Metabolome, transcriptome and metabolic flux analysis of arabinose fermentation by engineered Saccharomyces cerevisiae

Top-Down, Knowledge-Based Genetic Reduction of Yeast Central Carbon Metabolism

Saccharomyces cerevisiae, whose evolutionary past includes a whole-genome duplication event, is characterized by a mosaic genome configuration with substantial apparent genetic redundancy. This apparent redundancy raises questions about the evolutionary driving force for genomic fixation of “minor” paralogs and complicates modular and combinatorial metabolic engineering strategies. While isoenzymes might be important in specific environments, they could be dispensable in controlled laboratory or industrial contexts. The present study explores the extent to which the genetic complexity of the central carbon metabolism (CCM) in S. cerevisiae, here defined as the combination of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and a limited number of related pathways and reactions, can be reduced by elimination of (iso)enzymes without major negative impacts on strain physiology. Cas9-mediated, groupwise deletion of 35 of the 111 genes yielded a “minimal CCM” strain which, despite the elimination of 32% of CCM-related proteins, showed only a minimal change in phenotype on glucose-containing synthetic medium in controlled bioreactor cultures relative to a congenic reference strain. Analysis under a wide range of other growth and stress conditions revealed remarkably few phenotypic changes from the reduction of genetic complexity. Still, a well-documented context-dependent role of GPD1 in osmotolerance was confirmed. The minimal CCM strain provides a model system for further research into genetic redundancy of yeast genes and a platform for strategies aimed at large-scale, combinatorial remodeling of yeast CCM.

Ethanol yield improvement in Saccharomyces cerevisiae GPD2 Delta FPS1 Delta ADH2 Delta DLD3 Delta mutant and molecular mechanism exploration based on the metabolic flux and transcriptomics approaches

Background

Saccharomyces cerevisiae generally consumes glucose to produce ethanol accompanied by the main by-products of glycerol, acetic acid, and lactic acid. The minimization of the formation of by-products in S. cerevisiae was an effective way to improve the economic viability of the bioethanol industry. In this study, S. cerevisiae GPD2, FPS1, ADH2, and DLD3 genes were knocked out by the Clustered Regularly Interspaced Short Palindromic Repeats Cas9 (CRISPR-Cas9) approach. The mechanism of gene deletion affecting ethanol metabolism was further elucidated based on metabolic flux and transcriptomics approaches.

Results

The engineered S. cerevisiae with gene deletion of GPD2, FPS1, ADH2, and DLD3 was constructed by the CRISPR-Cas9 approach. The ethanol content of engineered S. cerevisiae GPD2 Delta FPS1 Delta ADH2 Delta DLD3 Delta increased by 18.58% with the decrease of glycerol, acetic acid, and lactic acid contents by 22.32, 8.87, and 16.82%, respectively. The metabolic flux analysis indicated that the carbon flux r_ethanol in engineered strain increased from 60.969 to 63.379. The sequencing-based RNA-Seq transcriptomics represented 472 differential expression genes (DEGs) were identified in engineered S. cerevisiae, in which 195 and 277 genes were significantly up-regulated and down-regulated, respectively. The enriched pathways of up-regulated genes were mainly involved in the energy metabolism of carbohydrates, while the down-regulated genes were mainly enriched in acid metabolic pathways.

Conclusions

The yield of ethanol in engineered S. cerevisiae increased with the decrease of the by-products including glycerol, acetic acid, and lactic acid. The deletion of genes GPD2, FPS1, ADH2, and DLD3 resulted in the redirection of carbon flux.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01885-3.

Reassessment of requirements for anaerobic xylose fermentation by engineered, non-evolved Saccharomyces cerevisiae strains

Expression of a heterologous xylose isomerase, deletion of the GRE3 aldose-reductase gene and overexpression of genes encoding xylulokinase (XKS1) and non-oxidative pentose-phosphate-pathway enzymes (RKI1, RPE1, TAL1, TKL1) enables aerobic growth of Saccharomyces cerevisiae on d-xylose. However, literature reports differ on whether anaerobic growth on d-xylose requires additional mutations. Here, CRISPR-Cas9-assisted reconstruction and physiological analysis confirmed an early report that this basic set of genetic modifications suffices to enable anaerobic growth on d-xylose in the CEN.PK genetic background. Strains that additionally carried overexpression cassettes for the transaldolase and transketolase paralogs NQM1 and TKL2 only exhibited anaerobic growth on d-xylose after a 7–10 day lag phase. This extended lag phase was eliminated by increasing inoculum concentrations from 0.02 to 0.2 g biomass L⁻¹. Alternatively, a long lag phase could be prevented by sparging low-inoculum-density bioreactor cultures with a CO₂/N₂-mixture, thus mimicking initial CO₂ concentrations in high-inoculum-density, nitrogen-sparged cultures, or by using l-aspartate instead of ammonium as nitrogen source. This study resolves apparent contradictions in the literature on the genetic interventions required for anaerobic growth of CEN.PK-derived strains on d-xylose. Additionally, it indicates the potential relevance of CO₂ availability and anaplerotic carboxylation reactions for anaerobic growth of engineered S. cerevisiae strains on d-xylose.

Laboratory evolution of a glucose-phosphorylation-deficient, arabinose-fermenting S. cerevisiae strain reveals mutations in GAL2 that enable glucose-insensitive l-arabinose uptake

Cas9-assisted genome editing was used to construct an engineered glucose-phosphorylation-negative S. cerevisiae strain, expressing the Lactobacillus plantaruml-arabinose pathway and the Penicillium chrysogenum transporter PcAraT. This strain, which showed a growth rate of 0.26 h⁻¹ on l-arabinose in aerobic batch cultures, was subsequently evolved for anaerobic growth on l-arabinose in the presence of d-glucose and d-xylose. In four strains isolated from two independent evolution experiments the galactose-transporter gene GAL2 had been duplicated, with all alleles encoding Gal2^N376T or Gal2^N376I substitutions. In one strain, a single GAL2 allele additionally encoded a Gal2^T89I substitution, which was subsequently also detected in the independently evolved strain IMS0010. In ¹⁴C-sugar-transport assays, Gal2^N376S, Gal2^N376T and Gal2^N376I substitutions showed a much lower glucose sensitivity of l-arabinose transport and a much higher K_m for d-glucose transport than wild-type Gal2. Introduction of the Gal2^N376I substitution in a non-evolved strain enabled growth on l-arabinose in the presence of d-glucose. Gal2^{N376T, T89I} and Gal2^T89I variants showed a lower K_m for l-arabinose and a higher K_m for d-glucose than wild-type Gal2, while reverting Gal2^{N376T, T89I} to Gal2^N376 in an evolved strain negatively affected anaerobic growth on l-arabinose. This study indicates that optimal conversion of mixed-sugar feedstocks may require complex ‘transporter landscapes’, consisting of sugar transporters with complementary kinetic and regulatory properties.

Approaches to Computational Strain Design in the Multiomics Era

Modern omics analyses are able to effectively characterize the genetic, regulatory, and metabolic phenotypes of engineered microbes, yet designing genetic interventions to achieve a desired phenotype remains challenging. With recent developments in genetic engineering techniques, timelines associated with building and testing strain designs have been greatly reduced, allowing for the first time an efficient closed loop iteration between experiment and analysis. However, the scale and complexity associated with multi-omics datasets complicates manual biological reasoning about the mechanisms driving phenotypic changes. Computational techniques therefore form a critical part of the Design-Build-Test-Learn (DBTL) cycle in metabolic engineering. Traditional statistical approaches can reduce the dimensionality of these datasets and identify common motifs among high-performing strains. While successful in many studies, these methods do not take full advantage of known connections between genes, proteins, and metabolic networks. There is therefore a growing interest in model-aided design, in which modeling frameworks from systems biology are used to integrate experimental data and generate effective and non-intuitive design predictions. In this mini-review, we discuss recent progress and challenges in this field. In particular, we compare methods augmenting flux balance analysis with additional constraints from fluxomic, genomic, and metabolomic datasets and methods employing kinetic representations of individual metabolic reactions, and machine learning. We conclude with a discussion of potential future directions for improving strain design predictions in the omics era and remaining experimental and computational hurdles.

Pentose Metabolism in Saccharomyces cerevisiae: The Need to Engineer Global Regulatory Systems

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Transporter engineering in biomass utilization by yeast

Biomass resources are attractive carbon sources for bioproduction because of their sustainability. Many studies have been performed using biomass resources to produce sugars as carbon sources for cell factories. Expression of biomass hydrolyzing enzymes in cell factories is an important approach for constructing biomass-utilizing bioprocesses because external addition of these enzymes is expensive. In particular, yeasts have been extensively engineered to be cell factories that directly utilize biomass because of their manageable responses to many genetic engineering tools, such as gene expression, deletion and editing. Biomass utilizing bioprocesses have also been developed using these genetic engineering tools to construct metabolic pathways. However, sugar input and product output from these cells are critical factors for improving bioproduction along with biomass utilization and metabolic pathways. Transporters are key components for efficient input and output activities. In this review, we focus on transporter engineering in yeast to enhance bioproduction from biomass resources.

Incorporating comparative genomics into the design-test-learn cycle of microbial strain engineering

Engineering microbes with new properties is an important goal in industrial engineering, to establish biological factories for production of biofuels, commodity chemicals and pharmaceutics. But engineering microbes to produce new compounds with high yield remains a major challenge toward economically viable production. Incorporating several modern approaches, including synthetic and systems biology, metabolic modeling and regulatory rewiring, has proven to significantly advance industrial strain engineering. This review highlights how comparative genomics can also facilitate strain engineering, by identifying novel genes and pathways, regulatory mechanisms and genetic background effects for engineering. We discuss how incorporating comparative genomics into the design-test-learn cycle of strain engineering can provide novel information that complements other engineering strategies.

Optimizing anaerobic growth rate and fermentation kinetics in Saccharomyces cerevisiae strains expressing Calvin-cycle enzymes for improved ethanol yield

BACKGROUND

Reduction or elimination of by-product formation is of immediate economic relevance in fermentation processes for industrial bioethanol production with the yeast Saccharomyces cerevisiae. Anaerobic cultures of wild-type S. cerevisiae require formation of glycerol to maintain the intracellular NADH/NAD+ balance. Previously, functional expression of the Calvin-cycle enzymes ribulose-1,5-bisphosphate carboxylase (RuBisCO) and phosphoribulokinase (PRK) in S. cerevisiae was shown to enable reoxidation of NADH with CO2 as electron acceptor. In slow-growing cultures, this engineering strategy strongly decreased the glycerol yield, while increasing the ethanol yield on sugar. The present study explores engineering strategies to improve rates of growth and alcoholic fermentation in yeast strains that functionally express RuBisCO and PRK, while maximizing the positive impact on the ethanol yield.

RESULTS

Multi-copy integration of a bacterial-RuBisCO expression cassette was combined with expression of the Escherichia coli GroEL/GroES chaperones and expression of PRK from the anaerobically inducible DAN1 promoter. In anaerobic, glucose-grown bioreactor batch cultures, the resulting S. cerevisiae strain showed a 31% lower glycerol yield and a 31% lower specific growth rate than a non-engineered reference strain. Growth of the engineered strain in anaerobic, glucose-limited chemostat cultures revealed a negative correlation between its specific growth rate and the contribution of the Calvin-cycle enzymes to redox homeostasis. Additional deletion of GPD2, which encodes an isoenzyme of NAD+-dependent glycerol-3-phosphate dehydrogenase, combined with overexpression of the structural genes for enzymes of the non-oxidative pentose-phosphate pathway, yielded a CO2-reducing strain that grew at the same rate as a non-engineered reference strain in anaerobic bioreactor batch cultures, while exhibiting a 86% lower glycerol yield and a 15% higher ethanol yield.

CONCLUSIONS

The metabolic engineering strategy presented here enables an almost complete elimination of glycerol production in anaerobic, glucose-grown batch cultures of S. cerevisiae, with an associated increase in ethanol yield, while retaining near wild-type growth rates and a capacity for glycerol formation under osmotic stress. Using current genome-editing techniques, the required genetic modifications can be introduced in one or a few transformations. Evaluation of this concept in industrial strains and conditions is therefore a realistic next step towards its implementation for improving the efficiency of first- and second-generation bioethanol production.

Saccharomyces cerevisiae strains for second-generation ethanol production: from academic exploration to industrial implementation

The recent start-up of several full-scale 'second generation' ethanol plants marks a major milestone in the development of Saccharomyces cerevisiae strains for fermentation of lignocellulosic hydrolysates of agricultural residues and energy crops. After a discussion of the challenges that these novel industrial contexts impose on yeast strains, this minireview describes key metabolic engineering strategies that have been developed to address these challenges. Additionally, it outlines how proof-of-concept studies, often developed in academic settings, can be used for the development of robust strain platforms that meet the requirements for industrial application. Fermentation performance of current engineered industrial S. cerevisiae strains is no longer a bottleneck in efforts to achieve the projected outputs of the first large-scale second-generation ethanol plants. Academic and industrial yeast research will continue to strengthen the economic value position of second-generation ethanol production by further improving fermentation kinetics, product yield and cellular robustness under process conditions.

Identification of Important Amino Acids in Gal2p for Improving the L-arabinose Transport and Metabolism in Saccharomyces cerevisiae

Efficient and cost-effective bioethanol production from lignocellulosic materials requires co-fermentation of the main hydrolyzed sugars, including glucose, xylose, and L-arabinose. Saccharomyces cerevisiae is a glucose-fermenting yeast that is traditionally used for ethanol production. Fermentation of L-arabinose is also possible after metabolic engineering. Transport into the cell is the first and rate-limiting step for L-arabinose metabolism. The galactose permease, Gal2p, is a non-specific, endogenous monosaccharide transporter that has been shown to transport L-arabinose. However, Gal2p-mediated transport of L-arabinose occurs at a low efficiency. In this study, homologous modeling and L-arabinose docking were used to predict amino acids in Gal2p that are crucial for L-arabinose transport. Nine amino acid residues in Gal2p were identified and were the focus for site-directed mutagenesis. In the Gal2p transport-deficient chassis cells, the capacity for L-arabinose transport of the different Gal2p mutants was compared by testing growth rates using L-arabinose as the sole carbon source. Almost all the tested mutations affected L-arabinose transport capacity. Among them, F85 is a unique site. The F85S, F85G, F85C, and F85T point mutations significantly increased L-arabinose transport activities, while, the F85E and F85R mutations decreased L-arabinose transport activities compared to the Gal2p-expressing wild-type strain. These results verified F85 as a key residue in L-arabinose transport. The F85S mutation, having the most significant effect, elevated the exponential growth rate by 40%. The F85S mutation also improved xylose transport efficiency and weakened the glucose transport preference. Overall, enhancing the L-arabinose transport capacity further improved the L-arabinose metabolism of engineered S. cerevisiae.

Mutations in PMR1 stimulate xylose isomerase activity and anaerobic growth on xylose of engineered Saccharomyces cerevisiae by influencing manganese homeostasis

Combined overexpression of xylulokinase, pentose-phosphate-pathway enzymes and a heterologous xylose isomerase (XI) is required but insufficient for anaerobic growth of Saccharomyces cerevisiae on d-xylose. Single-step Cas9-assisted implementation of these modifications yielded a yeast strain expressing Piromyces XI that showed fast aerobic growth on d-xylose. However, anaerobic growth required a 12-day adaptation period. Xylose-adapted cultures carried mutations in PMR1, encoding a Golgi Ca2+/Mn2+ ATPase. Deleting PMR1 in the parental XI-expressing strain enabled instantaneous anaerobic growth on d-xylose. In pmr1 strains, intracellular Mn2+ concentrations were much higher than in the parental strain. XI activity assays in cell extracts and reconstitution experiments with purified XI apoenzyme showed superior enzyme kinetics with Mn2+ relative to other divalent metal ions. This study indicates engineering of metal homeostasis as a relevant approach for optimization of metabolic pathways involving metal-dependent enzymes. Specifically, it identifies metal interactions of heterologous XIs as an underexplored aspect of engineering xylose metabolism in yeast.

Genome scale models of yeast: towards standardized evaluation and consistent omic integration

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted.

Biosorption and degradation of decabromodiphenyl ether by Brevibacillus brevis and the influence of decabromodiphenyl ether on cellular metabolic responses

There is global concern about the effects of decabromodiphenyl ether (BDE209) on environmental and public health. The molecular properties, biosorption, degradation, accumulation, and cellular metabolic effects of BDE209 were investigated in this study to identify the mechanisms involved in the aerobic biodegradation of BDE209. BDE209 is initially absorbed by wall teichoic acid and N-acetylglucosamine side chains in peptidoglycan, and then, BDE209 is transported and debrominated through three pathways, giving tri-, hepta-, octa-, and nona-bromodiphenyl ethers. The C-C bond energies decrease as the number of bromine atoms on the diphenyl decreases. Polybrominated diphenyl ethers (PBDEs) inhibit protein expression or accelerate protein degradation and increase membrane permeability and the release of Cl(-), Na(+), NH4 (+), arabinose, proteins, acetic acid, and oxalic acid. However, PBDEs increase the amounts of K(+), Mg(2+), PO4 (3-), SO4 (2-), and NO3 (-) assimilated. The biosorption, degradation, accumulation, and removal efficiencies when Brevibacillus brevis (1 g L(-1)) was exposed to BDE209 (0.5 mg L(-1)) for 7 days were 7.4, 69.5, 16.3, and 94.6 %, respectively.

Heterologous xylose isomerase pathway and evolutionary engineering improve xylose utilization in Saccharomyces cerevisiae

Xylose utilization is one key issue for the bioconversion of lignocelluloses. It is a promising approach to engineering heterologous pathway for xylose utilization in Saccharomyces cerevisiae. Here, we constructed a xylose-fermenting yeast SyBE001 through combinatorial fine-tuning the expression of XylA and endogenous XKS1. Additional overexpression of genes RKI1, RPE1, TKL1, and TAL1 in the non-oxidative pentose phosphate pathway (PPP) in SyBE001 increased the xylose consumption rate by 1.19-fold. By repetitive adaptation, the xylose utilization rate was further increased by ∼10-fold in the resultant strain SyBE003. Gene expression analysis identified a variety of genes with significantly changed expression in the PPP, glycolysis and the tricarboxylic acid cycle in SyBE003.

A Minimal Set of Glycolytic Genes Reveals Strong Redundancies in Saccharomyces cerevisiae Central Metabolism

As a result of ancestral whole-genome and small-scale duplication events, the genomes of Saccharomyces cerevisiae and many eukaryotes still contain a substantial fraction of duplicated genes. In all investigated organisms, metabolic pathways, and more particularly glycolysis, are specifically enriched for functionally redundant paralogs. In ancestors of the Saccharomyces lineage, the duplication of glycolytic genes is purported to have played an important role leading to S. cerevisiae's current lifestyle favoring fermentative metabolism even in the presence of oxygen and characterized by a high glycolytic capacity. In modern S. cerevisiae strains, the 12 glycolytic reactions leading to the biochemical conversion from glucose to ethanol are encoded by 27 paralogs. In order to experimentally explore the physiological role of this genetic redundancy, a yeast strain with a minimal set of 14 paralogs was constructed (the "minimal glycolysis" [MG] strain). Remarkably, a combination of a quantitative systems approach and semiquantitative analysis in a wide array of growth environments revealed the absence of a phenotypic response to the cumulative deletion of 13 glycolytic paralogs. This observation indicates that duplication of glycolytic genes is not a prerequisite for achieving the high glycolytic fluxes and fermentative capacities that are characteristic of S. cerevisiae and essential for many of its industrial applications and argues against gene dosage effects as a means of fixing minor glycolytic paralogs in the yeast genome. The MG strain was carefully designed and constructed to provide a robust prototrophic platform for quantitative studies and has been made available to the scientific community.

Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure

Microbial communities play important roles in health, industrial applications and earth's ecosystems. With current molecular techniques we can characterize these systems in unprecedented detail. However, such methods provide little mechanistic insight into how the genetic properties and the dynamic couplings between individual microorganisms give rise to their dynamic activities. Neither do they give insight into what we call “the community state”, that is the fluxes and concentrations of nutrients within the community. This knowledge is a prerequisite for rational control and intervention in microbial communities. Therefore, the inference of the community structure from experimental data is a major current challenge. We will argue that this inference problem requires mathematical models that can integrate heterogeneous experimental data with existing knowledge. We propose that two types of models are needed. Firstly, mathematical models that integrate existing genomic, physiological, and physicochemical information with metagenomics data so as to maximize information content and predictive power. This can be achieved with the use of constraint-based genome-scale stoichiometric modeling of community metabolism which is ideally suited for this purpose. Next, we propose a simpler coarse-grained model, which is tailored to solve the inference problem from the experimental data. This model unambiguously relate to the more detailed genome-scale stoichiometric models which act as heterogeneous data integrators. The simpler inference models are, in our opinion, key to understanding microbial ecosystems, yet until now, have received remarkably little attention. This has led to the situation where the modeling of microbial communities, using only genome-scale models is currently more a computational, theoretical exercise than a method useful to the experimentalist.

Metabolomic and (13)C-metabolic flux analysis of a xylose-consuming Saccharomyces cerevisiae strain expressing xylose isomerase

Over the past two decades, significant progress has been made in the engineering of xylose-consuming Saccharomyces cerevisiae strains for production of lignocellulosic biofuels. However, the ethanol productivities achieved on xylose are still significantly lower than those observed on glucose for reasons that are not well understood. We have undertaken an analysis of central carbon metabolite pool sizes and metabolic fluxes on glucose and on xylose under aerobic and anaerobic conditions in a strain capable of rapid xylose assimilation via xylose isomerase in order to investigate factors that may limit the rate of xylose fermentation. We find that during xylose utilization the flux through the non-oxidative Pentose Phosphate Pathway (PPP) is high but the flux through the oxidative PPP is low, highlighting an advantage of the strain employed in this study. Furthermore, xylose fails to elicit the full carbon catabolite repression response that is characteristic of glucose fermentation in S. cerevisiae. We present indirect evidence that the incomplete activation of the fermentation program on xylose results in a bottleneck in lower glycolysis, leading to inefficient re-oxidation of NADH produced in glycolysis.

Biosorption and biodegradation of triphenyltin by Stenotrophomonas maltophilia and their influence on cellular metabolism

Triphenyltin (TPT), an endocrine disruptor, is polluting the global environment through its worldwide use. However, information concerning the mechanisms of TPT biodegradation and cellular metabolism is severely limited. Therefore, these processes were elucidated through experiments involving TPT biosorption and degradation, intracellular metabolite analysis, nutrient use, ion and monosaccharide release, cellular membrane permeability and protein concentration quantification. The results verified that TPT was initially adsorbed by the cell surface of Stenotrophomonas maltophilia and was subsequently transported and degraded intracellularly with diphenyltin and monophenyltin production. Cl(-), Na(+), arabinose and glucose release, membrane permeability and the extracellular protein concentration increased during TPT treatment, whereas K(+) and PO4(3-) utilization and intracellular protein concentration declined. The biosorption, degradation and removal efficiencies of TPT at 0.5mgL(-1) by 0.3gL(-1) viable cells at 10 d were 3.8, 77.8 and 86.2%, respectively, and the adsorption efficiency by inactivated cells was 72.6%.

Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes

One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First, at the level of individual reactions, metabolite levels are non-linearly dependent on enzyme abundances as per the reaction kinetics mechanisms. Secondly, specific metabolite pools are tightly interlinked with the rest of the metabolic network through their production and consumption reactions. While the role of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different biological perturbations, namely gene knockout, nutrient shock and nutrient change. While the kinetic constraints applied at the level of individual reactions were found to be poor descriptors of the mRNA-metabolite relationship, their use in the context of the network enabled us to correlate changes in the expression of enzyme-coding genes to the alterations in metabolite levels. Our results highlight the key contribution of metabolic network connectivity in mediating cellular control over metabolite levels, and have implications towards bridging the gap between genotype and metabolic phenotype.

On the role of GAPDH isoenzymes during pentose fermentation in engineered Saccharomyces cerevisiae

In the metabolic network of the cell, many intermediary products are shared between different pathways. d-Glyceraldehyde-3-phosphate, a glycolytic intermediate, is a substrate of GAPDH but is also utilized by transaldolase and transketolase in the scrambling reactions of the nonoxidative pentose phosphate pathway. Recent efforts to engineer baker's yeast strains capable of utilizing pentose sugars present in plant biomass rely on increasing the carbon flux through this pathway. However, the competition between transaldolase and GAPDH for d-glyceraldehyde-3-phosphate produced in the first transketolase reaction compromises the carbon balance of the pathway, thereby limiting the product yield. Guided by the hypothesis that reduction in GAPDH activity would increase the availability of d-glyceraldehyde-3-phosphate for transaldolase and thereby improve ethanol production during fermentation of pentoses, we performed a comprehensive characterization of the three GAPDH isoenzymes in baker's yeast, Tdh1, Tdh2, and Tdh3 and analyzed the effect of their deletion on xylose utilization by engineered strains. Our data suggest that overexpression of transaldolase is a more promising strategy than reduction in GAPDH activity to increase the flux through the nonoxidative pentose phosphate pathway.

Enhanced expression of genes involved in initial xylose metabolism and the oxidative pentose phosphate pathway in the improved xylose-utilizing Saccharomyces cerevisiae through evolutionary engineering

Fermentation of xylose in lignocellulosic hydrolysates by Saccharomyces cerevisiae has been achieved through heterologous expression of the xylose reductase (XR)-xylitol dehydrogenase (XDH) pathway. However, the fermentation efficiency is far from the requirement for industrial application due to high yield of the byproduct xylitol, low ethanol yield, and low xylose consumption rate. Through evolutionary engineering, an improved xylose-utilizing strain SyBE005 was obtained with 78.3 % lower xylitol production and a 2.6-fold higher specific ethanol production rate than those of the parent strain SyBE004, which expressed an engineered NADP(+)-preferring XDH. The transcriptional differences between SyBE005 and SyBE004 were investigated by quantitative RT-PCR. Genes including XYL1, XYL2, and XKS1 in the initial xylose metabolic pathway showed the highest up-regulation in SyBE005. The increased expression of XYL1 and XYL2 correlated with enhanced enzymatic activities of XR and XDH. In addition, the expression level of ZWF1 in the oxidative pentose phosphate pathway increased significantly in SyBE005, indicating an elevated demand for NADPH from XR. Genes involved in the TCA cycle (LAT1, CIT1, CIT2, KGD1, KGD, SDH2) and gluconeogenesis (ICL1, PYC1) were also up-regulated in SyBE005. Genomic analysis revealed that point mutations in transcriptional regulators CYC8 and PHD1 might be responsible for the altered expression. In addition, a mutation (Y89S) in ZWF1 was identified which might improve NADPH production in SyBE005. Our results suggest that increasing the expression of XYL1, XYL2, XKS1, and enhancing NADPH supply are promising strategies to improve xylose fermentation in recombinant S. cerevisiae.

Improvement of L-arabinose fermentation by modifying the metabolic pathway and transport in Saccharomyces cerevisiae

The L-arabinose utilization pathway was established in Saccharomyces cerevisiae, by expressing the codon-optimized araA, araB, and araD genes of Lactobacillus plantarum. After overexpressing the TAL1, TKL1, RPE1, RKI1, and GAL2 genes and adaptive evolution, the L-arabinose utilization of the recombinant strain became efficient. The resulting strain displayed a maximum specific growth rate of 0.075 h⁻¹, a maximum specific L-arabinose consumption rate of 0.61 g h⁻¹ g⁻¹ dry cell weight, and a promising ethanol yield of 0.43 g g⁻¹ from L-arabinose fermentation.

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.

Adaptive laboratory evolution -- principles and applications for biotechnology

Adaptive laboratory evolution is a frequent method in biological studies to gain insights into the basic mechanisms of molecular evolution and adaptive changes that accumulate in microbial populations during long term selection under specified growth conditions. Although regularly performed for more than 25 years, the advent of transcript and cheap next-generation sequencing technologies has resulted in many recent studies, which successfully applied this technique in order to engineer microbial cells for biotechnological applications. Adaptive laboratory evolution has some major benefits as compared with classical genetic engineering but also some inherent limitations. However, recent studies show how some of the limitations may be overcome in order to successfully incorporate adaptive laboratory evolution in microbial cell factory design. Over the last two decades important insights into nutrient and stress metabolism of relevant model species were acquired, whereas some other aspects such as niche-specific differences of non-conventional cell factories are not completely understood. Altogether the current status and its future perspectives highlight the importance and potential of adaptive laboratory evolution as approach in biotechnological engineering.

Advances in Nutritional Metabolomics

Metabolomics is maturing as an experimental approach in nutrition science, and it is a useful analysis for revealing systems biology outcomes associated with changes in diet. A major goal of this review is to present the rapidly evolving body of scientific literature that seeks to reveal connections between an individual's metabolic profile and experimentally manipulated or naturally varied dietary intakes. Metabolite profiles in tissue, serum, urine, or stool reflect changes in metabolic pathways that respond to dietary intervention which makes them accessible samples for revealing metabolic effects of diet. Three broadly defined areas of investigation related to dietary-metabolomic strategies include: (1) describing the metabolite variation within and between dietary exposures or interventions; (2) characterizing the metabolic response to dietary interventions with respect to time; and (3) assessing individual variation in baseline nutritional health and/or disease status. An overview of metabolites that were responsive to dietary interventions as reported from original research in human or animal studies is provided and illustrates the breadth of metabolites affected by dietary intervention. Advantages and drawbacks for assessing metabolic changes are discussed in relation to types of metabolite analysis platforms. A combination of targeted and non-targeted global profiling studies as a component of future dietary intervention trials will increase our understanding of nutrition in a systems context.

Glucose-methanol co-utilization in Pichia pastoris studied by metabolomics and instationary ¹³C flux analysis

Background

Several studies have shown that the utilization of mixed carbon feeds instead of methanol as sole carbon source is beneficial for protein production with the methylotrophic yeast Pichia pastoris. In particular, growth under mixed feed conditions appears to alleviate the metabolic burden related to stress responses triggered by protein overproduction and secretion. Yet, detailed analysis of the metabolome and fluxome under mixed carbon source metabolizing conditions are missing. To obtain a detailed flux distribution of central carbon metabolism, including the pentose phosphate pathway under methanol-glucose conditions, we have applied metabolomics and instationary ¹³C flux analysis in chemostat cultivations.

Results

Instationary ¹³C-based metabolic flux analysis using GC-MS and LC-MS measurements in time allowed for an accurate mapping of metabolic fluxes of glycolysis, pentose phosphate and methanol assimilation pathways. Compared to previous results from NMR-derived stationary state labelling data (proteinogenic amino acids, METAFoR) more fluxes could be determined with higher accuracy. Furthermore, using a thermodynamic metabolic network analysis the metabolite measurements and metabolic flux directions were validated. Notably, the concentration of several metabolites of the upper glycolysis and pentose phosphate pathway increased under glucose-methanol feeding compared to the reference glucose conditions, indicating a shift in the thermodynamic driving forces. Conversely, the extracellular concentrations of all measured metabolites were lower compared with the corresponding exometabolome of glucose-grown P. pastoris cells.

The instationary ¹³C flux analysis resulted in fluxes comparable to previously obtained from NMR datasets of proteinogenic amino acids, but allowed several additional insights. Specifically, i) in vivo metabolic flux estimations were expanded to a larger metabolic network e.g. by including trehalose recycling, which accounted for about 1.5% of the glucose uptake rate; ii) the reversibility of glycolytic/gluconeogenesis, TCA cycle and pentose phosphate pathways reactions was estimated, revealing a significant gluconeogenic flux from the dihydroxyacetone phosphate/glyceraldehydes phosphate pool to glucose-6P. The origin of this finding could be carbon recycling from the methanol assimilatory pathway to the pentose phosphate pool. Additionally, high exchange fluxes of oxaloacetate with aspartate as well as malate indicated amino acid pool buffering and the activity of the malate/Asp shuttle; iii) the ratio of methanol oxidation vs utilization appeared to be lower (54 vs 79% assimilated methanol directly oxidized to CO₂).

Conclusions

In summary, the application of instationary ¹³C-based metabolic flux analysis to P. pastoris provides an experimental framework with improved capabilities to explore the regulation of the carbon and energy metabolism of this yeast, particularly for the case of methanol and multicarbon source metabolism.

Utilization of Saccharomyces cerevisiae recombinant strain incapable of both ethanol and glycerol biosynthesis for anaerobic bioproduction

The yeast Saccharomyces cerevisiae produces ethanol and glycerol as major unwanted byproducts, unless ethanol and glycerol are the target compounds. Minimizing the levels of these byproducts is important for bioproduction processes using yeast cells. In this study, we constructed a yeast strain in which both ethanol and glycerol production pathways were disrupted and examined its culture characteristics. In wild-type yeast strain, metabolic pathways that produce ethanol and glycerol play an important role in reoxidizing nicotinamide adenine dinucleotide (NADH) generated during glycolysis, particularly under anaerobic conditions. Strains in which both pathways were disrupted therefore failed to grow and consume glucose under anaerobic conditions. Introduction of desired metabolic reaction(s) coupled with NADH oxidation enabled the engineered strain to consume substrate and produce target compound(s). Here we introduced NADH-oxidization-coupled L-lactate production mechanisms into a yeast strain incapable of ethanol and glycerol biosynthesis, based on in silico simulation using a genome-scale metabolic model of S. cerevisiae. From the results of in silico simulation based on flux balance analysis, a feasible anaerobic non-growing metabolic state, in which L-lactate yield approached the theoretical maximum, was identified and this phenomenon was verified experimentally. The yeast strain incapable of both ethanol and glycerol biosynthesis is a potentially valuable host for bioproduction coupled with NADH oxidation under anaerobic conditions.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Toward pectin fermentation by Saccharomyces cerevisiae: expression of the first two steps of a bacterial pathway for D-galacturonate metabolism

Saccharomyces cerevisiae cannot metabolize D-galacturonate, an important monomer of pectin. Use of S. cerevisiae for production of ethanol or other compounds of interest from pectin-rich feedstocks therefore requires introduction of a heterologous pathway for D-galacturonate metabolism. Bacterial D-galacturonate pathways involve D-galacturonate isomerase, D-tagaturonate reductase and three additional enzymes. This study focuses on functional expression of bacterial D-galacturonate isomerases in S. cerevisiae. After demonstrating high-level functional expression of a D-tagaturonate reductase gene (uxaB from Lactococcus lactis), the resulting yeast strain was used to screen for functional expression of six codon-optimized bacterial D-galacturonate isomerase (uxaC) genes. The L. lactis uxaC gene stood out, yielding a tenfold higher enzyme activity than the other uxaC genes. Efficient expression of D-galacturonate isomerase and D-tagaturonate reductase represents an important step toward metabolic engineering of S. cerevisiae for bioethanol production from D-galacturonate. To investigate in vivo activity of the first steps of the D-galacturonate pathway, the L. lactis uxaB and uxaC genes were expressed in a gpd1Δ gpd2Δ S. cerevisiae strain. Although D-tagaturonate reductase could, in principle, provide an alternative means for re-oxidizing cytosolic NADH, addition of D-galacturonate did not restore anaerobic growth, possibly due to absence of a functional D-altronate exporter in S. cerevisiae.

What mRNA Abundances Can Tell us about Metabolism

Inferring decreased or increased metabolic functions from transcript profiles is at first sight a bold and speculative attempt because of the functional layers in between: proteins, enzymatic activities, and reaction fluxes. However, the growing interest in this field can easily be explained by two facts: the high quality of genome-scale metabolic network reconstructions and the highly developed technology to obtain genome-covering RNA profiles. Here, an overview of important algorithmic approaches is given by means of criteria by which published procedures can be classified. The frontiers of the methods are sketched and critical voices are being heard. Finally, an outlook for the prospects of the field is given.

Novel strategies to improve co-fermentation of pentoses with D-glucose by recombinant yeast strains in lignocellulosic hydrolysates

Economically feasible production of second-generation biofuels requires efficient co-fermentation of pentose and hexose sugars in lignocellulosic hydrolysates under very harsh conditions. Baker’s yeast is an excellent, traditionally used ethanol producer but is naturally not able to utilize pentoses. This is due to the lack of pentose-specific transporter proteins and enzymatic reactions. Thus, natural yeast strains must be modified by genetic engineering. Although the construction of various recombinant yeast strains able to ferment pentose sugars has been described during the last two decades, their rates of pentose utilization is still significantly lower than D-glucose fermentation. Moreover, pentoses are only fermented after D-glucose is exhausted, resulting in an uneconomical increase in the fermentation time. In this addendum, we discuss novel approaches to improve utilization of pentoses by development of specific transporters and substrate channeling in enzyme cascades.

Harnessing recombination to speed adaptive evolution in Escherichia coli

Evolutionary engineering typically involves asexual propagation of a strain to improve a desired phenotype. However, asexual populations suffer from extensive clonal interference, a phenomenon where distinct lineages of beneficial clones compete and are often lost from the population given sufficient time. Improved adaptive mutants can likely be generated by genetic exchange between lineages, thereby reducing clonal interference. We present a system that allows continuous in situ recombination by using an Esherichia coli F-based conjugation system lacking surface exclusion. Evolution experiments revealed that Hfr-mediated recombination significantly speeds adaptation in certain circumstances. These results show that our system is stable, effective, and suitable for use in evolutionary engineering applications.

Dynamic metabolomics differentiates between carbon and energy starvation in recombinant Saccharomyces cerevisiae fermenting xylose

BACKGROUND

The concerted effects of changes in gene expression due to changes in the environment are ultimately reflected in the metabolome. Dynamics of metabolite concentrations under a certain condition can therefore give a description of the cellular state with a high degree of functional information. We used this potential to evaluate the metabolic status of two recombinant strains of Saccharomyces cerevisiae during anaerobic batch fermentation of a glucose/xylose mixture. Two isogenic strains were studied, differing only in the pathways used for xylose assimilation: the oxidoreductive pathway with xylose reductase (XR) and xylitol dehydrogenase (XDH) or the isomerization pathway with xylose isomerase (XI). The isogenic relationship between the two strains ascertains that the observed responses are a result of the particular xylose pathway and not due to unknown changes in regulatory systems. An increased understanding of the physiological state of these strains is important for further development of efficient pentose-utilizing strains for bioethanol production.

RESULTS

Using LC-MS/MS we determined the dynamics in the concentrations of intracellular metabolites in central carbon metabolism, nine amino acids, the purine nucleotides and redox cofactors. The general response to the transition from glucose to xylose was increased concentrations of amino acids and TCA-cycle intermediates, and decreased concentrations of sugar phosphates and redox cofactors. The two strains investigated had significantly different uptake rates of xylose which led to an enhanced response in the XI-strain. Despite the difference in xylose uptake rate, the adenylate energy charge remained high and stable around 0.8 in both strains. In contrast to the adenylate pool, large changes were observed in the guanylate pool.

CONCLUSIONS

The low uptake of xylose by the XI-strain led to several distinguished responses: depletion of key metabolites in glycolysis and NADPH, a reduced GTP/GDP ratio and accumulation of PEP and aromatic amino acids. These changes are strong indicators of carbon starvation. The XR/XDH-strain displayed few such traits. The coexistence of these traits and a stable adenylate charge indicates that xylose supplies energy to the cells but does not suppress a response similar to carbon starvation. Particular signals may play a role in the latter, of which the GTP/GMP ratio could be a candidate as it decreased significantly in both strains.

Galacturonic acid inhibits the growth of Saccharomyces cerevisiae on galactose, xylose, and arabinose

The efficient fermentation of mixed substrates is essential for the microbial conversion of second-generation feedstocks, including pectin-rich waste streams such as citrus peel and sugar beet pulp. Galacturonic acid is a major constituent of hydrolysates of these pectin-rich materials. The yeast Saccharomyces cerevisiae, the main producer of bioethanol, cannot use this sugar acid. The impact of galacturonic acid on alcoholic fermentation by S. cerevisiae was investigated with anaerobic batch cultures grown on mixtures of glucose and galactose at various galacturonic acid concentrations and on a mixture of glucose, xylose, and arabinose. In cultures grown at pH 5.0, which is well above the pK(a) value of galacturonic acid (3.51), the addition of 10 g · liter(-1) galacturonic acid did not affect galactose fermentation kinetics and growth. In cultures grown at pH 3.5, the addition of 10 g · liter(-1) galacturonic acid did not significantly affect glucose consumption. However, at this lower pH, galacturonic acid completely inhibited growth on galactose and reduced galactose consumption rates by 87%. Additionally, it was shown that galacturonic acid strongly inhibits the fermentation of xylose and arabinose by the engineered pentose-fermenting S. cerevisiae strain IMS0010. The data indicate that inhibition occurs when nondissociated galacturonic acid is present extracellularly and corroborate the hypothesis that a combination of a decreased substrate uptake rate due to competitive inhibition on Gal2p, an increased energy requirement to maintain cellular homeostasis, and/or an accumulation of galacturonic acid 1-phosphate contributes to the inhibition. The role of galacturonic acid as an inhibitor of sugar fermentation should be considered in the design of yeast fermentation processes based on pectin-rich feedstocks.

Characterization of non-oxidative transaldolase and transketolase enzymes in the pentose phosphate pathway with regard to xylose utilization by recombinant Saccharomyces cerevisiae

The activity of transaldolase and transketolase, key enzymes in the non-oxidative pentose phosphate pathway, is rate-limiting for xylose utilization in recombinant Saccharomyces cerevisiae. Overexpression of TAL1 and TKL1, the major transaldolase and transketolase genes, increases the flux from the pentose phosphate pathway into the glycolytic pathway. However, the functional roles of NQM1 and TKL2, the secondary transaldolase and transketolase genes, especially in xylose utilization, remain unclear. This study focused on characterization of NQM1 and TKL2, together with TAL1 and TKL1, regarding their roles in xylose utilization and fermentation. Knockout or overexpression of these four genes on the phenotype of xylose-utilizing S. cerevisiae strains was also examined. Transcriptional analysis indicated that the expression of TAL1, NQM1, and TKL1 was up-regulated in the presence of xylose. A significant decrease in both growth on xylose and xylose-fermenting ability in tal1Δ and tkl1Δ mutants confirmed that TAL1 and TKL1 are essential for xylose assimilation and fermentation. Gene disruption analysis using a tkl1Δ mutant revealed that TKL1 is also required for utilization of glucose. Growth on xylose and xylose-fermenting ability were slightly influenced by deletion of NQM1 or TKL2 when xylose was used as the sole carbon source. Moreover, the rate of xylose consumption and ethanol production was slightly impaired in TKL1- and TKL2-overexpressing strains. NQM1 and TKL2 may thus play a physiological role via an effect on the non-oxidative pentose phosphate pathway in the xylose metabolic pathway, although their roles in xylose utilization and fermentation are less important than those of TAL1 and TKL1.

Laboratory evolution of new lactate transporter genes in a jen1Δ mutant of Saccharomyces cerevisiae and their identification as ADY2 alleles by whole-genome resequencing and transcriptome analysis

Laboratory evolution is a powerful approach in applied and fundamental yeast research, but complete elucidation of the molecular basis of evolved phenotypes remains a challenge. In this study, DNA microarray-based transcriptome analysis and whole-genome resequencing were used to investigate evolution of novel lactate transporters in Saccharomyces cerevisiae that can replace Jen1p, the only documented S. cerevisiae lactate transporter. To this end, a jen1Δ mutant was evolved for growth on lactate in serial batch cultures. Two independent evolution experiments yielded growth on lactate as sole carbon source (0.14 and 0.18 h(-1) , respectively). Transcriptome analysis did not provide leads, but whole-genome resequencing showed different single-nucleotide changes (C755G/Leu219Val and C655G/Ala252Gly) in the acetate transporter gene ADY2. Introduction of these ADY2 alleles in a jen1Δ ady2Δ strain enabled growth on lactate (0.14 h(-1) for Ady2p(Leu219Val) and 0.12 h(-1) for Ady2p(Ala252Gly) ), demonstrating that these alleles of ADY2 encode efficient lactate transporters. Depth of coverage of DNA sequencing, combined with karyotyping, gene deletions and diagnostic PCR, showed that an isochromosome III (c. 475 kb) with two additional copies of ADY2(C755G) had been formed via crossover between retrotransposons YCLWΔ15 and YCRCΔ6. The isochromosome formation shows how even short periods of selective pressure can cause substantial karyotype changes.