Systems biology of yeast: enabling technology for development of cell factories for production of advanced biofuels

Visualizing Metabolism in Biotechnologically Important Yeasts with dDNP NMR Reveals Evolutionary Strategies and Glycolytic Logic

Saccharomyces cerevisiae has long been a pillar of biotechnological production and basic research. More recently, strides to exploit the functional repertoire of nonconventional yeasts for biotechnological production have been made. Genomes and genetic tools for these yeasts are not always available, and yeast genomics alone may be insufficient to determine the functional features in yeast metabolism. Hence, functional assays of metabolism, ideally in the living cell, are best suited to characterize the cellular biochemistry of such yeasts. Advanced in cell NMR methods can allow the direct observation of carbohydrate influx into central metabolism on a seconds time scale: dDNP NMR spectroscopy temporarily enhances the nuclear spin polarization of substrates by more than 4 orders of magnitude prior to functional assays probing central metabolism. We use various dDNP enhanced carbohydrates for in-cell NMR to compare the metabolism of S. cerevisiae and nonconventional yeasts, with an emphasis on the wine yeast Hanseniaspora uvarum. In-cell observations indicated more rapid exhaustion of free cytosolic NAD+ in H. uvarum and alternative routes for pyruvate conversion, in particular, rapid amination to alanine. In-cell observations indicated that S. cerevisiae outcompetes other biotechnologically relevant yeasts by rapid ethanol formation due to the efficient adaptation of cofactor pools and the removal of competing reactions from the cytosol. By contrast, other yeasts were better poised to use redox neutral processes that avoided CO2-emission. Beyond visualizing the different cellular strategies for arriving at redox neutral end points, in-cell dDNP NMR probing showed that glycolytic logic is more conserved: nontoxic precursors of cellular building blocks formed high-population intermediates in the influx of glucose into the central metabolism of eight different biotechnologically important yeasts. Unsupervised clustering validated that the observation of rapid intracellular chemistry is a viable means to functionally classify biotechnologically important organisms.

In-Cell NMR Approach for Real-Time Exploration of Pathway Versatility: Substrate Mixtures in Nonengineered Yeast

The central carbon metabolism of microbes will likely be used in future sustainable bioproduction. A sufficiently deep understanding of central metabolism would advance the control of activity and selectivity in whole-cell catalysis. Opposite to the more obvious effects of adding catalysts through genetic engineering, the modulation of cellular chemistry through effectors and substrate mixtures remains less clear. NMR spectroscopy is uniquely suited for in-cell tracking to advance mechanistic insight and to optimize pathway usage. Using a comprehensive and self-consistent library of chemical shifts, hyperpolarized NMR, and conventional NMR, we probe the versatility of cellular pathways to changes in substrate composition. Conditions for glucose influx into a minor pathway to an industrial precursor (2,3-butanediol) can thus be designed. Changes to intracellular pH can be followed concurrently, while mechanistic details for the minor pathway can be derived using an intermediate-trapping strategy. Overflow at the pyruvate level can be induced in nonengineered yeast with suitably mixed carbon sources (here glucose with auxiliary pyruvate), thus increasing glucose conversion to 2,3-butanediol by more than 600-fold. Such versatility suggests that a reassessment of canonical metabolism may be warranted using in-cell spectroscopy.

Fructan Biosynthesis by Yeast Cell Factories

Fructan is a polysaccharide composed of fructose and can be classified into several types, such as inulin, levan, and fructo-oligosaccharides, based on their linkage patterns and degree of polymerization. Owing to its structural and functional diversity, fructan has been used in various fields including prebiotics, foods and beverages, cosmetics, and pharmaceutical applications. With increasing interest in fructans, efficient and straightforward production methods have been explored. Since the 1990s, yeast cells have been employed as producers of recombinant enzymes for enzymatic conversion of fructans including fructosyltransferases derived from various microbes and plants. More recently, yeast cell factories are highlighted as efficient workhorses for fructan production by direct fermentation. In this review, recent advances and strategies for fructan biosynthesis by yeast cell factories are discussed.

Whole Genome Sequencing Analysis of Effects of CRISPR/Cas9 in Komagataella phaffii: A Budding Yeast in Distress

The industrially important non-conventional yeast Komagataella phaffii suffers from low rates of homologous recombination, making site specific genetic engineering tedious. Therefore, genome editing using CRISPR/Cas represents a simple and efficient alternative. To characterize on- and off-target mutations caused by CRISPR/Cas9 followed by non-homologous end joining repair, we chose a diverse set of CRISPR/Cas targets and conducted whole genome sequencing on 146 CRISPR/Cas9 engineered single colonies. We compared the outcomes of single target CRISPR transformations to double target experiments. Furthermore, we examined the extent of possible large deletions by targeting a large genomic region, which is likely to be non-essential. The analysis of on-target mutations showed an unexpectedly high number of large deletions and chromosomal rearrangements at the CRISPR target loci. We also observed an increase of on-target structural variants in double target experiments as compared to single target experiments. Targeting of two loci within a putatively non-essential region led to a truncation of chromosome 3 at the target locus in multiple cases, causing the deletion of 20 genes and several ribosomal DNA repeats. The identified de novo off-target mutations were rare and randomly distributed, with no apparent connection to unspecific CRISPR/Cas9 off-target binding sites.

Easy efficient HDR-based targeted knock-in in Saccharomyces cerevisiae genome using CRISPR-Cas9 system

During the last two decades, yeast has been used as a biological tool to produce various small molecules, biofuels, etc., using an inexpensive bioprocess. The application of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated protein (Cas) techniques in yeast genetic and metabolic engineering has made a paradigm shift, particularly with a significant improvement in targeted chromosomal integration using synthetic donor constructs, which was previously a challenge. This study reports the CRISPR-Cas9-based highly efficient strategy for targeted chromosomal integration and in-frame expression of a foreign gene in the genome of Saccharomyces cerevisiae (S. cerevisiae) by homology-dependent recombination (HDR); our optimized methods show that CRISPR-Cas9-based chromosomal targeted integration of small constructs at multiple target sites of the yeast genome can be achieved with an efficiency of 74%. Our study also suggests that 15 bp microhomology flanked arms are sufficient for 50% targeted knock-in at minimal knock-in construct concentration. Whole-genome sequencing confirmed that there is no off-target effect. This study provides a comprehensive and streamlined protocol that will support the targeted integration of essential genes into the yeast genome for synthetic biology and other industrial purposes.Highlights• CRISPR-Cas9 based in-frame expression of foreign protein in Saccharomyces cerevisiae using Homology arm without a promoter.• As low as 15 base pairs of microhomology (HDR) are sufficient for targeted integration in Saccharomyces cerevisiae.• The methodology is highly efficient and very specific as no off-targeted effects were shown by the whole-genome sequence.

Active pharmaceutical ingredient (API) chemicals: a critical review of current biotechnological approaches

The aim of this article was to generate a framework of bio-based economy by an effective utilization of biomass from the perspectives of agriculture for developing potential end bio-based products (e.g. pharmaceuticals, active pharmaceutical ingredients). Our discussion is also extended to the conservatory ways of bioenergy along with development of bio-based products and biofuels. This review article further showcased the fundamental principles for producing these by-products. Thereby, the necessity of creating these products is to be efficaciously utilization by small-scale farmers that can aid the local needs for bio-based materials and energy. Concurrently, the building up of small markets will open up the avenues and linkages for bigger markets. In nutshell, the aim of the review is to explore the pathway of the biotechnological approaches so that less chosen producers and underdeveloped areas can be allied so that pressure on the systems of biomass production can be relaxed.

The yeastGemMap: A process diagram to assist yeast systems-metabolic studies

Visualization is a key aspect of the analysis of omics data. Although many tools can generate pathway maps for visualization of yeast metabolism, they fail in reconstructing genome-scale metabolic diagrams of compartmentalized metabolism. Here we report on the yeastGemMap, a process diagram of whole yeast metabolism created to assist data analysis in systems-metabolic studies. The map was manually reconstructed with reactions from a compartmentalized genome-scale metabolic model, based on biochemical process diagrams typically found in educational and specialized literature. The yeastGemMap consists of 3815 reactions representing 1150 genes, 2742 metabolites, and 14 compartments. Computational functions for adapting the graphical representation of the map are also reported. These functions modify the visual representation of the map to assist in three systems-metabolic tasks: illustrating reaction networks, interpreting metabolic flux data, and visualizing omics data. The versatility of the yeastGemMap and algorithms to assist visualization of systems-metabolic data was demonstrated in various tasks, including for single lethal reaction evaluation, flux balance analysis, and transcriptomic data analysis. For instance, visual interpretation of metabolic transcriptomes of thermally evolved and parental yeast strains allowed to demonstrate that evolved strains activate a preadaptation response at 30°C, which enabled thermotolerance. A quick interpretation of systems-metabolic data is promoted with yeastGemMap visualizations.

The Potential of Single-Cell Oils Derived From Filamentous Fungi as Alternative Feedstock Sources for Biodiesel Production

Microbial lipids, also known as single-cell oils (SCOs), are highly attractive feedstocks for biodiesel production due to their fast production rates, minimal labor requirements, independence from seasonal and climatic changes, and ease of scale-up for industrial processing. Among the SCO producers, the less explored filamentous fungi (molds) exhibit desirable features such as a repertoire of hydrolyzing enzymes and a unique pellet morphology that facilitates downstream harvesting. Although several oleaginous filamentous fungi have been identified and explored for SCO production, high production costs and technical difficulties still make the process less attractive compared to conventional lipid sources for biodiesel production. This review aims to highlight the ability of filamentous fungi to hydrolyze various organic wastes for SCO production and explore current strategies to enhance the efficiency and cost-effectiveness of the SCO production and recovery process. The review also highlights the mechanisms and components governing lipogenic pathways, which can inform the rational designs of processing conditions and metabolic engineering efforts for increasing the quality and accumulation of lipids in filamentous fungi. Furthermore, we describe other process integration strategies such as the co-production with hydrogen using advanced fermentation processes as a step toward a biorefinery process. These innovative approaches allow for integrating upstream and downstream processing units, thus resulting in an efficient and cost-effective method of simultaneous SCO production and utilization for biodiesel production.

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desirable features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find nonobvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocesses. Finally, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

Valorisation of pectin-rich agro-industrial residues by yeasts: potential and challenges

Pectin-rich agro-industrial residues are feedstocks with potential for sustainable biorefineries. They are generated in high amounts worldwide from the industrial processing of fruits and vegetables. The challenges posed to the industrial implementation of efficient bioprocesses are however manyfold and thoroughly discussed in this review paper, mainly at the biological level. The most important yeast cell factory platform for advanced biorefineries is currently Saccharomyces cerevisiae, but this yeast species cannot naturally catabolise the main sugars present in pectin-rich agro-industrial residues hydrolysates, in particular d-galacturonic acid and l-arabinose. However, there are non-Saccharomyces species (non-conventional yeasts) considered advantageous alternatives whenever they can express highly interesting metabolic pathways, natively assimilate a wider range of carbon sources or exhibit higher tolerance to relevant bioprocess-related stresses. For this reason, the interest in non-conventional yeasts for biomass-based biorefineries is gaining momentum. This review paper focuses on the valorisation of pectin-rich residues by exploring the potential of yeasts that exhibit vast metabolic versatility for the efficient use of the carbon substrates present in their hydrolysates and high robustness to cope with the multiple stresses encountered. The major challenges and the progresses made related with the isolation, selection, sugar catabolism, metabolic engineering and use of non-conventional yeasts and S. cerevisiae-derived strains for the bioconversion of pectin-rich residue hydrolysates are discussed. The reported examples of value-added products synthesised by different yeasts using pectin-rich residues are reviewed.

Key Points • Review of the challenges and progresses made on the bioconversion of pectin-rich residues by yeasts. • Catabolic pathways for the main carbon sources present in pectin-rich residues hydrolysates. • Multiple stresses with potential to affect bioconversion productivity. • Yeast metabolic engineering to improve pectin-rich residues bioconversion.

Development and optimization of N-acetylneuraminic acid biosensors in Bacillus subtilis

Transcriptional factor (TF)-based metabolite-responsive biosensors are important tools for screening engineered enzymes with desired properties and for the dynamic regulation of biosynthetic pathways. However, TF-based biosensor construction is often constrained by undesired effects of TF-binding site sequence insertion on gene expression and unpredictable optimal TF expression levels. In the present study, a stepwise TF-based biosensor construction approach was developed using an N-acetylneuraminic acid (NeuAc) biosensor for Bacillus subtilis, as a case study. Specifically, 12 promoters with various strengths were selected as the first promoter library. Next, binding site sequences for the NanR were inserted into various positions of the selected promoter sequences to develop the second promoter library, resulting in 6 engineered promoters containing TF-binding site sequences (NanO), without major effects on promoter strength. NanR expression cassettes with different expression levels were further integrated to construct the biosensor library, yielding 9 NeuAc biosensors with efficient repression in the absence of NeuAc. Finally, biosensor activation was characterized by testing fold changes in expression levels of the green fluorescent protein reporter in the presence of NeuAc in vivo, which revealed 61-fold activation when NeuAc was present. The NeuAc biosensor developed in this study can be used for screening engineered enzymes for enhanced NeuAc biosynthesis in B. subtilis.

Challenges of biofilm control and utilization: lessons from mathematical modelling

This article reviews modern applications of mathematical descriptions of biofilm formation. The focus is on theoretically obtained results which have implications for areas including the medical sector, food industry and wastewater treatment. Examples are given as to how models have contributed to the overall knowledge on biofilms and how they are used to predict biofilm behaviour. We conclude that the use of mathematical models of biofilms has demonstrated over the years the ability to significantly contribute to the vast field of biofilm research. Among other things, they have been used to test various hypotheses on the nature of interspecies interactions, viability of biofilm treatment methods or forces behind observed biofilm pattern formations. Mathematical models can also play a key role in future biofilm research. Many models nowadays are analysed through computer simulations and continue to improve along with computational capabilities. We predict that models will keep on providing answers to important challenges involving biofilm formation. However, further strengthening of the ties between various disciplines is necessary to fully use the tools of collective knowledge in tackling the biofilm phenomenon.

CRISPR-mediated genome editing in non-conventional yeasts for biotechnological applications

Non-conventional yeasts are playing important roles as cell factories for bioproduction of biofuels, food additives and proteins with outstanding natural characteristics. However, the precise genome editing is challenging in non-conventional yeasts due to lack of efficient genetic tools. In the past few years, CRISPR-based genome editing worked as a revolutionary tool for genetic engineering and showed great advantages in cellular metabolic engineering. Here, we review the current advances and barriers of CRISPR-Cas9 for genome editing in non-conventional yeasts and propose the possible solutions in enhancing its efficiency for precise genetic engineering.

High-Throughput Microfluidics for the Screening of Yeast Libraries

Cell factory development is critically important for efficient biological production of chemicals, biofuels, and pharmaceuticals. Many rounds of the Design-Build-Test-Learn cycles may be required before an engineered strain meeting specific metrics required for industrial application. The bioindustry prefer products in secreted form (secreted products or extracellular metabolites) as it can lower the cost of downstream processing, reduce metabolic burden to cell hosts, and allow necessary modification on the final products , such as biopharmaceuticals. Yet, products in secreted form result in the disconnection of phenotype from genotype, which may have limited throughput in the Test step for identification of desired variants from large libraries of mutant strains. In droplet microfluidic screening, single cells are encapsulated in individual droplet and enable high-throughput processing and sorting of single cells or clones. Encapsulation in droplets allows this technology to overcome the throughput limitations present in traditional methods for screening by extracellular phenotypes. In this chapter, we describe a protocol/guideline for high-throughput droplet microfluidics screening of yeast libraries for higher protein secretion . This protocol can be adapted to screening by a range of other extracellular products from yeast or other hosts.

Orthogonal partial least squares/projections to latent structures regression-based metabolomics approach for identification of gene targets for improvement of 1-butanol production in Escherichia coli

Metabolomics is the comprehensive analysis of metabolites in biological systems that uses multivariate analyses such as principal component analysis (PCA) or partial least squares/projections to latent structures regression (PLSR) to understand the metabolome state and extract important information from biological systems. In this study, orthogonal PLSR (OPLSR) model-based metabolomics approach was applied to 1-butanol producing Escherichia coli to facilitate in strain improvement strategies. Here, metabolite data obtained by liquid chromatography/mass spectrometry (LC/MS) was used to construct an OPLSR model to correlate metabolite changes with 1-butanol production and rationally identify gene targets for strain improvement. Using this approach, acetyl-CoA was determined as the rate-limiting step of the pathway while free CoA was found to be insufficient for 1-butanol production. By resolving the problems addressed by the OPLSR model, higher 1-butanol productivity was achieved. In this study, the usefulness of OPLSR-based metabolomics approach for understanding the whole metabolome state and determining the most relevant metabolites was demonstrated. Moreover, it was able to provide valuable insights for selection of rational gene targets for strain improvement.

Genome-wide search for candidate genes for yeast robustness improvement against formic acid reveals novel susceptibility (Trk1 and positive regulators) and resistance (Haa1-regulon) determinants

BACKGROUND

Formic acid is an inhibitory compound present in lignocellulosic hydrolysates. Understanding the complex molecular mechanisms underlying Saccharomyces cerevisiae tolerance to this weak acid at the system level is instrumental to guide synthetic pathway engineering for robustness improvement of industrial strains envisaging their use in lignocellulosic biorefineries.

RESULTS

This study was performed to identify, at a genome-wide scale, genes whose expression confers protection or susceptibility to formic acid, based on the screening of a haploid deletion mutant collection to search for these phenotypes in the presence of 60, 70 and 80 mM of this acid, at pH 4.5. This chemogenomic analysis allowed the identification of 172 determinants of tolerance and 41 determinants of susceptibility to formic acid. Clustering of genes required for maximal tolerance to this weak acid, based on their biological function, indicates an enrichment of those involved in intracellular trafficking and protein synthesis, cell wall and cytoskeleton organization, carbohydrate metabolism, lipid, amino acid and vitamin metabolism, response to stress, chromatin remodelling, transcription and internal pH homeostasis. Among these genes is HAA1 encoding the main transcriptional regulator of yeast transcriptome reprograming in response to acetic acid and genes of the Haa1-regulon; all demonstrated determinants of acetic acid tolerance. Among the genes that when deleted lead to increased tolerance to formic acid, TRK1, encoding the high-affinity potassium transporter and a determinant of resistance to acetic acid, was surprisingly found. Consistently, genes encoding positive regulators of Trk1 activity were also identified as formic acid susceptibility determinants, while a negative regulator confers protection. At a saturating K⁺ concentration of 20 mM, the deletion mutant trk1Δ was found to exhibit a much higher tolerance compared with the parental strain. Given that trk1Δ accumulates lower levels of radiolabelled formic acid, compared to the parental strain, it is hypothesized that Trk1 facilitates formic acid uptake into the yeast cell.

CONCLUSIONS

The list of genes resulting from this study shows a few marked differences from the list of genes conferring protection to acetic acid and provides potentially valuable information to guide improvement programmes for the development of more robust strains against formic acid.

Metabolic engineering of microbial competitive advantage for industrial fermentation processes

Microbial contamination is an obstacle to widespread production of advanced biofuels and chemicals. Current practices such as process sterilization or antibiotic dosage carry excess costs or encourage the development of antibiotic resistance. We engineered Escherichia coli to assimilate melamine, a xenobiotic compound containing nitrogen. After adaptive laboratory evolution to improve pathway efficiency, the engineered strain rapidly outcompeted a control strain when melamine was supplied as the nitrogen source. We additionally engineered the yeasts Saccharomyces cerevisiae and Yarrowia lipolytica to assimilate nitrogen from cyanamide and phosphorus from potassium phosphite, and they outcompeted contaminating strains in several low-cost feedstocks. Supplying essential growth nutrients through xenobiotic or ecologically rare chemicals provides microbial competitive advantage with minimal external risks, given that engineered biocatalysts only have improved fitness within the customized fermentation environment.

Constructing kinetic models of metabolism at genome-scales: A review

Constraint-based modeling of biological networks (metabolism, transcription and signal transduction), although used successfully in many applications, suffer from specific limitations such as the lack of representation of metabolite concentrations and enzymatic regulation, which are necessary for a complete physiologically relevant model. Kinetic models conversely overcome these shortcomings and enable dynamic analysis of biological systems for enhanced in silico hypothesis generation. Nonetheless, kinetic models also have limitations for modeling at genome-scales chiefly due to: (i) model non-linearity; (ii) computational tractability; (iii) parameter identifiability; (iv) estimability; and (v) uncertainty. In order to support further development of kinetic models as viable alternatives to constraint-based models, this review presents a brief description of the existing obstacles towards building genome-scale kinetic models. Specific kinetic modeling frameworks capable of overcoming these obstacles are covered in this review. The tractability and physiological feasibility of these models are discussed with the objective of using available in vivo experimental observations to define the model parameter space. Among the different methods discussed, Monte Carlo kinetic models of metabolism stand out as potentially tractable methods to model genome scale networks while also addressing in vivo parameter uncertainty.

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.

OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell Metabolism

Constraint-based metabolic modeling such as flux balance analysis (FBA) has been widely used to simulate cell metabolism. Thanks to its simplicity and flexibility, numerous algorithms have been developed based on FBA and successfully predicted the phenotypes of various biological systems. However, their phenotype predictions may not always be accurate in FBA because of using the objective function that is assumed for cell metabolism. To overcome this challenge, we have developed a novel computational framework, namely omFBA, to integrate multi-omics data (e.g. transcriptomics) into FBA to obtain omics-guided objective functions with high accuracy. In general, we first collected transcriptomics data and phenotype data from published database (e.g. GEO database) for different microorganisms such as Saccharomyces cerevisiae. We then developed a “Phenotype Match” algorithm to derive an objective function for FBA that could lead to the most accurate estimation of the known phenotype (e.g. ethanol yield). The derived objective function was next correlated with the transcriptomics data via regression analysis to generate the omics-guided objective function, which was next used to accurately simulate cell metabolism at unknown conditions. We have applied omFBA in studying sugar metabolism of S. cerevisiae and found that the ethanol yield could be accurately predicted in most of the cases tested (>80%) by using transcriptomics data alone, and revealed valuable metabolic insights such as the dynamics of flux ratios. Overall, omFBA presents a novel platform to potentially integrate multi-omics data simultaneously and could be incorporated with other FBA-derived tools by replacing the arbitrary objective function with the omics-guided objective functions.

Operational parameters and their influence on particle-side mass transfer resistance in a packed bed bioreactor

The influence of internal mass transfer on productivity as well as the performance of packed bed bioreactor was determined by varying a number of parameters; chitosan coating, flow rate, glucose concentration and particle size. Saccharomyces cerevisiae cells were immobilized in chitosan and non-chitosan coated alginate beads to demonstrate the effect on particle side mass transfer on substrate consumption time, lag phase and ethanol production. The results indicate that chitosan coating, beads size, glucose concentration and flow rate have a significant effect on lag phase duration. The duration of lag phase for different size of beads (0.8, 2 and 4 mm) decreases by increasing flow rate and by decreasing the size of beads. Moreover, longer lag phase were found at higher glucose medium concentration and also with chitosan coated beads. It was observed that by increasing flow rates; lag phase and glucose consumption time decreased. The reason is due to the reduction of external (fluid side) mass transfer as a result of increase in flow rate as glucose is easily transported to the surface of the beads. Varying the size of beads is an additional factor: as it reduces the internal (particle side) mass transfer by reducing the size of beads. The reason behind this is the distance for reactants to reach active site of catalyst (cells) and the thickness of fluid created layer around alginate beads is reduced. The optimum combination of parameters consisting of smaller beads size (0.8 mm), higher flow rate of 90 ml/min and glucose concentration of 10 g/l were found to be the maximum condition for ethanol production.

Physiological and transcriptional characterization of Saccharomyces cerevisiae engineered for production of fatty acid ethyl esters

Saccharomyces cerevisiae has previously been engineered to become a cell factory for the production of fatty acid ethyl esters (FAEEs), molecules suitable for crude diesel replacement. To find new metabolic engineering targets for the improvement of FAEE cell factories, three different FAEE-producing strains of S. cerevisiae, constructed previously, were compared and characterized by quantification of key fluxes and genome-wide transcription analysis. From both the physiological and the transcriptional data, it was indicated that strain CB2I20, with high expression of a heterologous wax ester synthase gene (ws2) and strain BdJ15, containing disruptions of genes DGA1, LRO1, ARE1, ARE2 and POX1, which prevent the conversion of acyl-CoA to sterol esters, triacylglycerides and the degradation to acetyl-CoA, triggered oxidative stress that consequently influenced cellular growth. In the latter strain, stress was possibly triggered by disabling the buffering capacity of lipid droplets in encapsulating toxic fatty acids such as oleic acid. Additionally, it was indicated that there was an increased demand for NADPH required for the reduction steps in fatty acid biosynthesis. In conclusion, our analysis clearly shows that engineering of fatty acid biosynthesis results in transcriptional reprogramming and has a significant effect on overall cellular metabolism.

The use of 'Omics technology to rationally improve industrial mammalian cell line performance

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development.

Combinatorial metabolic engineering of Saccharomyces cerevisiae for terminal alkene production

Biological production of terminal alkenes has garnered a significant interest due to their industrial applications such as lubricants, detergents and fuels. Here, we engineered the yeast Saccharomyces cerevisiae to produce terminal alkenes via a one-step fatty acid decarboxylation pathway and improved the alkene production using combinatorial engineering strategies. In brief, we first characterized eight fatty acid decarboxylases to enable and enhance alkene production. We then increased the production titer 7-fold by improving the availability of the precursor fatty acids. We additionally increased the titer about 5-fold through genetic cofactor engineering and gene expression tuning in rich medium. Lastly, we further improved the titer 1.8-fold to 3.7 mg/L by optimizing the culturing conditions in bioreactors. This study represents the first report of terminal alkene biosynthesis in S. cerevisiae, and the abovementioned combinatorial engineering approaches collectively increased the titer 67.4-fold. We envision that these approaches could provide insights into devising engineering strategies to improve the production of fatty acid-derived biochemicals in S. cerevisiae.

Rapid and high-throughput construction of microbial cell-factories with regulatory noncoding RNAs

Due to global crises such as pollution and depletion of fossil fuels, sustainable technologies based on microbial cell-factories have been garnering great interest as an alternative to chemical factories. The development of microbial cell-factories is imperative in cutting down the overall manufacturing cost. Thus, diverse metabolic engineering strategies and engineering tools have been established to obtain a preferred genotype and phenotype displaying superior productivity. However, these tools are limited to only a handful of genes with permanent modification of a genome and significant labor costs, and this is one of the bottlenecks associated with biofactory construction. Therefore, a groundbreaking rapid and high-throughput engineering tool is needed for efficient construction of microbial cell-factories. During the last decade, copious small noncoding RNAs (ncRNAs) have been discovered in bacteria. These are involved in substantial regulatory roles like transcriptional and post-transcriptional gene regulation by modulating mRNA elongation, stability, or translational efficiency. Because of their vulnerability, ncRNAs can be used as another layer of conditional control over gene expression without modifying chromosomal sequences, and hence would be a promising high-throughput tool for metabolic engineering. Here, we review successful design principles and applications of ncRNAs for high-throughput metabolic engineering or physiological studies of diverse industrially important microorganisms.

Influence of operational parameters on the fluid-side mass transfer resistance observed in a packed bed bioreactor

The influence of mass transfer on productivity as well as the performance of packed bed bioreactor was determined by varying a number of parameters; flow rate, glucose concentration and polymers (chitosan). Saccharomyces cerevisiae cells were immobilized in chitosan and non-chitosan coated alginate beads to demonstrate the effect on external mass transfer by substrate consumption time, lag phase and ethanol production. The results indicate that coating has a significant effect on the lag phase duration, being 30-40 min higher than non-coated beads. After lag phase, no significant change was observed in both types of beads on consumption of glucose with the same flow rate. It was observed that by increasing flow rates; lag phase and glucose consumption time decreased. The reason is due to the reduction of external mass transfer as a result of increase in flow rate as glucose is easily transported to and from the beads surface by diffusion. It is observed that chitosan acts as barrier for transfer of substrate and products, in and out of beads, at initial time of fermentation as it shows longer lag phase for chitosan coated beads than non-coated. Glucose consumption at low flow rate was lower as compared to higher flow rates. The optimum combination of parameters consisting of higher flow rates 30-90 ml/min and between 10 and 20 g/l of glucose was found for maximum production of ethanol.

Improved activity of the Cel5A endoglucanase in Saccharomyces cerevisiae deletion mutants defective in oxidative stress defense mechanisms

OBJECTIVES

Developing a Saccharomyces cerevisiae system for optimizing the expression of recombinant eukaryotic proteins.

RESULTS

Two deletion mutants, which were hypersensitive to H2O2, were obtained by knocking out CTT1 and SOD2, respectively. The mutation rate of the mutants was up to over 4000 times of the spontaneous mutation rate when treated with H2O2. Endoglucanase Cel5A was used as a model enzyme to evaluate the system for improving the expression of the recombinant protein. Sixteen mutants of the RDKY3615 (ctt1∆) transformant and seven mutants of the RDKY3615 (sod2∆) transformant had significantly high Cel5A activity, while none mutants of the RDKY3615 transformant had significantly high enzyme activity.

CONCLUSION

The combination of deletion mutagenesis and H2O2 treatment greatly accelerate the generation of genetic variants and will be a useful tool in improving the heterologous expression in S. cerevisiae.

Recent advances in engineering yeast for pharmaceutical protein production

Currently available systems and synthetic biology tools can be applied to yeast engineering for improved biopharmaceutical protein production.

Metabolic engineering of microbes for branched-chain biodiesel production with low-temperature property

BACKGROUND

The steadily increasing demand for diesel fuels calls for renewable energy sources. This has attracted a growing amount of research to develop advanced, alternative biodiesel worldwide. Several major disadvantages of current biodiesels are the undesirable physical properties such as high viscosity and poor low-temperature operability. Therefore, there is an urgent need to develop novel and advanced biodiesels.

RESULTS

Inspired by the proven capability of wax ester synthase/acyl-coenzyme A, diacylglycerol acyltransferase (WS/DGAT) to generate fatty acid esters, de novo biosynthesis of fatty acid branched-chain esters (FABCEs) and branched fatty acid branched-chain esters (BFABCEs) was performed in engineered Escherichia coli through combination of the (branched) fatty acid biosynthetic pathway and the branched-chain amino acid biosynthetic pathway. Furthermore, by modifying the fatty acid pathway, we improved FABCE production to 273 mg/L and achieved a high proportion of FABCEs at 99.3 % of total fatty acid esters. In order to investigate the universality of this strategy, Pichia pastoris yeast was engineered and produced desirable levels of FABCEs for the first time with a good starting point of 169 mg/L.

CONCLUSIONS

We propose new pathways of fatty acid ester biosynthesis and establish proof of concept through metabolic engineering of E. coli and P. pastoris yeast. We were able to produce advanced biodiesels with high proportions FABCEs and BFABCEs. Furthermore, this new strategy promises to achieve advanced biodiesels with beneficial low-temperature properties.

Metabolic pathway engineering for fatty acid ethyl ester production in Saccharomyces cerevisiae using stable chromosomal integration

Fatty acid ethyl esters are fatty acid derived molecules similar to first generation biodiesel (fatty acid methyl esters; FAMEs) which can be produced in a microbial cell factory. Saccharomyces cerevisiae is a suitable candidate for microbial large scale and long term cultivations, which is the typical industrial production setting for biofuels. It is crucial to conserve the metabolic design of the cell factory during industrial cultivation conditions that require extensive propagation. Genetic modifications therefore have to be introduced in a stable manner. Here, several metabolic engineering strategies for improved production of fatty acid ethyl esters in S. cerevisiae were combined and the genes were stably expressed from the organisms' chromosomes. A wax ester synthase (ws2) was expressed in different yeast strains with an engineered acetyl-CoA and fatty acid metabolism. Thus, we compared expression of ws2 with and without overexpression of alcohol dehydrogenase (ADH2), acetaldehyde dehydrogenase (ALD6) and acetyl-CoA synthetase (acs SE (L641P) ) and further evaluated additional overexpression of a mutant version of acetyl-CoA decarboxylase (ACC1 (S1157A,S659A) ) and the acyl-CoA binding protein (ACB1). The combined engineering efforts of the implementation of ws2, ADH2, ALD6 and acs SE (L641P) , ACC1 (S1157A,S659A) and ACB1 in a S. cerevisiae strain lacking storage lipid formation (are1Δ, are2Δ, dga1Δ and lro1Δ) and β-oxidation (pox1Δ) resulted in a 4.1-fold improvement compared with sole expression of ws2 in S. cerevisiae.

Improving industrial yeast strains: exploiting natural and artificial diversity

Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.

Synthetic microbial consortia: from systematic analysis to construction and applications

Synthetic biology is an emerging research field that focuses on using rational engineering strategies to program biological systems, conferring on them new functions and behaviours. By developing genetic parts and devices based on transcriptional, translational, post-translational modules, many genetic circuits and metabolic pathways had been programmed in single cells. Extending engineering capabilities from single-cell behaviours to multicellular microbial consortia represents a new frontier of synthetic biology. Herein, we first reviewed binary interaction modes of microorganisms in microbial consortia and their underlying molecular mechanisms, which lay the foundation of programming cell-cell interactions in synthetic microbial consortia. Systems biology studies on cellular systems enable systematic understanding of diverse physiological processes of cells and their interactions, which in turn offer insights into the optimal design of synthetic consortia. Based on such fundamental understanding, a comprehensive array of synthetic microbial consortia constructed in the last decade were reviewed, including isogenic microbial communities programmed by quorum sensing-based cell-cell communications, sender-receiver microbial communities with one-way communications, and microbial ecosystems wired by two-way (bi-directional) communications. Furthermore, many applications including using synthetic microbial consortia for distributed bio-computations, chemicals and bioenergy production, medicine and human health, and environments were reviewed. Synergistic development of systems and synthetic biology will provide both a thorough understanding of naturally occurring microbial consortia and rational engineering of these complicated consortia for novel applications.

Current development in genetic engineering strategies of Bacillus species

The complete sequencing and annotation of the genomes of industrially-important Bacillus species has enhanced our understanding of their properties, and allowed advances in genetic manipulations in other Bacillus species. Post-genomic studies require simple and highly efficient tools to enable genetic manipulation. Here, we summarize the recent progress in genetic engineering strategies for Bacillus species. We review the available genetic tools that have been developed in Bacillus species, as well as methods developed in other species that may also be applicable in Bacillus. Furthermore, we address the limitations and challenges of the existing methods, and discuss the future research prospects in developing novel and useful tools for genetic modification of Bacillus species.

An auto-inducible mechanism for ionic liquid resistance in microbial biofuel production

Ionic liquids (ILs) are emerging as superior solvents for numerous industrial applications, including the pretreatment of biomass for the microbial production of biofuels. However, some of the most effective ILs used to solubilize cellulose inhibit microbial growth, decreasing efficiency in the overall process. Here we identify an IL-resistance mechanism consisting of two adjacent genes from Enterobacter lignolyticus, a rain forest soil bacterium that is tolerant to an imidazolium-based IL. These genes retain their full functionality when transferred to an Escherichia coli biofuel host, with IL resistance established by an inner membrane transporter, regulated by an IL-inducible repressor. Expression of the transporter is dynamically adjusted in direct response to IL, enabling growth and biofuel production at levels of IL that are toxic to native strains. This natural auto-regulatory system provides the basis for engineering IL-tolerant microbes, which should accelerate progress towards effective conversion of lignocellulosic biomass to fuels and renewable chemicals.

Improved production of fatty acid ethyl esters in Saccharomyces cerevisiae through up-regulation of the ethanol degradation pathway and expression of the heterologous phosphoketolase pathway

BACKGROUND

Due to an increasing demand of transportation fuels, a lower availability of cheap crude oil and a lack of sustainability of fossil fuels, a gradual shift from petroleum based fuels towards alternative and renewable fuel resources will be required in the near future. Fatty acid ethyl esters (FAEEs) have properties similar to current crude diesel and could therefore form an important contribution to the development of sustainable transportation fuels in future. It is important to develop novel cell factories for efficient production of FAEEs and their precursors.

RESULTS

Here, a Saccharomyces cerevisiae cell factory expressing a heterologous wax ester synthase (ws2) from Marinobacter hydrocarbonoclasticus was used to produce FAEEs from ethanol and acyl-coenzyme A (acyl-CoA). The production of acyl-CoA requires large amounts of NADPH and acetyl-CoA. Therefore, two metabolic engineering strategies for improved provision of NADPH and acetyl-CoA were evaluated. First, the ethanol degradation pathway was employed to re-channel carbon flow towards the synthesis of acetyl-CoA. Therefore, ADH2 and ALD6 encoding, respectively, alcohol dehydrogenase and acetaldehyde dehydrogenase were overexpressed together with the heterologous gene acsSEL641P encoding acetyl-CoA synthetase. The co-overexpression of ADH2, ALD6 and acsSEL641P with ws2 resulted in 408 ± 270 μg FAEE gCDW-1, a 3-fold improvement. Secondly, for the expression of the PHK pathway two genes, xpkA and ack, both descending from Aspergillus nidulans, were co-expressed together with ws2 to catalyze, respectively, the conversion of xylulose-5-phosphate to acetyl phosphate and glyceraldehyde-3-phosphate and acetyl phosphate to acetate. Alternatively, ack was substituted with pta from Bacillus subtilis, encoding phosphotransacetylase for the conversion of acetyl phosphate to acetyl-CoA. Both PHK pathways were additionally expressed in a strain with multiple chromosomally integrated ws2 gene, which resulted in respectively 5100 ± 509 and 4670 ± 379 μg FAEE gCDW-1, an up to 1.7-fold improvement.

CONCLUSION

Two different strategies for engineering of the central carbon metabolism for efficient provision of acetyl-CoA and NADPH required for fatty acid biosynthesis and hence FAEE production were evaluated and it was found that both the ethanol degradation pathway as well as the phosphoketolase pathway improve the yield of FAEEs.

Whole-cell biocatalysis for selective and productive C-O functional group introduction and modification

During the last decades, biocatalysis became of increasing importance for chemical and pharmaceutical industries. Regarding regio- and stereospecificity, enzymes have shown to be superior compared to traditional chemical synthesis approaches, especially in C-O functional group chemistry. Catalysts established on a process level are diverse and can be classified along a functional continuum starting with single-step biotransformations using isolated enzymes or microbial strains towards fermentative processes with recombinant microorganisms containing artificial synthetic pathways. The complex organization of respective enzymes combined with aspects such as cofactor dependency and low stability in isolated form often favors the use of whole cells over that of isolated enzymes. Based on an inventory of the large spectrum of biocatalytic C-O functional group chemistry, this review focuses on highlighting the potentials, limitations, and solutions offered by the application of self-regenerating microbial cells as biocatalysts. Different cellular functionalities are discussed in the light of their (possible) contribution to catalyst efficiency. The combined achievements in the areas of protein, genetic, metabolic, and reaction engineering enable the development of whole-cell biocatalysts as powerful tools in organic synthesis.

COFACTOR MODIFICATION ANALYSIS: A COMPUTATIONAL FRAMEWORK TO IDENTIFY COFACTOR SPECIFICITY ENGINEERING TARGETS FOR STRAIN IMPROVEMENT

Cofactors, such as NAD(H) and NADP(H), play important roles in energy transfer within the cells by providing the necessary redox carriers for a myriad of metabolic reactions, both anabolic and catabolic. Thus, it is crucial to establish the overall cellular redox balance for achieving the desired cellular physiology. Of several methods to manipulate the intracellular cofactor regeneration rates, altering the cofactor specificity of a particular enzyme is a promising one. However, the identification of relevant enzyme targets for such cofactor specificity engineering (CSE) is often very difficult and labor intensive. Therefore, it is necessary to develop more systematic approaches to find the cofactor engineering targets for strain improvement. Presented herein is a novel mathematical framework, cofactor modification analysis (CMA), developed based on the well-established constraints-based flux analysis, for the systematic identification of suitable CSE targets while exploring the global metabolic effects. The CMA algorithm was applied to E. coli using its genome-scale metabolic model, iJO1366, thereby identifying the growth-coupled cofactor engineering targets for overproducing four of its native products: acetate, formate, ethanol, and lactate, and three non-native products: 1-butanol, 1,4-butanediol, and 1,3-propanediol. Notably, among several target candidates for cofactor engineering, glyceraldehyde-3-phosphate dehydrogenase (GAPD) is the most promising enzyme; its cofactor modification enhanced both the desired product and biomass yields significantly. Finally, given the identified target, we further discussed potential mutational strategies for modifying cofactor specificity of GAPD in E. coli as suggested by in silico protein docking experiments.

A laboratory-scale pretreatment and hydrolysis assay for determination of reactivity in cellulosic biomass feedstocks

BACKGROUND

The rapid determination of the release of structural sugars from biomass feedstocks is an important enabling technology for the development of cellulosic biofuels. An assay that is used to determine sugar release for large numbers of samples must be robust, rapid, and easy to perform, and must use modest amounts of the samples to be tested.In this work we present a laboratory-scale combined pretreatment and saccharification assay that can be used as a biomass feedstock screening tool. The assay uses a commercially available automated solvent extraction system for pretreatment followed by a small-scale enzymatic hydrolysis step. The assay allows multiple samples to be screened simultaneously, and uses only ~3 g of biomass per sample. If the composition of the biomass sample is known, the results of the assay can be expressed as reactivity (fraction of structural carbohydrate present in the biomass sample released as monomeric sugars).

RESULTS

We first present pretreatment and enzymatic hydrolysis experiments on a set of representative biomass feedstock samples (corn stover, poplar, sorghum, switchgrass) in order to put the assay in context, and then show the results of the assay applied to approximately 150 different feedstock samples covering 5 different materials. From the compositional analysis data we identify a positive correlation between lignin and structural carbohydrates, and from the reactivity data we identify a negative correlation between both carbohydrate and lignin content and total reactivity. The negative correlation between lignin content and total reactivity suggests that lignin may interfere with sugar release, or that more mature samples (with higher structural sugars) may have more recalcitrant lignin.

CONCLUSIONS

The assay presented in this work provides a robust and straightforward method to measure the sugar release after pretreatment and saccharification that can be used as a biomass feedstock screening tool. We demonstrated the utility of the assay by identifying correlations between feedstock composition and reactivity in a population of 150 samples.

Fermentation of xylose causes inefficient metabolic state due to carbon/energy starvation and reduced glycolytic flux in recombinant industrial Saccharomyces cerevisiae

In the present study, comprehensive, quantitative metabolome analysis was carried out on the recombinant glucose/xylose-cofermenting S. cerevisiae strain MA-R4 during fermentation with different carbon sources, including glucose, xylose, or glucose/xylose mixtures. Capillary electrophoresis time-of-flight mass spectrometry was used to determine the intracellular pools of metabolites from the central carbon pathways, energy metabolism pathways, and the levels of twenty amino acids. When xylose instead of glucose was metabolized by MA-R4, glycolytic metabolites including 3- phosphoglycerate, 2- phosphoglycerate, phosphoenolpyruvate, and pyruvate were dramatically reduced, while conversely, most pentose phosphate pathway metabolites such as sedoheptulose 7- phosphate and ribulose 5-phosphate were greatly increased. These results suggest that the low metabolic activity of glycolysis and the pool of pentose phosphate pathway intermediates are potential limiting factors in xylose utilization. It was further demonstrated that during xylose fermentation, about half of the twenty amino acids declined, and the adenylate/guanylate energy charge was impacted due to markedly decreased adenosine triphosphate/adenosine monophosphate and guanosine triphosphate/guanosine monophosphate ratios, implying that the fermentation of xylose leads to an inefficient metabolic state where the biosynthetic capabilities and energy balance are severely impaired. In addition, fermentation with xylose alone drastically increased the level of citrate in the tricarboxylic acid cycle and increased the aromatic amino acids tryptophan and tyrosine, strongly supporting the view that carbon starvation was induced. Interestingly, fermentation with xylose alone also increased the synthesis of the polyamine spermidine and its precursor S-adenosylmethionine. Thus, differences in carbon substrates, including glucose and xylose in the fermentation medium, strongly influenced the dynamic metabolism of MA-R4. These results provide a metabolic explanation for the low ethanol productivity on xylose compared to glucose.

Specific growth rate and substrate dependent polyhydroxybutyrate production in Saccharomyces cerevisiae

Production of the biopolymer polyhydroxybutyrate (PHB) in Saccharomyces cerevisiae starts at the end of exponential phase particularly when the specific growth rate is decreased due to the depletion of glucose in the medium. The specific growth rate and the type of carbon source (fermentable/non-fermentable) have been known to influence the cell physiology and hence affect the fermentability of S. cerevisiae. The production of PHB utilizes cytosolic acetyl-CoA as a precursor and the S. cerevisiae employed in this study is therefore a strain with the enhanced cytosolic acetyl-CoA supply. Growth and PHB production at different specific growth rates were evaluated on glucose, ethanol and a mixture of glucose and ethanol as carbon source. Ethanol as carbon source yielded a higher PHB production compared to glucose since it can be directly used for cytosolic acetyl-CoA production and hence serves as a precursor for PHB production. However, this carbon source results in lower biomass yield and hence it was found that to ensure both biomass formation and PHB production a mixture of glucose and ethanol was optimal, and this resulted in the highest volumetric productivity of PHB, 8.23 mg/L · h^-1, at a dilution rate of 0.1 h^-1.

Transporter engineering for improved tolerance against alkane biofuels in Saccharomyces cerevisiae

BACKGROUND

Hydrocarbon alkanes, components of major fossil fuels, are considered as next-generation biofuels because their biological production has recently been shown to be possible. However, high-yield alkane production requires robust host cells that are tolerant against alkanes, which exhibit cytotoxicity. In this study, we aimed to improve alkane tolerance in Saccharomyces cerevisiae, a key industrial microbial host, by harnessing heterologous transporters that potentially pump out alkanes.

RESULTS

To this end, we attempted to exploit ABC transporters in Yarrowia lipolytica based on the observation that it utilizes alkanes as a carbon source. We confirmed the increased transcription of ABC2 and ABC3 transporters upon exposure to a range of alkanes in Y. lipolytica. We then showed that the heterologous expression of ABC2 and ABC3 transporters significantly increased tolerance against decane and undecane in S. cerevisiae through maintaining lower intracellular alkane level. In particular, ABC2 transporter increased the tolerance limit of S. cerevisiae about 80-fold against decane. Furthermore, through site-directed mutagenesis for glutamate (E988 for ABC2, and E989 for ABC3) and histidine (H1020 for ABC2, and H1021 for ABC3), we provided the evidence that glutamate was essential for the activity of ABC2 and ABC3 transporters, with ATP most likely to be hydrolyzed by a catalytic carboxylate mechanism.

CONCLUSIONS

Here, we demonstrated that transporter engineering through expression of heterologous efflux pumps led to significantly improved tolerance against alkane biofuels in S. cerevisiae. We believe that our results laid the groundwork for developing robust alkane-producing yeast cells through transporter engineering, which will greatly aid in next-generation alkane biofuel production and recovery.