Robustness: linking strain design to viable bioprocesses

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

Large-scale bioprocesses are increasing globally to cater to the larger market demands for biological products. As fermenter volumes increase, the efficiency of mixing decreases, and environmental gradients become more pronounced compared to smaller scales. Consequently, the cells experience gradients in process parameters, which in turn affects the efficiency and profitability of the process. Computational fluid dynamics (CFD) simulations are being widely embraced for their ability to simulate bioprocess performance, facilitate bioprocess upscaling, downsizing, and process optimisation. Recently, CFD approaches have been integrated with dynamic Cell reaction kinetic (CRK) modelling to generate valuable information about the cellular response to fluctuating hydrodynamic parameters inside large production processes. Such coupled approaches have the potential to facilitate informed decision-making in intelligent biomanufacturing, aligning with the principles of "Industry 4.0" concerning digitalisation and automation. In this review, we discuss the benefits of utilising integrated CFD-CRK models and the different approaches to integrating CFD-based bioreactor hydrodynamic models with cellular kinetic models. We also highlight the suitability of different coupling approaches for bioprocess modelling in the purview of associated computational loads.

Genomic and metabolic instability during long-term fermentation of an industrial Saccharomyces cerevisiae strain engineered for C5 sugar utilization

The genetic stability and metabolic robustness of production strains is one of the key criteria for the production of bio-based products by microbial fermentation on an industrial scale. These criteria were here explored in an industrial ethanol-producer strain of Saccharomyces cerevisiae able to co-ferment D-xylose and L-arabinose with glucose through the chromosomal integration of several copies of pivotal genes for the use of these pentose (C5) sugars. Using batch sequential cultures in a controlled bioreactor that mimics long-term fermentation in an industrial setting, this strain was found to exhibit significant fluctuations in D-xylose and L-arabinose consumption as early as the 50th generation and beyond. These fluctuations seem not related to the few low-consumption C5 sugar clones that appeared throughout the sequential batch cultures at a frequency lower than 1.5% and that were due to the reduction in the number of copies of transgenes coding for C5 sugar assimilation enzymes. Also, subpopulations enriched with low or high RAD52 expression, whose expression level was reported to be proportional to homologous recombination rate did not exhibit defect in C5-sugar assimilation, arguing that other mechanisms may be responsible for copy number variation of transgenes. Overall, this work highlighted the existence of genetic and metabolic instabilities in an industrial yeast which, although modest in our conditions, could be more deleterious in harsher industrial conditions, leading to reduced production performance.

Shared and more specific genetic determinants and pathways underlying yeast tolerance to acetic, butyric, and octanoic acids

BACKGROUND

The improvement of yeast tolerance to acetic, butyric, and octanoic acids is an important step for the implementation of economically and technologically sustainable bioprocesses for the bioconversion of renewable biomass resources and wastes. To guide genome engineering of promising yeast cell factories toward highly robust superior strains, it is instrumental to identify molecular targets and understand the mechanisms underlying tolerance to those monocarboxylic fatty acids. A chemogenomic analysis was performed, complemented with physiological studies, to unveil genetic tolerance determinants in the model yeast and cell factory Saccharomyces cerevisiae exposed to equivalent moderate inhibitory concentrations of acetic, butyric, or octanoic acids.

RESULTS

Results indicate the existence of multiple shared genetic determinants and pathways underlying tolerance to these short- and medium-chain fatty acids, such as vacuolar acidification, intracellular trafficking, autophagy, and protein synthesis. The number of tolerance genes identified increased with the linear chain length and the datasets for butyric and octanoic acids include the highest number of genes in common suggesting the existence of more similar toxicity and tolerance mechanisms. Results of this analysis, at the systems level, point to a more marked deleterious effect of an equivalent inhibitory concentration of the more lipophilic octanoic acid, followed by butyric acid, on the cell envelope and on cellular membranes function and lipid remodeling. The importance of mitochondrial genome maintenance and functional mitochondria to obtain ATP for energy-dependent detoxification processes also emerged from this chemogenomic analysis, especially for octanoic acid.

CONCLUSIONS

This study provides new biological knowledge of interest to gain further mechanistic insights into toxicity and tolerance to linear-chain monocarboxylic acids of increasing liposolubility and reports the first lists of tolerance genes, at the genome scale, for butyric and octanoic acids. These genes and biological functions are potential targets for synthetic biology approaches applied to promising yeast cell factories, toward more robust superior strains, a highly desirable phenotype to increase the economic viability of bioprocesses based on mixtures of volatiles/medium-chain fatty acids derived from low-cost biodegradable substrates or lignocellulose hydrolysates.

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.

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.

Four ways of implementing robustness quantification in strain characterisation

BACKGROUND

In industrial bioprocesses, microorganisms are generally selected based on performance, whereas robustness, i.e., the ability of a system to maintain a stable performance, has been overlooked due to the challenges in its quantification and implementation into routine experimental procedures. This work presents four ways of implementing robustness quantification during strain characterisation. One Saccharomyces cerevisiae laboratory strain (CEN.PK113-7D) and two industrial strains (Ethanol Red and PE2) grown in seven different lignocellulosic hydrolysates were assessed for growth-related functions (specific growth rate, product yields, etc.) and eight intracellular parameters (using fluorescent biosensors).

RESULTS

Using flasks and high-throughput experimental setups, robustness was quantified in relation to: (i) stability of growth functions in response to the seven hydrolysates; (ii) stability of growth functions across different strains to establish the impact of perturbations on yeast metabolism; (iii) stability of intracellular parameters over time; (iv) stability of intracellular parameters within a cell population to indirectly quantify population heterogeneity. Ethanol Red was the best-performing strain under all tested conditions, achieving the highest growth function robustness. PE2 displayed the highest population heterogeneity. Moreover, the intracellular environment varied in response to non-woody or woody lignocellulosic hydrolysates, manifesting increased oxidative stress and unfolded protein response, respectively.

CONCLUSIONS

Robustness quantification is a powerful tool for strain characterisation as it offers novel information on physiological and biochemical parameters. Owing to the flexibility of the robustness quantification method, its implementation was successfully validated at single-cell as well as high-throughput levels, showcasing its versatility and potential for several applications.

Random mutagenesis as a tool for industrial strain improvement for enhanced production of antibiotics: a review

Secondary metabolites are produced by microbes in minimal quantities in the natural environment out of necessity. However, in the pharmaceutical industry, their overproduction becomes essential. To achieve higher yields, genetic modifications are employed to create strains that surpass the productivity of the initially isolated strains. While rational screening and genetic engineering have emerged as valuable practices in recent years, the cost-effective technique of mutagenesis and selection, known as "random screening," remains a preferred method for efficient short-term strain development. This review aims to comprehensively explore all aspects of strain improvement, focusing on why random mutagenesis continues to be widely adopted.

Monitoring Phenotype Heterogeneity at the Single-Cell Level within Bacillus Populations Producing Poly-3-hydroxybutyrate by Label-Free Super-resolution Infrared Imaging

Phenotypic heterogeneity is commonly found among bacterial cells within microbial populations due to intrinsic factors as well as equipping the organisms to respond to external perturbations. The emergence of phenotypic heterogeneity in bacterial populations, particularly in the context of using these bacteria as microbial cell factories, is a major concern for industrial bioprocessing applications. This is due to the potential impact on overall productivity by allowing the growth of subpopulations consisting of inefficient producer cells. Monitoring the spread of phenotypes across bacterial cells within the same population at the single-cell level is key to the development of robust, high-yield bioprocesses. Here, we discuss the novel development of optical photothermal infrared (O-PTIR) spectroscopy to probe phenotypic heterogeneity within Bacillus strains by monitoring the production of the bioplastic poly-3-hydroxybutyrate (PHB) at the single-cell level. Measurements obtained on single-point and in imaging mode show significant variability in the PHB content within bacterial cells, ranging from whether or not a cell produces PHB to variations in the intragranular biochemistry of PHB within bacterial cells. Our results show the ability of O-PTIR spectroscopy to probe PHB production at the single-cell level in a rapid, label-free, and semiquantitative manner. These findings highlight the potential of O-PTIR spectroscopy in single-cell microbial metabolomics as a whole-organism fingerprinting tool that can be used to monitor the dynamic of bacterial populations as well as for understanding their mechanisms for dealing with environmental stress, which is crucial for metabolic engineering research.

Creating Polyploid Escherichia Coli and Its Application in Efficient L-Threonine Production

Prokaryotic genomes are generally organized in haploid. In synthetic biological research, efficient chassis cells must be constructed to produce bio-based products. Here, the essential division of the ftsZ gene to create functional polyploid E. coli is regulated. The artificial polyploid E. coli containing 2-4 chromosomes is confirmed through PCR amplification, terminator localization, and flow cytometry. The polyploid E. coli exhibits a larger cell size, and its low pH tolerance and acetate resistance are stronger than those of haploid E. coli. Transcriptome analysis shows that the genes of the cell's main functional pathways are significantly upregulated in the polyploid E. coli. These advantages of the polyploid E. coli results in the highest reported L-threonine yield (160.3 g L-1 ) in fed-batch fermentation to date. In summary, an easy and convenient method for constructing polyploid E. coli and demonstrated its application in L-threonine production is developed. This work provides a new approach for creating an excellent host strain for biochemical production and studying the evolution of prokaryotes and their chromosome functions.

Engineering of the DNA replication and repair machinery to develop binary mutators for rapid genome evolution of Corynebacterium glutamicum

Corynebacterium glutamicum is an important industrial workhorse for production of amino acids and chemicals. Although recently developed genome editing technologies have advanced the rational genetic engineering of C. glutamicum, continuous genome evolution based on genetic mutators is still unavailable. To address this issue, the DNA replication and repair machinery of C. glutamicum was targeted in this study. DnaQ, the homolog of ϵ subunit of DNA polymerase III responsible for proofreading in Escherichia coli, was proven irrelevant to DNA replication fidelity in C. glutamicum. However, the histidinol phosphatase (PHP) domain of DnaE1, the α subunit of DNA polymerase III, was characterized as the key proofreading element and certain variants with PHP mutations allowed elevated spontaneous mutagenesis. Repression of the NucS-mediated post-replicative mismatch repair pathway or overexpression of newly screened NucS variants also impaired the DNA replication fidelity. Simultaneous interference with the DNA replication and repair machinery generated a binary genetic mutator capable of increasing the mutation rate by up to 2352-fold. The mutators facilitated rapid evolutionary engineering of C. glutamicum to acquire stress tolerance and protein overproduction phenotypes. This study provides efficient tools for evolutionary engineering of C. glutamicum and could inspire the development of mutagenesis strategy for other microbial hosts.

Analyzing and understanding the robustness of bioprocesses

The robustness of bioprocesses is becoming increasingly important. The main driving forces of this development are, in particular, increasing demands on product purities as well as economic aspects. In general, bioprocesses exhibit extremely high complexity and variability. Biological systems often have a much higher intrinsic variability compared with chemical processes, which makes the development and characterization of robust processes tedious task. To predict and control robustness, a clear understanding of interactions between input and output variables is necessary. Robust bioprocesses can be realized, for example, by using advanced control strategies for the different unit operations. In this review, we discuss the different biological, technical, and mathematical tools for the analysis and control of bioprocess robustness.

Influence of Varying Pre-Culture Conditions on the Level of Population Heterogeneity in Batch Cultures with an Escherichia coli Triple Reporter Strain

When targeting robust, high-yielding bioprocesses, phenomena such as population heterogeneity have to be considered. Therefore, the influence of the conditions which the cells experience prior to the main culture should also be evaluated. Here, the influence of a pre-culture medium (complex vs. minimal medium), optical density for inoculation of the main culture (0.005, 0.02 and 0.0125) and harvest time points of the pre-culture in exponential growth phase (early, mid and late) on the level of population heterogeneity in batch cultures of the Escherichia coli triple reporter strain G7_BL21(DE3) in stirred-tank bioreactors was studied. This strain allows monitoring the growth (rrnB-EmGFP), general stress response (rpoS-mStrawberry) and oxygen limitation (nar-TagRFP657) of single cells through the expression of fluorescent proteins. Data from batch cultivations with varying pre-culture conditions were analysed with principal component analysis. According to fluorescence data, the pre-culture medium had the largest impact on population heterogeneities during the bioprocess. While a minimal medium as a pre-culture medium elevated the differences in cellular growth behaviour in the subsequent batch process, a complex medium increased the general stress response and led to a higher population heterogeneity. The latter was promoted by an early harvest of the cells with low inoculation density. Seemingly, nar-operon expression acted independently of the pre-culture conditions.

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones' relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system's application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.

Bioeconomy and net-zero carbon: lessons from Trends in Biotechnology, volume 1, issue 1

Many biotechnology applications tend to be for low production volumes and relatively high-value products such as insulin and vaccines. More difficult to perfect at scale are bioprocesses for high-volume products with lower value, especially if the target product is a reduced chemical such as a solvent or a plastic. Historically, industrial microbiology succeeded under special circumstances when fossil feedstocks were either unavailable or expensive. Inevitably, as these circumstances relaxed, bioprocesses struggled to compete with petrochemistry. Why try to compete? Fossil resources will be phased out in the coming decades in the struggle with climate change. To reach net-zero carbon by 2050 will require all sectors to transition, not only energy and transportation. This may herald a new opportunity for industrial bioprocesses with much better tools.

Production of indigo by recombinant bacteria

Indigo is an economically important dye, especially for the textile industry and the dyeing of denim fabrics for jeans and garments. Around 80,000 tonnes of indigo are chemically produced each year with the use of non-renewable petrochemicals and the use and generation of toxic compounds. As many microorganisms and their enzymes are able to synthesise indigo after the expression of specific oxygenases and hydroxylases, microbial fermentation could offer a more sustainable and environmentally friendly manufacturing platform. Although multiple small-scale studies have been performed, several existing research gaps still hinder the effective translation of these biochemical approaches. No article has evaluated the feasibility and relevance of the current understanding and development of indigo biocatalysis for real-life industrial applications. There is no record of either established or practically tested large-scale bioprocess for the biosynthesis of indigo. To address this, upstream and downstream processing considerations were carried out for indigo biosynthesis. 5 classes of potential biocatalysts were identified, and 2 possible bioprocess flowsheets were designed that facilitate generating either a pre-reduced dye solution or a dry powder product. Furthermore, considering the publicly available data on the development of relevant technology and common bioprocess facilities, possible platform and process values were estimated, including titre, DSP yield, potential plant capacities, fermenter size and batch schedule. This allowed us to project the realistic annual output of a potential indigo biosynthesis platform as 540 tonnes. This was interpreted as an industrially relevant quantity, sufficient to provide an annual dye supply to a single industrial-size denim dyeing plant. The conducted sensitivity analysis showed that this anticipated output is most sensitive to changes in the reaction titer, which can bring a 27.8% increase or a 94.4% drop. Thus, although such a biological platform would require careful consideration, fine-tuning and optimization before real-life implementation, the recombinant indigo biosynthesis was found as already attractive for business exploitation for both, luxury segment customers and mass-producers of denim garments.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40643-023-00626-7.

Exploring Yeast Diversity to Produce Lipid-Based Biofuels from Agro-Forestry and Industrial Organic Residues

Exploration of yeast diversity for the sustainable production of biofuels, in particular biodiesel, is gaining momentum in recent years. However, sustainable, and economically viable bioprocesses require yeast strains exhibiting: (i) high tolerance to multiple bioprocess-related stresses, including the various chemical inhibitors present in hydrolysates from lignocellulosic biomass and residues; (ii) the ability to efficiently consume all the major carbon sources present; (iii) the capacity to produce lipids with adequate composition in high yields. More than 160 non-conventional (non-Saccharomyces) yeast species are described as oleaginous, but only a smaller group are relatively well characterised, including Lipomyces starkeyi, Yarrowia lipolytica, Rhodotorula toruloides, Rhodotorula glutinis, Cutaneotrichosporonoleaginosus and Cutaneotrichosporon cutaneum. This article provides an overview of lipid production by oleaginous yeasts focusing on yeast diversity, metabolism, and other microbiological issues related to the toxicity and tolerance to multiple challenging stresses limiting bioprocess performance. This is essential knowledge to better understand and guide the rational improvement of yeast performance either by genetic manipulation or by exploring yeast physiology and optimal process conditions. Examples gathered from the literature showing the potential of different oleaginous yeasts/process conditions to produce oils for biodiesel from agro-forestry and industrial organic residues are provided.

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.