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

Synthetic Engineering of Microbes for Production of Terpenoid Food Ingredients

Terpenoids are a class of chemicals comprising many food ingredient chemicals. Synthetic biology and metabolic engineering have been performed to produce microbial cell factories for their production. For improved production of various terpenoid ingredients, heterologous synthetic pathways can be optimized at multiple dimensions. Optimizing chassis precursor supply and overcoming the host's inherent metabolic rigidity are crucial for enhancing overall efficiency of heterologous terpenoid production. Integrating synthetic regulatory circuits can facilitate the staged programming and precise optimization of heterologous and endogenous metabolism. Engineering long-term genetic and metabolic stability is essential for the successful scale-up of commercial production. Maximizing efficiency in food terpenoid production will rely on interdisciplinary synthetic and engineering biology tools to advance state-of-the-art capabilities for the streamlined design and construction of complex genotypes in microbial chassis.

Physiology and Robustness of Yeasts Exposed to Dynamic pH and Glucose Environments

Gradients negatively affect performance in large-scale bioreactors; however, they are difficult to predict at laboratory scale. Dynamic microfluidics single-cell cultivation (dMSCC) has emerged as an important tool for investigating cell behavior in rapidly changing environments. In the present study, dMSCC, biosensors of intracellular parameters, and robustness quantification were employed to investigate the physiological response of three Saccharomyces cerevisiae strains to substrate and pH changes every 0.75-48 min. All strains showed higher sensitivity to substrate than pH oscillations. Strain-specific intracellular responses included higher relative glycolytic flux and oxidative stress response for strains PE2 and CEN.PK113-7D, respectively. Instead, the Ethanol Red strain displayed the least heterogeneous populations and the highest robustness for multiple functions when exposed to substrate oscillations. This result could arise from a positive trade-off between ATP levels and ATP stability over time. The present study demonstrates the importance of coupling physiological responses to dynamic environments with simultaneous characterization of strains, conditions, individual regimes, and robustness analysis. All these tools are a suitable add-on to traditional evaluation and screening workflows at both laboratory and industrial scale, and can help bridge the gap between these two.

Robustness quantification of a mutant library screen revealed key genetic markers in yeast

BACKGROUND

Microbial robustness is crucial for developing cell factories that maintain consistent performance in a challenging environment such as large-scale bioreactors. Although tools exist to assess and understand robustness at a phenotypic level, the underlying metabolic and genetic mechanisms are not well defined, which limits our ability to engineer more strains with robust functions.

RESULTS

This study encompassed four steps. (I) Fitness and robustness were analyzed from a published dataset of yeast mutants grown in multiple environments. (II) Genes and metabolic processes affecting robustness or fitness were identified, and 14 of these genes were deleted in Saccharomyces cerevisiae CEN.PK113-7D. (III) The mutants bearing gene deletions were cultivated in three perturbation spaces mimicking typical industrial processes. (IV) Fitness and robustness were determined for each mutant in each perturbation space. We report that robustness varied according to the perturbation space. We identified genes associated with increased robustness such as MET28, linked to sulfur metabolism; as well as genes associated with decreased robustness, including TIR3 and WWM1, both involved in stress response and apoptosis.

CONCLUSION

The present study demonstrates how phenomics datasets can be analyzed to reveal the relationship between phenotypic response and associated genes. Specifically, robustness analysis makes it possible to study the influence of single genes and metabolic processes on stable microbial performance in different perturbation spaces. Ultimately, this information can be used to enhance robustness in targeted strains.

Engineering Saccharomyces cerevisiae for targeted hydrolysis and fermentation of glucuronoxylan through CRISPR/Cas9 genome editing

BACKGROUND

The abundance of glucuronoxylan (GX) in agricultural and forestry residual side streams positions it as a promising feedstock for microbial conversion into valuable compounds. By engineering strains of the widely employed cell factory Saccharomyces cerevisiae with the ability to directly hydrolyze and ferment GX polymers, we can avoid the need for harsh chemical pretreatments and costly enzymatic hydrolysis steps prior to fermentation. However, for an economically viable bioproduction process, the engineered strains must efficiently express and secrete enzymes that act in synergy to hydrolyze the targeted polymers.

RESULTS

The aim of this study was to equip the xylose-fermenting S. cerevisiae strain CEN.PK XXX with xylanolytic enzymes targeting beechwood GX. Using a targeted enzyme approach, we matched hydrolytic enzyme activities to the chemical features of the GX substrate and determined that besides endo-1,4-β-xylanase and β-xylosidase activities, α-methyl-glucuronidase activity was of great importance for GX hydrolysis and yeast growth. We also created a library of strains expressing different combinations of enzymes, and screened for yeast strains that could express and secrete the enzymes and metabolize the GX hydrolysis products efficiently. While strains engineered with BmXyn11A xylanase and XylA β-xylosidase could grow relatively well in beechwood GX, strains further engineered with Agu115 α-methyl-glucuronidase did not display an additional growth benefit, likely due to inefficient expression and secretion of this enzyme. Co-cultures of strains expressing complementary enzymes as well as external enzyme supplementation boosted yeast growth and ethanol fermentation of GX, and ethanol titers reached a maximum of 1.33 g L- 1 after 48 h under oxygen limited condition in bioreactor fermentations.

CONCLUSION

This work underscored the importance of identifying an optimal enzyme combination for successful engineering of S. cerevisiae strains that can hydrolyze and assimilate GX. The enzymes must exhibit high and balanced activities, be compatible with the yeast's expression and secretion system, and the nature of the hydrolysis products must be such that they can be taken up and metabolized by the yeast. The engineered strains, particularly when co-cultivated, display robust growth and fermentation of GX, and represent a significant step forward towards a sustainable and cost-effective bioprocessing of GX-rich biomass. They also provide valuable insights for future strain and process development targets.

POMBOX: A Fission Yeast Cloning Toolkit for Molecular and Synthetic Biology

The fission yeast Schizosaccharomyces pombe is a popular model organism in molecular biology and cell physiology. With its ease of genetic manipulation and growth, supported by in-depth functional annotations in the PomBase database and genome-wide metabolic models,S. pombe is an attractive option for synthetic biology applications. However,S. pombe currently lacks modular tools for generating genetic circuits with more than 1 transcriptional unit. We developed a toolkit to address this gap. Adapted from the MoClo-YTK plasmid kit for Saccharomyces cerevisiae and using the same modular cloning grammar, our POMBOX toolkit is designed to facilitate fast, efficient, and modular construction of genetic circuits inS. pombe. It allows for interoperability when working with DNA sequences that are functional in bothS. cerevisiae and S. pombe (e.g., protein tags, antibiotic resistance cassettes, and coding sequences). Moreover, POMBOX enables the modular assembly of multigene pathways and increases the possible pathway length from 6 to 12 transcriptional units. We also adapted the stable integration vector homology arms to Golden Gate assembly and tested the genomic integration success rates depending on different sequence sizes, from 4 to 24 kb. We included 14 S. pombe promoters that we characterized using two fluorescent proteins, in both minimally defined (EMM2─Edinburgh minimal media) and complex (YES─yeast extract with supplements) media. Then, we examined the efficacy of 6 S. cerevisiae and 6 synthetic terminators in S. pombe. Finally, we used the POMBOX kit for a synthetic biology application in metabolic engineering and expressed plant enzymes in S. pombe to produce specialized metabolite precursors, namely, methylxanthine, amorpha-4,11-diene, and cinnamic acid from the purine, mevalonate, and aromatic amino acid pathways.

Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation

BACKGROUND

Microorganisms must respond to changes in their environment. Analysing the robustness of functions (i.e. performance stability) to such dynamic perturbations is of great interest in both laboratory and industrial settings. Recently, a quantification method capable of assessing the robustness of various functions, such as specific growth rate or product yield, across different conditions, time frames, and populations has been developed for microorganisms grown in a 96-well plate. In micro-titer-plates, environmental change is slow and undefined. Dynamic microfluidic single-cell cultivation (dMSCC) enables the precise maintenance and manipulation of microenvironments, while tracking single cells over time using live-cell imaging. Here, we combined dMSCC and a robustness quantification method to a pipeline for assessing performance stability to changes occurring within seconds or minutes.

RESULTS

Saccharomyces cerevisiae CEN.PK113-7D, harbouring a biosensor for intracellular ATP levels, was exposed to glucose feast-starvation cycles, with each condition lasting from 1.5 to 48 min over a 20 h period. A semi-automated image and data analysis pipeline was developed and applied to assess the performance and robustness of various functions at population, subpopulation, and single-cell resolution. We observed a decrease in specific growth rate but an increase in intracellular ATP levels with longer oscillation intervals. Cells subjected to 48 min oscillations exhibited the highest average ATP content, but the lowest stability over time and the highest heterogeneity within the population.

CONCLUSION

The proposed pipeline enabled the investigation of function stability in dynamic environments, both over time and within populations. The strategy allows for parallelisation and automation, and is easily adaptable to new organisms, biosensors, cultivation conditions, and oscillation frequencies. Insights on the microbial response to changing environments will guide strain development and bioprocess optimisation.

Lighting up Pyruvate Metabolism in Saccharomyces cerevisiae by a Genetically Encoded Fluorescent Biosensor

Monitoring intracellular pyruvate is useful for the exploration of fundamental metabolism and for guiding the construction of yeast cell factories for chemical production. Here, we employed a genetically encoded fluorescent Pyronic biosensor to light up the pyruvate metabolic state in the cytoplasm, nucleus, and mitochondria of Saccharomyces cerevisiae BY4741. A strong correlation was observed between the pyruvate fluctuation in mitochondria and cytoplasm when exposed to different metabolites. Further metabolic analysis of pyruvate uptake and glycolytic dynamics showed that glucose and fructose dose-dependently activated cytoplasmic pyruvate levels more effectively than direct exposure to pyruvate. Meanwhile, the Pyronic biosensor could visually distinguish phenotypes of the wild-type S. cerevisiae BY4741 and the pyruvate-hyperproducing S. cerevisiae TAM at a single-cell resolution, having the potential for high-throughput screening. Overall, Pyronic biosensors targeting different suborganelles contribute to mapping and studying the central carbon metabolism in-depth and guide the design and construction of yeast cell factories.

A transcriptomic atlas of acute stress response to low pH in multiple Issatchenkia orientalis strains

IMPORTANCE

Issatchenkia orientalis is a promising industrial chassis to produce biofuels and bioproducts due to its high tolerance to multiple environmental stresses such as low pH, heat, and other chemicals otherwise toxic for the most widely used microbes. Yet, little is known about specific mechanisms of such tolerance in this organism, hindering our ability to engineer this species to produce valuable biochemicals. Here, we report a comprehensive study of the mechanisms of acidic tolerance in this species via transcriptome profiling across variable pH for 12 different strains with different phenotypes. We found multiple regulatory mechanisms involved in tolerance to low pH in different strains of I. orientalis, marking potential targets for future gene editing and perturbation experiments.

Automated yeast cultivation control using a biosensor and flow cytometry

Effective microbial bioprocessing relies on maintaining ideal cultivation conditions, highlighting the necessity for tools that monitor and regulate cellular performance and robustness. This study evaluates a fed-batch cultivation control system based on at-line flow cytometry monitoring of intact yeast cells having a fluorescent transcription factor-based redox biosensor. Specifically, the biosensor assesses the response of an industrial xylose-fermenting Saccharomyces cerevisiae strain carrying the TRX2p-yEGFP biosensor for NADPH/NADP+ ratio imbalance when exposed to furfural. The developed control system successfully detected biosensor output and automatically adjusted furfural feed rate, ensuring physiological fitness at high furfural levels. Moreover, the single-cell measurements enabled the monitoring of subpopulation dynamics, enhancing control precision over traditional methods. The presented automated control system highlights the potential of combining biosensors and flow cytometry for robust microbial cultivations by leveraging intracellular properties as control inputs.

ONE-SENTENCE SUMMARY

An automated control system using flow cytometry and biosensors enhances microbial bioprocessing by regulating cellular performance in response to the environmental stressor furfural.

Performance and robustness analysis reveals phenotypic trade-offs in yeast

To design strains that can function efficiently in complex industrial settings, it is crucial to consider their robustness, that is, the stability of their performance when faced with perturbations. In the present study, we cultivated 24 Saccharomyces cerevisiae strains under conditions that simulated perturbations encountered during lignocellulosic bioethanol production, and assessed the performance and robustness of multiple phenotypes simultaneously. The observed negative correlations confirmed a trade-off between performance and robustness of ethanol yield, biomass yield, and cell dry weight. Conversely, the specific growth rate performance positively correlated with the robustness, presumably because of evolutionary selection for robust, fast-growing cells. The Ethanol Red strain exhibited both high performance and robustness, making it a good candidate for bioproduction in the tested perturbation space. Our results experimentally map the robustness-performance trade-offs, previously demonstrated mainly by single-phenotype and computational studies.

ScEnSor Kit for Saccharomyces cerevisiae Engineering and Biosensor-Driven Investigation of the Intracellular Environment

In this study, the three-step build-transform-assess toolbox for real-time monitoring of the yeast intracellular environment has been expanded and upgraded to the two-module ScEnSor (S. cerevisiae Engineering + Biosensor) Kit. The Biosensor Module includes eight fluorescent reporters for the intracellular environment; three of them (unfolded protein response, pyruvate metabolism, and ethanol consumption) were newly implemented to complement the original five. The Genome-Integration Module comprises a set of backbone plasmids for the assembly of 1-6 transcriptional units (each consisting of promoter, coding sequence, and terminator) for efficient marker-free single-locus genome integration (in HO and/or X2 loci). Altogether, the ScEnSor Kit enables rapid and easy construction of strains with new transcriptional units as well as high-throughput investigation of the yeast intracellular environment.

Physiology of Saccharomyces cerevisiae during growth on industrial sugar cane molasses can be reproduced in a tailor-made defined synthetic medium

Fully defined laboratory media have the advantage of allowing for reproducibility and comparability of results among different laboratories, as well as being suitable for the investigation of how different individual components affect microbial or process performance. We developed a fully defined medium that mimics sugarcane molasses, a frequently used medium in different industrial processes where yeast is cultivated. The medium, named 2SMol, builds upon a previously published semi-defined formulation and is conveniently prepared from some stock solutions: C-source, organic N, inorganic N, organic acids, trace elements, vitamins, Mg + K, and Ca. We validated the 2SMol recipe in a scaled-down sugarcane biorefinery model, comparing the physiology of Saccharomyces cerevisiae in different actual molasses-based media. We demonstrate the flexibility of the medium by investigating the effect of nitrogen availability on the ethanol yield during fermentation. Here we present in detail the development of a fully defined synthetic molasses medium and the physiology of yeast strains in this medium compared to industrial molasses. This tailor-made medium was able to satisfactorily reproduce the physiology of S. cerevisiae in industrial molasses. Thus, we hope the 2SMol formulation will be valuable to researchers both in academia and industry to obtain new insights and developments in industrial yeast biotechnology.

Imaging of mtHyPer7, a Ratiometric Biosensor for Mitochondrial Peroxide, in Living Yeast Cells

Mitochondrial dysfunction, or functional alteration, is found in many diseases and conditions, including neurodegenerative and musculoskeletal disorders, cancer, and normal aging. Here, an approach is described to assess mitochondrial function in living yeast cells at cellular and subcellular resolutions using a genetically encoded, minimally invasive, ratiometric biosensor. The biosensor, mitochondria-targeted HyPer7 (mtHyPer7), detects hydrogen peroxide (H2O2) in mitochondria. It consists of a mitochondrial signal sequence fused to a circularly permuted fluorescent protein and the H2O2-responsive domain of a bacterial OxyR protein. The biosensor is generated and integrated into the yeast genome using a CRISPR-Cas9 marker-free system, for more consistent expression compared to plasmid-borne constructs. mtHyPer7 is quantitatively targeted to mitochondria, has no detectable effect on yeast growth rate or mitochondrial morphology, and provides a quantitative readout for mitochondrial H2O2 under normal growth conditions and upon exposure to oxidative stress. This protocol explains how to optimize imaging conditions using a spinning-disk confocal microscope system and perform quantitative analysis using freely available software. These tools make it possible to collect rich spatiotemporal information on mitochondria both within cells and among cells in a population. Moreover, the workflow described here can be used to validate other biosensors.

Assessment of the TRX2p-yEGFP Biosensor to Monitor the Redox Response of an Industrial Xylose-Fermenting Saccharomyces cerevisiae Strain during Propagation and Fermentation

The commercial production of bioethanol from lignocellulosic biomass such as wheat straw requires utilizing a microorganism that can withstand all the stressors encountered in the process while fermenting all the sugars in the biomass. Therefore, it is essential to develop tools for monitoring and controlling the cellular fitness during both cell propagation and sugar fermentation to ethanol. In the present study, on-line flow cytometry was adopted to assess the response of the biosensor TRX2p-yEGFP for redox imbalance in an industrial xylose-fermenting strain of Saccharomyces cerevisiae during cell propagation and the following fermentation of wheat-straw hydrolysate. Rapid and transient induction of the sensor was recorded upon exposure to furfural and wheat straw hydrolysate containing up to 3.8 g/L furfural. During the fermentation step, the induction rate of the sensor was also found to correlate to the initial ethanol production rate, highlighting the relevance of redox monitoring and the potential of the presented tool to assess the ethanol production rate in hydrolysates. Three different propagation strategies were also compared, and it was confirmed that pre-exposure to hydrolysate during propagation remains the most efficient method for high ethanol productivity in the following wheat-straw hydrolysate fermentations.

Real-Time Assessment of Intracellular Metabolites in Single Cells through RNA-Based Sensors

Quantification of the concentration of particular cellular metabolites reports on the actual utilization of metabolic pathways in physiological and pathological conditions. Metabolite concentration also constitutes the readout for screening cell factories in metabolic engineering. However, there are no direct approaches that allow for real-time assessment of the levels of intracellular metabolites in single cells. In recent years, the modular architecture of natural bacterial RNA riboswitches has inspired the design of genetically encoded synthetic RNA devices that convert the intracellular concentration of a metabolite into a quantitative fluorescent signal. These so-called RNA-based sensors are composed of a metabolite-binding RNA aptamer as the sensor domain, connected through an actuator segment to a signal-generating reporter domain. However, at present, the variety of available RNA-based sensors for intracellular metabolites is still very limited. Here, we go through natural mechanisms for metabolite sensing and regulation in cells across all kingdoms, focusing on those mediated by riboswitches. We review the design principles underlying currently developed RNA-based sensors and discuss the challenges that hindered the development of novel sensors and recent strategies to address them. We finish by introducing the current and potential applicability of synthetic RNA-based sensors for intracellular metabolites.

Confocal imaging of biomarkers at a single-cell resolution: quantifying 'living' in 3D-printable engineered living material based on Pluronic F-127 and yeast Saccharomyces cerevisiae

BACKGROUND

Engineered living materials (ELMs) combine living cells with non-living scaffolds to obtain life-like characteristics, such as biosensing, growth, and self-repair. Some ELMs can be 3D-printed and are called bioinks, and their scaffolds are mostly hydrogel-based. One such scaffold is polymer Pluronic F127, a liquid at 4 °C but a biocompatible hydrogel at room temperature. In such thermally-reversible hydrogel, the microorganism-hydrogel interactions remain uncharacterized, making truly durable 3D-bioprinted ELMs elusive.

METHODS

We demonstrate the methodology to assess cell-scaffold interactions by characterizing intact alive yeast cells in cross-linked F127-based hydrogels, using genetically encoded ratiometric biosensors to measure intracellular ATP and cytosolic pH at a single-cell level through confocal imaging.

RESULTS

When embedded in hydrogel, cells were ATP-rich, in exponential or stationary phase, and assembled into microcolonies, which sometimes merged into larger superstructures. The hydrogels supported (micro)aerobic conditions and induced a nutrient gradient that limited microcolony size. External compounds could diffuse at least 2.7 mm into the hydrogels, although for optimal yeast growth bioprinted structures should be thinner than 0.6 mm. Moreover, the hydrogels could carry whole-cell copper biosensors, shielding them from contaminations and providing them with nutrients.

CONCLUSIONS

F127-based hydrogels are promising scaffolds for 3D-bioprinted ELMs, supporting a heterogeneous cell population primarily shaped by nutrient availability.

Identification of acetic acid sensitive strains through biosensor-based screening of a Saccharomyces cerevisiae CRISPRi library

Background

Acetic acid tolerance is crucial for the development of robust cell factories for conversion of lignocellulosic hydrolysates that typically contain high levels of acetic acid. Screening mutants for growth in medium with acetic acid is an attractive way to identify sensitive variants and can provide novel insights into the complex mechanisms regulating the acetic acid stress response.

Results

An acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1, was used to screen a CRISPRi yeast strain library where dCas9-Mxi was set to individually repress each essential or respiratory growth essential gene. Fluorescence-activated cell sorting led to the enrichment of a population of cells with higher acetic acid retention. These cells with higher biosensor signal were demonstrated to be more sensitive to acetic acid. Biosensor-based screening of the CRISPRi library strains enabled identification of strains with increased acetic acid sensitivity: strains with gRNAs targeting TIF34, MSN5, PAP1, COX10 or TRA1.

Conclusions

This study demonstrated that biosensors are valuable tools for screening and monitoring acetic acid tolerance in yeast. Fine-tuning the expression of essential genes can lead to altered acetic acid tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01938-7.

Assessment of fluorescent protein candidates for multi-color flow cytometry analysis of Saccharomyces cerevisiae

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In vivo fluorescence of candidate fluorescent proteins was assessed in Saccharomyces cerevisiae.

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eEGFP, CyOFP1opt and mBeRFPopt were found to be suitable for multicolour flow cytometry.

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Successful protein selection and equipment configuration allowed potential tri-color flow cytometry with 488 nm single-laser excitation.

Transcription factor-based biosensors represent promising tools in the construction and evaluation of efficient cell factories for the sustainable production of fuels, chemicals and pharmaceuticals. They can notably be designed to follow the production of a target compound or to monitor key cellular properties, such as stress or starvation. In most cases, the biosensors are built with fluorescent protein (FP) genes as reporter genes because of the direct correlation between promoter activity and fluorescence level that can be measured using, for instance, flow cytometry or fluorometry. The expansion of available FPs offers the possibility of using several FPs - and biosensors – in parallel in one host, with simultaneous detection using multicolor flow cytometry. However, the technique is currently limited by the unavailability of combinations of FP whose genes can be successfully expressed in the host and whose fluorescence can be efficiently distinguished from each other.

In the present study, the broad collection of available FPs was explored and four different FPs were successfully expressed in the yeast Saccharomyces cerevisiae: yEGFP, mEGFP, CyOFP1opt and mBeRFPopt. After studying their fluorescence signals, population heterogeneity and possible interactions, we recommend two original combinations of FPs for bi-color flow cytometry: mEGFP together with either CyOFP1opt or mBeRFPopt, as well as the combination of all three FPs mEGFP, CyOFP1opt and mBeRFPopt for tri-color flow cytometry. These combinations will allow to perform different types of bi-color or possibly tri-color flow cytometry and FACS experiments with yeast, such as phenotype evaluation, screening or sorting, by single-laser excitation with a standard 488 nm blue laser.

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.