The future of self-selecting and stable fermentations

Unfavorable cell heterogeneity is a frequent risk during bioprocess scale-up and characterized by rising frequencies of low-producing cells. Low-producing cells emerge by both non-genetic and genetic variation and will enrich due to their higher specific growth rate during the extended number of cell divisions of large-scale bioproduction. Here, we discuss recent strategies for synthetic stabilization of fermentation populations and argue for their application to make cell factory designs that better suit industrial needs. Genotype-directed strategies leverage DNA-sequencing data to inform strain design. Self-selecting phenotype-directed strategies couple high production with cell proliferation, either by redirected metabolic pathways or synthetic product biosensing to enrich for high-performing cell variants. Evaluating production stability early in new cell factory projects will guide heterogeneity-reducing design choices. As good initial metrics, we propose production half-life from standardized serial-passage stability screens and production load, quantified as production-associated percent-wise growth rate reduction. Incorporating more stable genetic designs will greatly increase scalability of future cell factories through sustaining a high-production phenotype and enabling stable long-term production

Quantification of Microbial Robustness in Yeast

Stable cell performance in a fluctuating environment is essential for sustainable bioproduction and synthetic cell functionality; however, microbial robustness is rarely quantified. Here, we describe a high-throughput strategy for quantifying robustness of multiple cellular functions and strains in a perturbation space. We evaluated quantification theory on experimental data and concluded that the mean-normalized Fano factor allowed accurate, reliable, and standardized quantification. Our methodology applied to perturbations related to lignocellulosic bioethanol production showed that the industrial bioethanol producing strain Saccharomyces cerevisiae Ethanol Red exhibited both higher and more robust growth rates than the laboratory strain CEN.PK and industrial strain PE-2, while a more robust product yield traded off for lower mean levels. The methodology validated that robustness is function-specific and characterized by positive and negative function-specific trade-offs. Systematic quantification of robustness to end-use perturbations will be important to analyze and construct robust strains with more predictable functions

Real-Time Monitoring of the Yeast Intracellular State During Bioprocesses With a Toolbox of Biosensors

Industrial fermentation processes strive for high robustness to ensure optimal and consistent performance. Medium components, fermentation products, and physical perturbations may cause stress and lower performance. Cellular stress elicits a range of responses, whose extracellular manifestations have been extensively studied; whereas intracellular aspects remain poorly known due to lack of tools for real-time monitoring. Genetically encoded biosensors have emerged as promising tools and have been used to improve microbial productivity and tolerance toward industrially relevant stresses. Here, fluorescent biosensors able to sense the yeast intracellular environment (pH, ATP levels, oxidative stress, glycolytic flux, and ribosome production) were implemented into a versatile and easy-to-use toolbox. Marker-free and efficient genome integration at a conserved site on chromosome X of Saccharomyces cerevisiae strains and a commercial Saccharomyces boulardii strain was developed. Moreover, multiple biosensors were used to simultaneously monitor different intracellular parameters in a single cell. Even when combined together, the biosensors did not significantly affect key physiological parameters, such as specific growth rate and product yields. Activation and response of each biosensor and their interconnection were assessed using an advanced micro-cultivation system. Finally, the toolbox was used to screen cell behavior in a synthetic lignocellulosic hydrolysate that mimicked harsh industrial substrates, revealing differences in the oxidative stress response between laboratory (CEN.PK113-7D) and industrial (Ethanol Red) S. cerevisiae strains. In summary, the toolbox will allow both the exploration of yeast diversity and physiological responses in natural and complex industrial conditions, as well as the possibility to monitor production processes

Exploring Microbial Robustness for a Sustainable and Efficient Bioproduction

Efficient microbial cell factories that produce valuable compounds are gaining increasing interest as one path towards a more sustainable economy. Therefore, there is an increasing need for robust microorganisms which can optimally perform even in harsh and challenging industrial conditions. The identification of robustness traits is crucial to improve the already-existing strains and develop new, better ones. Here, different approaches to study microbial robustness are presented. First, single-cell analysis in a cell population might give some insights on the development of more robust sub-populations. Physiological parameters (such as intracellular pH, fluxes, redox balance, etc.) and morphologic features were monitored with fluorescent biosensors and tagged proteins to study the single-cell status. Moreover, a barcoding technique will be used to discover and underline patterns in the development of population dynamics during the different industrial processes. Furthermore, an objective method to quantify robustness was developed for selection of useful strains and a large dataset was analysed to find predictive parameters for robustness. All together, these tools will give the possibility to identify robustness traits and understand robustness leading to improved industrial strains and processes

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness – the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses

Microbial robustness 101: tools and applications

Striving for a fossil-free society, bio-production is gaining increasing interest over time. Bioproduction applies microorganisms (bacteria, yeast, fungi) to produce valuable chemicals from different raw materials (plant biomass, waste materials, etc.) and offers sustainable use of side-streams and/or waste streams. Bioproduction suffers from challenges such as poor microbial performance and reproducibility. One key feature in this field is microbial robustness, i.e., the stability of a phenotype (cellular function) when a system is challenged by different perturbations. Microbial robustness, due to its abstract nature, has been poorly studied also due to the lack of tools available. Moreover, being able to include robustness evaluation in the early stages of bioprocess and strain design would facilitate their scaling up from the laboratory- to the industrial scales.Here two tools to explore microbial robustness with some applications and case studies in Saccharomyces cerevisiae are presented. First, a way to quantify the robustness of cellular functions was developed. The robustness coefficient proposed allows comparison between strains and cellular functions in a given perturbation space. This method, based on the Fano factor, is dimensionless, free from arbitrary control conditions and frequency-independent. Second, fluorescent biosensors sensing the intracellular environment were developed into a versatile and easy-to-use toolbox. Such toolbox was used in population studies to identify different physiological responses in different strains exposed to industrially-relevant media and conditions. In the future, it will be implemented in single-cell analysis in microfluidic devices and for studying the formation of subpopulations in large-scale fermentations. All together, these tools will give the possibility to identify robustness traits and mechanisms, allowing for physiological insights that are a foundation for improving industrial strains and process designs

RNA sequencing reveals metabolic and regulatory changes leading to more robust fermentation performance during short-term adaptation of Saccharomyces cerevisiae to lignocellulosic inhibitors

Background: The limited tolerance of Saccharomyces cerevisiae to inhibitors is a major challenge in second-generation bioethanol production, and our understanding of the molecular mechanisms providing tolerance to inhibitor-rich lignocellulosic hydrolysates is incomplete. Short-term adaptation of the yeast in the presence of dilute hydrolysate can improve its robustness and productivity during subsequent fermentation. Results: We utilized RNA sequencing to investigate differential gene expression in the industrial yeast strain CR01 during short-term adaptation, mimicking industrial conditions for cell propagation. In this first transcriptomic study of short-term adaption of S. cerevisiae to lignocellulosic hydrolysate, we found that cultures respond by fine-tuned up- and down-regulation of a subset of general stress response genes. Furthermore, time-resolved RNA sequencing allowed for identification of genes that were differentially expressed at 2 or more sampling points, revealing the importance of oxidative stress response, thiamin and biotin biosynthesis. furan-aldehyde reductases and specific drug:H+ antiporters, as well as the down-regulation of certain transporter genes. Conclusions: These findings provide a better understanding of the molecular mechanisms governing short-term adaptation of S. cerevisiae to lignocellulosic hydrolysate, and suggest new genetic targets for improving fermentation robustness

Synthetic addiction extends the productive life time of engineered Escherichia coli populations

Significance Bioproduction of chemicals offers a sustainable alternative to petrochemical synthesis routes by using genetically engineered microorganisms to convert waste and simple substrates into higher-value products. However, efficient high-yield production commonly introduces a metabolic burden that selects for subpopulations of nonproducing cells in large fermentations. To postpone such detrimental evolution, we have synthetically addicted production cells to production by carefully linking signals of product presence to expression of nonconditionally essential genes. We addict Escherichia coli cells to their engineered biosynthesis of mevalonic acid by fine-tuned control of essential genes using a product-responsive transcription factor. Over the course of a long-term fermentation equivalent to industrial 200-m 3 bioreactors such addicted cells remained productive, unlike the control, in which evolution fully terminated production. </jats:p

Reconstruction of the biosynthetic pathway for the core fungal polyketide scaffold rubrofusarin in Saccharomyces cerevisiae

BACKGROUND: Fungal polyketides include commercially important pharmaceuticals and food additives, e.g. the cholesterol-lowering statins and the red and orange monascus pigments. Presently, production relies on isolation of the compounds from the natural producers, and systems for heterologous production in easily fermentable and genetically engineerable organisms, such as Saccharomyces cerevisiae and Escherichia coli are desirable. Rubrofusarin is an orange polyketide pigment that is a common intermediate in many different fungal biosynthetic pathways. RESULTS: In this study, we established a biosynthetic pathway for rubrofusarin in S. cerevisiae. First, the Fusarium graminearum gene encoding polyketide synthase 12 (PKS12) was heterologously co-expressed with the Aspergillus fumigatus gene encoding phosphopantetheinyl transferase (npgA) resulting in production of YWA1. This aromatic heptaketide intermediate was converted into nor-rubrofusarin upon expression of the dehydratase gene aurZ from the aurofusarin gene cluster of F. graminearum. Final conversion into rubrofusarin was achieved by expression of the O-methyltransferase encoding gene aurJ, also obtained from the aurofusarin gene cluster, resulting in a titer of 1.1 mg/L. Reduced levels of rubrofusarin were detected when expressing PKS12, npgA, and aurJ alone, presumably due to spontaneous conversion of YWA1 to nor-rubrofusarin. However, the co-expression of aurZ resulted in an approx. six-fold increase in rubrofusarin production. CONCLUSIONS: The reconstructed pathway for rubrofusarin in S. cerevisiae allows the production of a core scaffold molecule with a branch-point role in several fungal polyketide pathways, thus paving the way for production of further natural pigments and bioactive molecules. Furthermore, the reconstruction verifies the suggested pathway, and as such, it is the first example of utilizing a synthetic biological “bottom up” approach for the validation of a complex fungal polyketide pathway