Consolidated bioprocessing for bioethanol production by metabolically engineered cellulolytic fungus Myceliophthora thermophila

Investigation of the influence of Candida tropicalis on bioethanol production using sugarcane bagasse: stochastic and in silico analysis

This study investigated the impact of Candida tropicalis NITCSK13 on sugarcane bagasse (SCB) consolidated bioprocessing (CSB) using various parameters, such as pH, steam explosion (STEX) pretreatment, and temperature (at two different temperatures, cellulose hydrolysis and ethanol fermentation). The backpropagation neural network (BPNN) method simulated the optimal CSB conditions, achieving a maximum ethanol yield of 44 ± 0.32 g/L (0.443 g of ethanol/g of SCB) from STEX pretreated SCB within 48 h at 55 °C for cellulose hydrolysis and 33 °C for ethanol fermentation and pH 3.5. The simulated conditions were experimentally validated and showed an R2 value of 0.998 and absolute average deviation (AAD) of 1.23%. The strain NITCSK13 also exhibited a high ethanol tolerance of 16% (v/v). The interactions between the inhibitors, cellobiose, furfural, and thermocellulase were assessed through molecular docking. The results revealed a maximum inhibitory constant of 3.7 mM for furfural against the endoglucanase (EnG) of Humicola insolens (2ENG) at 50 °C. Acremonium chrysogenum endoglucanase (5M2D) exhibited a maximum of 88.7 µM for cellobiose at 50 °C. The SWISS homology model of EnG from Candida viswanathii exhibited inhibitory effects similar to those of EnG from Thermoascus and Thermotoga, indicating that the moderately thermophilic yeast Candida sp. cellulase may be capable of efficiently tolerating inhibitors and could be a promising candidate for consolidated bioprocessing of cellulosic ethanol.

Value-added biotransformation of agricultural byproducts by cellulolytic fungi: a review

Agricultural byproducts generally contain abundant bioactive compounds (e.g., cellulose/hemicellulose, phenolic compounds (PCs), and dietary fibers (DFs)), but most of them are neglected and underutilized. Owing to the complicated and rigid structures of agricultural byproducts, a considerable amount of bioactive compounds are entrapped in the polymer matrix, impeding their further development and utilization. In recent years, the prominent performance of cellulolytic fungi to grow and degrade agricultural byproducts has been applied to achieve efficient biotransformation of byproducts to high-value compounds, which is a green and sustainable strategy for the reutilization of agricultural byproducts. This review comprehensively summarizes recent progress in the value-added biotransformation of agricultural byproducts by cellulolytic fungi, including (1) direct utilization of agricultural byproducts for biochemicals and bioethanol production via a consolidated bioprocessing, (2) recovery and biotransformation of bounded PCs from agricultural byproducts for higher bioactive properties, as well as (3) modification and conversion of insoluble DF from agricultural byproducts to produce functional soluble DF. The functional enzymes, potential mechanisms, and metabolic pathways involved are emphasized. Moreover, promising advantages and current bottlenecks using cellulolytic fungi have also been elucidated, shedding further perspectives for sustainable and efficient reutilization of agricultural byproducts by cellulolytic fungi.

Construction of an enzyme-constrained metabolic network model for Myceliophthora thermophila using machine learning-based kcat data

BACKGROUND

Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have emerged as a valuable advancement, providing more accurate predictions and unveiling new engineering targets compared to models lacking enzyme constraints. In 2022, a stoichiometric GEM, iDL1450, was reconstructed for the industrially significant fungus Myceliophthora thermophila. To enhance the GEM's performance, an ecGEM was developed for M. thermophila in this study.

RESULTS

Initially, the model iDL1450 underwent refinement and updates, resulting in a new version named iYW1475. These updates included adjustments to biomass components, correction of gene-protein-reaction (GPR) rules, and a consensus on metabolites. Subsequently, the first ecGEM for M. thermophila was constructed using machine learning-based kcat data predicted by TurNuP within the ECMpy framework. During the construction, three versions of ecGEMs were developed based on three distinct kcat collection methods, namely AutoPACMEN, DLKcat and TurNuP. After comparison, the ecGEM constructed using TurNuP-predicted kcat values performed better in several aspects and was selected as the definitive version of ecGEM for M. thermophila (ecMTM). Comparing ecMTM to iYW1475, the solution space was reduced and the growth simulation results more closely resembled realistic cellular phenotypes. Metabolic adjustment simulated by ecMTM revealed a trade-off between biomass yield and enzyme usage efficiency at varying glucose uptake rates. Notably, hierarchical utilization of five carbon sources derived from plant biomass hydrolysis was accurately captured and explained by ecMTM. Furthermore, based on enzyme cost considerations, ecMTM successfully predicted reported targets for metabolic engineering modification and introduced some new potential targets for chemicals produced in M. thermophila.

CONCLUSIONS

In this study, the incorporation of enzyme constraint to iYW1475 not only improved prediction accuracy but also broadened the model's applicability. This research demonstrates the effectiveness of integrating of machine learning-based kcat data in the construction of ecGEMs especially in situations where there is limited measured enzyme kinetic parameters for a specific organism.

Fungal bioprocessing for circular bioeconomy: Exploring lignocellulosic waste valorization

The rising global demand for sustainable and eco-friendly practices has led to a burgeoning interest in circular bioeconomy, wherein waste materials are repurposed into valuable resources. Lignocellulosic waste, abundant in agricultural residues and forestry by-products, represents a significant untapped resource. This article explores the potential of fungal-mediated processes for the valorisation of lignocellulosic waste, highlighting their role in transforming these recalcitrant materials into bio-based products. The articles delve into the diverse enzymatic and metabolic capabilities of fungi, which enable them to efficiently degrade and metabolise lignocellulosic materials. The paper further highlights key fungal species and their mechanisms involved in the breakdown of complex biomass, emphasising the importance of understanding their intricate biochemical pathways for optimising waste conversion processes. The key insights of the article will significantly contribute to advancing the understanding of fungal biotechnology for circular bioeconomy applications, fostering a paradigm shift towards a more resource-efficient and environmentally friendly approach to waste management and bio-based product manufacturing.

A green pathway for lignin valorization: Enzymatic lignin depolymerization in biocompatible ionic liquids and deep eutectic solvents

Lignin depolymerization, which enables the breakdown of a complex and heterogeneous aromatic polymer into relatively uniform derivatives, serves as a critical process in valorization of lignin. Enzymatic lignin depolymerization has become a promising biological strategy to overcome the heterogeneity of lignin, due to its mild reaction conditions and high specificity. However, the low solubility of lignin compounds in aqueous environments prevents efficient lignin depolymerization by lignin-degrading enzymes. The employment of biocompatible ionic liquids (ILs) and deep eutectic solvents (DESs) in lignin fractionation has created a promising pathway to enzymatically depolymerize lignin within these green solvents to increase lignin solubility. In this review, recent research progress on enzymatic lignin depolymerization, particularly in a consolidated process involving ILs/DESs is summarized. In addition, the interactions between lignin-degrading enzymes and solvent systems are explored, and potential protein engineering methodology to improve the performance of lignin-degrading enzymes is discussed. Consolidation of enzymatic lignin depolymerization and biocompatible ILs/DESs paves a sustainable, efficient, and synergistic way to convert lignin into value-added products.

Reprogramming Metabolic Flux in Escherichia Coli to Enhance Chondroitin Production

Reprogramming metabolic flux is a promising approach for constructing efficient microbial cell factories (MCFs) to produce chemicals. However, how to boost the transmission efficiency of metabolic flux is still challenging in complex metabolic pathways. In this study, metabolic flux is systematically reprogrammed by regulating flux size, flux direction, and flux rate to build an efficient MCF for chondroitin production. The ammoniation pool for UDP-GalNAc synthesis and the carbonization pool for UDP-GlcA synthesis are first enlarged to increase flux size for providing enough precursors for chondroitin biosynthesis. Then, the ammoniation pool and the carbonization pool are rematched using molecular valves to shift flux direction from cell growth to chondroitin biosynthesis. Next, the adaptability of polymerization pool with the ammoniation and carbonization pools is fine-tuned by dynamic and static valve-based adapters to accelerate flux rate for polymerizing UDP-GalNAc and UDP-GlcA to produce chondroitin. Finally, the engineered strain E. coli F51 is able to produce 9.2 g L-1 chondroitin in a 5-L bioreactor. This strategy shown here provides a systematical approach for regulating metabolic flux in complex metabolic pathways for efficient biosynthesis of chemicals.

Development of an efficient protein expression system in the thermophilic fungus Myceliophthora thermophila

BACKGROUND

Thermophilic fungus Myceliophthora thermophila has been widely used in industrial applications due to its ability to produce various enzymes. However, the lack of an efficient protein expression system has limited its biotechnological applications.

RESULTS

In this study, using a laccase gene reporting system, we developed an efficient protein expression system in M. thermophila through the selection of strong constitutive promoters, 5'UTRs and signal peptides. The expression of the laccase was confirmed by enzyme activity assays. The results showed that the Mtpdc promoter (Ppdc) was able to drive high-level expression of the target protein in M. thermophila. Manipulation of the 5'UTR also has significant effects on protein expression and secretion. The best 5'UTR (NCA-7d) was identified. The transformant containing the laccase gene under the Mtpdc promoter, NCA-7d 5'UTR and its own signal peptide with the highest laccase activity (1708 U/L) was obtained. In addition, the expression system was stable and could be used for the production of various proteins, including homologous proteins like MtCbh-1, MtGh5-1, MtLPMO9B, and MtEpl1, as well as a glucoamylase from Trichoderma reesei.

CONCLUSIONS

An efficient protein expression system was established in M. thermophila for the production of various proteins. This study provides a valuable tool for protein production in M. thermophila and expands its potential for biotechnological applications.