking and biofuels. A common requirement in these fields is to reduce the temperatures of the processes, leading to a continuous search for microorganisms that secrete cold-active amylases and cellulases. Psychrotolerant yeasts are good candidates because they inhabit cold-environments. In this work, we analyzed the ability of yeasts isolated from the Antarctic region to grow on starch or carboxymethylcellulose, and their potential extracellular amylases and cellulases.

Result

All tested yeasts were able to grow with soluble starch or carboxymethylcellulose as the sole carbon source; however, not all of them produced ethanol by fermentation of these carbon sources. For the majority of the yeast species, the extracellular amylase or cellulase activity was higher when cultured in medium supplemented with glucose rather than with soluble starch or carboxymethylcellulose. Additionally, higher amylase activities were observed when tested at pH 5.4 and 6.2, and at 30–37 °C, except for Rhodotorula glacialis that showed elevated activity at 10–22 °C. In general, cellulase activity was high until pH 6.2 and between 22–37 °C, while the sample from Mrakia blollopis showed high activity at 4–22 °C. Peptide mass fingerprinting analysis of a potential amylase from Tetracladium sp. of about 70 kDa, showed several peptides with positive matches with glucoamylases from other fungi.

Conclusions

Almost all yeast species showed extracellular amylase or cellulase activity, and an inducing effect by the respective substrate was observed in a minor number of yeasts. These enzymatic activities were higher at 30 °C in most yeast, with highest amylase and cellulase activity in Tetracladium sp. and M. gelida, respectively. However, Rh. glacialis and M. blollopis displayed high amylase or cellulase activity, respectively, under 22 °C. In this sense, these yeasts are interesting candidates for industrial processes that require lower temperatures.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0640-8) contains supplementary material, which is available to authorized users.

Efficient co-displaying and artificial ratio control of α-amylase and glucoamylase on the yeast cell surface by using combinations of different anchoring domains

Recombinant yeast strains that display heterologous amylolytic enzymes on their cell surface via the glycosylphosphatidylinositol (GPI)-anchoring system are considered as promising biocatalysts for direct ethanol production from starchy materials. For the effective hydrolysis of these materials, the ratio optimization of multienzyme activity displayed on the cell surface is important. In this study, we have presented a ratio control system of multienzymes displayed on the yeast cell surface by using different GPI-anchoring domains. The novel gene cassettes for the cell-surface display of Streptococcus bovis α-amylase and Rhizopus oryzae glucoamylase were constructed using the Saccharomyces cerevisiae SED1 promoter and two different GPI-anchoring regions derived from Saccharomyces cerevisiae SED1 or SAG1. These gene cassettes were integrated into the Saccharomyces cerevisiae genome in different combinations. Then, the cell-surface α-amylase and glucoamylase activities and ethanol productivity of these recombinant strains were evaluated. The combinations of the gene cassettes of these enzymes affected the ratio of cell-surface α-amylase and glucoamylase activities and ethanol productivity of the recombinant strains. The highest ethanol productivity from raw starch was achieved by the strain harboring one α-amylase gene cassette carrying the SED1-anchoring region and two glucoamylase gene cassettes carrying the SED1-anchoring region (BY-AASS/GASS/GASS). This strain yielded 22.5 ± 0.6 g/L of ethanol from 100 g/L of raw starch in 120 h of fermentation.

An algorithmic framework for multiobjective optimization

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.

Application of an integrated statistical design for optimization of culture condition for ammonium removal by Nitrosomonas europaea

Statistical methodology was applied to the optimization of the ammonium oxidation by Nitrosomonas europaea for biomass concentration (C_B), nitrite yield (Y_N) and ammonium removal (R_A). Initial screening by Plackett-Burman design was performed to select major variables out of nineteen factors, among which NH₄Cl concentration (C_N), trace element solution (TES), agitation speed (AS), and fermentation time (T) were found to have significant effects. Path of steepest ascent and response surface methodology was applied to optimize the levels of the selected factors. Finally, multi-objective optimization was used to obtain optimal condition by compromise of the three desirable objectives through a combination of weighted coefficient method coupled with entropy measurement methodology. These models enabled us to identify the optimum operation conditions (C_N = 84.1 mM; TES = 0.74 ml; AS = 100 rpm and T = 78 h), under which C_B = 3.386×10⁸ cells/ml; Y_N = 1.98 mg/mg and R_A = 97.76% were simultaneously obtained. The optimized conditions were shown to be feasible through verification tests.