Metabolic flux analysis for metabolome data validation of naturally xylose-fermenting yeasts

Current advances for omics-guided process optimization of microbial manufacturing

Currently, microbial manufacturing is widely used in various fields, such as food, medicine and energy, for its advantages of greenness and sustainable development. Process optimization is the committed step enabling the commercialization of microbial manufacturing products. However, the present optimization processes mainly rely on experience or trial-and-error method ignoring the intrinsic connection between cellular physiological requirement and production performance, so in many cases the productivity of microbial manufacturing could not been fully exploited at economically feasible cost. Recently, the rapid development of omics technologies facilitates the comprehensive analysis of microbial metabolism and fermentation performance from multi-levels of molecules, cells and microenvironment. The use of omics technologies makes the process optimization more explicit, boosting microbial manufacturing performance and bringing significant economic benefits and social value. In this paper, the traditional and omics technologies-guided process optimization of microbial manufacturing are systematically reviewed, and the future trend of process optimization is prospected.

Identification of traits to improve co-assimilation of glucose and xylose by adaptive evolution of Spathaspora passalidarum and Scheffersomyces stipitis yeasts

Lignocellulosic biomass is a renewable raw material for producing several high-value-added chemicals and fuels. In general, xylose and glucose are the major sugars in biomass hydrolysates, and their efficient utilization by microorganisms is critical for an economical production process. Yeasts capable of co-consuming mixed sugars might lead to higher yields and productivities in industrial fermentation processes. Herein, we performed adaptive evolution assays with two xylose-fermenting yeasts, Spathaspora passalidarum and Scheffersomyces stipitis, to obtain derived clones with improved capabilities of glucose and xylose co-consumption. Adapted strains were obtained after successive growth selection using xylose and the non-metabolized glucose analog 2-deoxy-D-glucose as a selective pressure. The co-fermentation capacity of evolved and parental strains was evaluated on xylose-glucose mixtures. Our results revealed an improved co-assimilation capability by the evolved strains; however, xylose and glucose consumption were observed at slower rates than the parental yeasts. Genome resequencing of the evolved strains revealed genes affected by non-synonymous variants that might be involved with the co-consumption phenotype, including the HXT2.4 gene that encodes a putative glucose transporter in Sp. passalidarum. Expression of this mutant HXT2.4 in Saccharomyces cerevisiae improved the cells' co-assimilation of glucose and xylose. Therefore, our results demonstrated the successful improvement of co-fermentation through evolutionary engineering and the identification of potential targets for further genetic engineering of different yeast strains. KEY POINTS: • Laboratory evolution assay was used to obtain improved sugar co-consumption of non-Saccharomyces strains. • Evolved Sp. passalidarum and Sc. stipitis were able to more efficiently co-ferment glucose and xylose. • A mutant Hxt2.4 permease, which co-transports xylose and glucose, was identified.

Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis

BACKGROUND

Elucidating cellular metabolism led to many breakthroughs in biotechnology, synthetic biology, and health sciences. To date, deriving metabolic fluxes by ¹³C tracer experiments is the most prominent approach for studying metabolic fluxes quantitatively, often with high accuracy and precision. However, the technique has a high demand for experimental resources. Alternatively, flux balance analysis (FBA) has been employed to estimate metabolic fluxes without labeling experiments. It is less informative but can benefit from the low costs and low experimental efforts and gain flux estimates in experimentally difficult conditions. Methods to integrate relevant experimental data have been emerged to improve FBA flux estimations. Data from transcription profiling is often selected since it is easy to generate at the genome scale, typically embedded by a discretization of differential and non-differential expressed genes coding for the respective enzymes.

RESULT

We established the novel method Linear Programming based Gene Expression Model (LPM-GEM). LPM-GEM linearly embeds gene expression into FBA constraints. We implemented three strategies to reduce thermodynamically infeasible loops, which is a necessary prerequisite for such an omics-based model building. As a case study, we built a model of B. subtilis grown in eight different carbon sources. We obtained good flux predictions based on the respective transcription profiles when validating with ¹³C tracer based metabolic flux data of the same conditions. We could well predict the specific carbon sources. When testing the model on another, unseen dataset that was not used during training, good prediction performance was also observed. Furthermore, LPM-GEM outperformed a well-established model building methods.

CONCLUSION

Employing LPM-GEM integrates gene expression data efficiently. The method supports gene expression-based FBA models and can be applied as an alternative to estimate metabolic fluxes when tracer experiments are inappropriate.

Metabolomic profiling of Spathaspora passalidarum fermentations reveals mechanisms that overcome hemicellulose hydrolysate inhibitors

Understanding the mechanisms involved in tolerance to inhibitors is the first step in developing robust yeasts for industrial second-generation ethanol (E2G) production. Here, we used ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) and MetaboAnalyst 4.0 for analysis of MS data to examine the changes in the metabolic profile of the yeast Spathaspora passalidarum during early fermentation of hemicellulosic hydrolysates containing high or low levels of inhibitors (referred to as control hydrolysate or CH and strategy hydrolysate or SH, respectively). During fermentation of SH, the maximum ethanol production was 16 g L^-1 with a yield of 0.28 g g^-1 and productivity of 0.22 g L^-1 h^-1, whereas maximum ethanol production in CH fermentation was 1.74 g L^-1 with a yield of 0.11 g g^-1 and productivity of 0.01 g L^-1 h^-1. The high level of inhibitors in CH induced complex physiological and biochemical responses related to stress tolerance in S. passalidarum. This yeast converted compounds with aldehyde groups (hydroxymethylfurfural, furfural, 4-hydroxybenzaldehyde, syringaldehyde, and vanillin) into less toxic compounds, and inhibitors were found to reduce cell viability and ethanol production. Intracellularly, high levels of inhibitors altered the energy homeostasis and redox balance, resulting in lower levels of ATP and NADPH, while that of glycolytic, pentose phosphate, and tricarboxylic acid (TCA) cycle pathways were the most affected, being the catabolism of glucogenic amino acids, the main cellular response to inhibitor-induced stress. This metabolomic investigation reveals interesting targets for metabolic engineering of ethanologenic yeast strains tolerant against multiple inhibitors for E2G production. KEY POINTS: • Inhibitors in the hydrolysates affected the yeast's redox balance and energy status. • Inhibitors altered the glycolytic, pentose phosphate, TCA cycle and amino acid pathways. • S. passalidarum converted aldehyde groups into less toxic compounds.

Insights into the Lignocellulose-Degrading Enzyme System of Humicola grisea var. thermoidea Based on Genome and Transcriptome Analysis

Humicola grisea var. thermoidea is a thermophilic ascomycete and important enzyme producer that has an efficient enzymatic system with a broad spectrum of thermostable carbohydrate-active (CAZy) enzymes. These enzymes can be employed in lignocellulose biomass deconstruction and other industrial applications. In this work, the genome of H. grisea var. thermoidea was sequenced. The acquired sequence reads were assembled into a total length of 28.75 Mbp. Genome features correlate with what was expected for thermophilic Sordariomycetes. The transcriptomic data showed that sugarcane bagasse significantly upregulated genes related to primary metabolism and polysaccharide deconstruction, especially hydrolases, at both pH 5 and pH 8. However, a number of exclusive and shared genes between the pH values were found, especially at pH 8. H. grisea expresses an average of 211 CAZy enzymes (CAZymes), which are capable of acting in different substrates. The top upregulated genes at both pH values represent CAZyme-encoding genes from different classes, including acetylxylan esterase, endo-1,4-β-mannosidase, exoglucanase, and endoglucanase genes. For the first time, the arsenal that the thermophilic fungus H. grisea var. thermoidea possesses to degrade the lignocellulosic biomass is shown. Carbon source and pH are of pivotal importance in regulating gene expression in this organism, and alkaline pH is a key regulatory factor for sugarcane bagasse hydrolysis. This work paves the way for the genetic manipulation and robust biotechnological applications of this fungus.

IMPORTANCE Most studies regarding the use of fungi as enzyme producers for biomass deconstruction have focused on mesophile species, whereas the potential of thermophiles has been evaluated less. This study revealed, through genome and transcriptome analyses, the genetic repertoire of the biotechnological relevant thermophile fungus Humicola grisea. Comparative genomics helped us to further understand the biology and biotechnological potential of H. grisea. The results demonstrate that this fungus possesses an arsenal of carbohydrate-active (CAZy) enzymes to degrade the lignocellulosic biomass. Indeed, it expresses more than 200 genes encoding CAZy enzymes when cultivated in sugarcane bagasse. Carbon source and pH are key factors for regulating the gene expression in this organism. This work shows, for the first time, the great potential of H. grisea as an enzyme producer and a gene donor for biotechnological applications and provides the base for the genetic manipulation and robust biotechnological applications of this fungus.

Recent advances in systems and synthetic biology approaches for developing novel cell-factories in non-conventional yeasts

Microbial bioproduction of chemicals, proteins, and primary metabolites from cheap carbon sources is currently an advancing area in industrial research. The model yeast, Saccharomyces cerevisiae, is a well-established biorefinery host that has been used extensively for commercial manufacturing of bioethanol from myriad carbon sources. However, its Crabtree-positive nature often limits the use of this organism for the biosynthesis of commercial molecules that do not belong in the fermentative pathway. To avoid extensive strain engineering of S. cerevisiae for the production of metabolites other than ethanol, non-conventional yeasts can be selected as hosts based on their natural capacity to produce desired commodity chemicals. Non-conventional yeasts like Kluyveromyces marxianus, K. lactis, Yarrowia lipolytica, Pichia pastoris, Scheffersomyces stipitis, Hansenula polymorpha, and Rhodotorula toruloides have been considered as potential industrial eukaryotic hosts owing to their desirable phenotypes such as thermotolerance, assimilation of a wide range of carbon sources, as well as ability to secrete high titers of protein and lipid. However, the advanced metabolic engineering efforts in these organisms are still lacking due to the limited availability of systems and synthetic biology methods like in silico models, well-characterised genetic parts, and optimized genome engineering tools. This review provides an insight into the recent advances and challenges of systems and synthetic biology as well as metabolic engineering endeavours towards the commercial usage of non-conventional yeasts. Particularly, the approaches in emerging non-conventional yeasts for the production of enzymes, therapeutic proteins, lipids, and metabolites for commercial applications are extensively discussed here. Various attempts to address current limitations in designing novel cell factories have been highlighted that include the advances in the fields of genome-scale metabolic model reconstruction, flux balance analysis, 'omics'-data integration into models, genome-editing toolkit development, and rewiring of cellular metabolisms for desired chemical production. Additionally, the understanding of metabolic networks using ¹³C-labelling experiments as well as the utilization of metabolomics in deciphering intracellular fluxes and reactions have also been discussed here. Application of cutting-edge nuclease-based genome editing platforms like CRISPR/Cas9, and its optimization towards efficient strain engineering in non-conventional yeasts have also been described. Additionally, the impact of the advances in promising non-conventional yeasts for efficient commercial molecule synthesis has been meticulously reviewed. In the future, a cohesive approach involving systems and synthetic biology will help in widening the horizon of the use of unexplored non-conventional yeast species towards industrial biotechnology.

A common approach for absolute quantification of short chain CoA thioesters in prokaryotic and eukaryotic microbes

BACKGROUND

Thioesters of coenzyme A participate in 5% of all enzymatic reactions. In microbial cell factories, they function as building blocks for products of recognized commercial value, including natural products such as polyketides, polyunsaturated fatty acids, biofuels, and biopolymers. A core spectrum of approximately 5-10 short chain thioesters is present in many microbes, as inferred from their genomic repertoire. The relevance of these metabolites explains the high interest to trace and quantify them in microbial cells.

RESULTS

Here, we describe a common workflow for extraction and absolute quantification of short chain CoA thioesters in different gram-positive and gram-negative bacteria and eukaryotic yeast, i.e. Corynebacterium glutamicum, Streptomyces albus, Pseudomonas putida, and Yarrowia lipolytica. The approach assessed intracellular CoA thioesters down to the picomolar level and exhibited high precision and reproducibility for all microbes, as shown by principal component analysis. Furthermore, it provided interesting insights into microbial CoA metabolism. A succinyl-CoA synthase defective mutant of C. glutamicum exhibited an unaffected level of succinyl-CoA that indicated a complete compensation by the L-lysine pathway to bypass the disrupted TCA cycle. Methylmalonyl-CoA, an important building block of high-value polyketides, was identified as dominant CoA thioester in the actinomycete S. albus. The microbe revealed a more than 10,000-fold difference in the abundance of intracellular CoA thioesters. A recombinant strain of S. albus, which produced different derivatives of the antituberculosis polyketide pamamycin, revealed a significant depletion of CoA thioesters of the ethylmalonyl CoA pathway, influencing product level and spectrum.

CONCLUSIONS

The high relevance of short chain CoA thioesters to synthetize industrial products and the interesting insights gained from the examples shown in this work, suggest analyzing these metabolites in microbial cell factories more routinely than done so far. Due to its broad application range, the developed approach appears useful to be applied this purpose. Hereby, the possibility to use one single protocol promises to facilitate automatized efforts, which rely on standardized workflows.

The Xylose Metabolizing Yeast Spathaspora passalidarum is a Promising Genetic Treasure for Improving Bioethanol Production

Currently, the fermentation technology for recycling agriculture waste for generation of alternative renewable biofuels is getting more and more attention because of the environmental merits of biofuels for decreasing the rapid rise of greenhouse gas effects compared to petrochemical, keeping in mind the increase of petrol cost and the exhaustion of limited petroleum resources. One of widely used biofuels is bioethanol, and the use of yeasts for commercial fermentation of cellulosic and hemicellulosic agricultural biomasses is one of the growing biotechnological trends for bioethanol production. Effective fermentation and assimilation of xylose, the major pentose sugar element of plant cell walls and the second most abundant carbohydrate, is a bottleneck step towards a robust biofuel production from agricultural waste materials. Hence, several attempts were implemented to engineer the conventional Saccharomyces cerevisiae yeast to transport and ferment xylose because naturally it does not use xylose, using genetic materials of Pichia stipitis, the pioneer native xylose fermenting yeast. Recently, the nonconventional yeast Spathaspora passalidarum appeared as a founder member of a new small group of yeasts that, like Pichia stipitis, can utilize and ferment xylose. Therefore, the understanding of the molecular mechanisms regulating the xylose assimilation in such pentose fermenting yeasts will enable us to eliminate the obstacles in the biofuels pipeline, and to develop industrial strains by means of genetic engineering to increase the availability of renewable biofuel products from agricultural biomass. In this review, we will highlight the recent advances in the field of native xylose metabolizing yeasts, with special emphasis on S. passalidarum for improving bioethanol production.