Experimental methods and modeling techniques for description of cell population heterogeneity

Spontaneous Attenuation of Alcoholic Fermentation via the Dysfunction of Cyc8p in Saccharomyces cerevisiae

A cell population characterized by the release of glucose repression and known as [GAR+] emerges spontaneously in the yeast Saccharomyces cerevisiae. This study revealed that the [GAR+] variants exhibit retarded alcoholic fermentation when glucose is the sole carbon source. To identify the key to the altered glucose response, the gene expression profile of [GAR+] cells was examined. Based on RNA-seq data, the [GAR+] status was linked to impaired function of the Cyc8p-Tup1p complex. Loss of Cyc8p led to a decrease in the initial rate of alcoholic fermentation under glucose-rich conditions via the inactivation of pyruvate decarboxylase, an enzyme unique to alcoholic fermentation. These results suggest that Cyc8p can become inactive to attenuate alcoholic fermentation. These findings may contribute to the elucidation of the mechanism of non-genetic heterogeneity in yeast alcoholic fermentation.

Evolutionary Epidemiology Consequences of Trait-Dependent Control of Heterogeneous Parasites

AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

Impact of mixing insufficiencies on L-phenylalanine production with an Escherichia coli reporter strain in a novel two-compartment bioreactor

BACKGROUND

The omnipresence of population heterogeneity in industrial bioprocesses originates from prevailing dynamic bioprocess conditions, which promote differences in the expression of cellular characteristics. Despite the awareness, the concrete consequences of this phenomenon remain poorly understood.

RESULTS

Therefore, for the first time, a L-phenylalanine overproducing Escherichia coli quadruple reporter strain was established for monitoring of general stress response, growth behavior, oxygen limitation and product formation of single cells based on mTagBFP2, mEmerald, CyOFP1, and mCardinal2 expression measured by flow cytometry. This strain was applied for the fed-batch production of L-phenylalanine from glycerol and ammonia in a stirred-tank bioreactor at homogeneous conditions compared to the same process in a novel two-compartment bioreactor. This two-compartment bioreactor consists of a stirred-tank bioreactor with an initial volume of 0.9 L (homogeneous zone) with a coiled flow inverter with a fixed working volume of 0.45 L as a bypass (limitation zone) operated at a mean hydraulic residence time of 102 s. The product formation was similar in both bioreactor setups with maximum L-phenylalanine concentrations of 21.1 ± 0.6 g L-1 demonstrating the consistency of this study's microbial L-phenylalanine production. However, cell growth was vulnerable to repetitive exposure to the dynamically changing conditions in the two-compartment bioreactor with maximum biomass yields reduced by 21%. The functionality of reporter molecules was approved in the stirred-tank bioreactor cultivation, in which expressed fluorescence levels of all four markers were in accordance with respective process state variables. Additional evaluation of the distributions on single-cell level revealed the presence of population heterogeneity in both bioprocesses. Especially for the marker of the general stress response and the product formation, the corresponding histograms were characterized by bimodal shapes and broad distributions. These phenomena were pronounced particularly at the beginning and the end of the fed-batch process.

CONCLUSIONS

The here shown findings confirm multiple reporter strains to be a noninvasive tool for monitoring cellular characteristics and identifying potential subpopulations in bioprocesses. In combination with experiments in scale-down setups, these can be utilized for a better physiological understanding of bioprocesses and support future scale-up procedures.

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.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Non-inhibitory levels of oxygen during cultivation increase freeze-drying stress tolerance in Limosilactobacillus reuteri DSM 17938

The physiological effects of oxygen on Limosilactobacillus reuteri DSM 17938 during cultivation and the ensuing properties of the freeze-dried probiotic product was investigated. On-line flow cytometry and k-means clustering gating was used to follow growth and viability in real time during cultivation. The bacterium tolerated aeration at 500 mL/min, with a growth rate of 0.74 ± 0.13 h^-1 which demonstrated that low levels of oxygen did not influence the growth kinetics of the bacterium. Modulation of the redox metabolism was, however, seen already at non-inhibitory oxygen levels by 1.5-fold higher production of acetate and 1.5-fold lower ethanol production. A significantly higher survival rate in the freeze-dried product was observed for cells cultivated in presence of oxygen compared to absence of oxygen (61.8% ± 2.4% vs. 11.5% ± 4.3%), coinciding with a higher degree of unsaturated fatty acids (UFA:SFA ratio of 10 for air sparged vs. 3.59 for N₂ sparged conditions.). Oxygen also resulted in improved bile tolerance and boosted 5'nucleotidase activity (370 U/L vs. 240 U/L in N₂ sparged conditions) but lower tolerance to acidic conditions compared bacteria grown under complete anaerobic conditions which survived up to 90 min of exposure at pH 2. Overall, our results indicate the controlled supply of oxygen during production may be used as means for probiotic activity optimization of L. reuteri DSM 17938.

Synthetic Biology Meets Machine Learning

This chapter outlines the myriad applications of machine learning (ML) in synthetic biology, specifically in engineering cell and protein activity, and metabolic pathways. Though by no means comprehensive, the chapter highlights several prominent computational tools applied in the field and their potential use cases. The examples detailed reinforce how ML algorithms can enhance synthetic biology research by providing data-driven insights into the behavior of living systems, even without detailed knowledge of their underlying mechanisms. By doing so, ML promises to increase the efficiency of research projects by modeling hypotheses in silico that can then be tested through experiments. While challenges related to training dataset generation and computational costs remain, ongoing improvements in ML tools are paving the way for smarter and more streamlined synthetic biology workflows that can be readily employed to address grand challenges across manufacturing, medicine, engineering, agriculture, and beyond.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Population balance modelling captures host cell protein dynamics in CHO cell cultures

Monoclonal antibodies (mAbs) have been extensively studied for their wide therapeutic and research applications. Increases in mAb titre has been achieved mainly by cell culture media/feed improvement and cell line engineering to increase cell density and specific mAb productivity. However, this improvement has shifted the bottleneck to downstream purification steps. The higher accumulation of the main cell-derived impurities, host cell proteins (HCPs), in the supernatant can negatively affect product integrity and immunogenicity in addition to increasing the cost of capture and polishing steps. Mathematical modelling of bioprocess dynamics is a valuable tool to improve industrial production at fast rate and low cost. Herein, a single stage volume-based population balance model (PBM) has been built to capture Chinese hamster ovary (CHO) cell behaviour in fed-batch bioreactors. Using cell volume as the internal variable, the model captures the dynamics of mAb and HCP accumulation extracellularly under physiological and mild hypothermic culture conditions. Model-based analysis and orthogonal measurements of lactate dehydrogenase activity and double-stranded DNA concentration in the supernatant show that a significant proportion of HCPs found in the extracellular matrix is secreted by viable cells. The PBM then served as a platform for generating operating strategies that optimise antibody titre and increase cost-efficiency while minimising impurity levels.

Implantation of Bacillus pseudomycoides Chromate Transporter Increases Chromate Tolerance in Bacillus subtilis

Chromium of anthropogenic origin contaminates the environment worldwide. The toxicity of chromium, a group I human carcinogen, is greatest when it is in a hexavalent oxidation state, Cr(VI). Cr(VI) is actively transported into the cell, triggering oxidative damage intracellularly. Due to the abundance of unspecific intracellular reductants, any microbial species is capable of bio-transformation of toxic Cr(VI) to innocuous Cr(III), however, this process is often lethal. Only some bacterial species are capable of sustaining the vegetative growth in the presence of a high concentration of Cr(VI) and thus operate as self-sustainable bioremediation agents. One of the successful microbial Cr(VI) detoxification strategies is the activation of chromate efflux pumps. This work describes transplantation of the chromate efflux pump from the potentially pathogenic but highly Cr resistant Bacillus pseudomycoides environmental strain into non-pathogenic but only transiently Cr tolerant Bacillus subtilis strain. In our study, we compared the two Bacillus spp. strains harboring evolutionarily diverged chromate efflux proteins. We have found that individual cells of the Cr-resistant B. pseudomycoides environmental strain accumulate less Cr than the cells of B. subtilis strain. Further, we found that survival of the B. subtilis strain during the Cr stress can be increased by the introduction of the chromate transporter from the Cr resistant environmental strain into its genome. Additionally, the expression of B. pseudomycoides chromate transporter ChrA in B. subtilis seems to be activated by the presence of chromate, hinting at versatility of Cr-efflux proteins. This study outlines the future direction for increasing the Cr-tolerance of non-pathogenic species and safe bioremediation using soil bacteria.

Ascorbic acid and all-trans retinoic acid promote proliferation of chicken blastoderm cells (cBCs) by mediating DNA demethylation

Chicken blastoderm cells (cBCs) obtained from stage X (EG&K) embryos are easily available materials for the study of cell development. However, cBCs are not widely used because they are hard to maintain in long-term culture in vitro. To solve this problem, ascorbic acid (AA; also known as vitamin C (VC)) and all-trans retinoic acid (ATRA) were added into basic culture medium to promote cell growth. Results suggested that cultured cBCs possessed strongly proliferative activity and maintained their pluripotency on the support of chicken embryonic fibroblast (CEF) feeder. Moreover, when VC or/and ATRA was added, the number and area of cBC colonies increased significantly compared with the control group. The expression of pluripotency genes (Sox2 and Nanog) and cell cycle-regulated genes (CCND1 and CDK6) was upregulated obviously. Furthermore, results showed that 5hmC levels in VC and RA groups increased significantly by DNA dot blot and immunofluorescence staining. These results provide strong evidence that VC and ATRA induced DNA demethylation and enhanced 5hmC level. The level of H3K27me3 was raised, while the level of H3K9me2 was reduced by addition of VC and ATRA. Finally, the expression of Tet1 and Dnmt3b was upregulated remarkably. Therefore, these results indicated that VC and ATRA enhanced DNA demethylation and then promoted cBC survival and proliferation in vitro.

Application of an Escherichia coli triple reporter strain for at-line monitoring of single-cell physiology during L-phenylalanine production

Biotechnological production processes are sustainable approaches for the production of biobased components such as amino acids for food and feed industry. Scale-up from ideal lab-scale bioreactors to large-scale processes is often accompanied by loss in productivity. This may be related to population heterogeneities of cells originating from isogenic cultures that arise due to dynamic non-ideal conditions in the bioreactor. To better understand this phenomenon, deeper insights into single-cell physiologies in bioprocesses are mandatory before scale-up. Here, a triple reporter strain (3RP) was developed by chromosomally integrating the fluorescent proteins mEmerald, CyOFP1, and mTagBFP2 into the L-phenylalanine producing Escherichia coli strain FUS4 (pF81_kan) to allow monitoring of growth, oxygen availability, and general stress response of the single cells. Functionality of the 3RP was confirmed in well-mixed lab-scale fed-batch processes with glycerol as carbon source in comparison to the strain without fluorescent proteins, leading to no difference in process performance. Fluorescence levels could successfully reflect the course of related process state variables, revealed population heterogeneities during the transition between different process phases and potentially subpopulations that exhibit superior process performance. Furthermore, indications were found for noise in gene expression as regulation strategy against environmental perturbation.

Dynamic response of Aspergillus niger to periodical glucose pulse stimuli in chemostat cultures

In industrial large-scale bioreactors, microorganisms encounter heterogeneous substrate concentration conditions, which can impact growth or product formation. Here we carried out an extended (12 h) experiment of repeated glucose pulsing with a 10-min period to simulate fluctuating glucose concentrations with Aspergillus niger producing glucoamylase, and investigated its dynamic response by rapid sampling and quantitative metabolomics. The 10-min period represents worst-case conditions, as in industrial bioreactors the average cycling duration is usually in the order of 1 min. We found that cell growth and the glucoamylase productivity were not significantly affected, despite striking metabolomic dynamics. Periodical dynamic responses were found across all central carbon metabolism pathways, with different time scales, and the frequently reported ATP paradox was confirmed for this A. niger strain under the dynamic conditions. A thermodynamics analysis revealed that several reactions of the central carbon metabolism remained in equilibrium even under periodical dynamic conditions. The dynamic response profiles of the intracellular metabolites did not change during the pulse exposure, showing no significant adaptation of the strain to the more than 60 perturbation cycles applied. The apparent high tolerance of the glucoamylase producing A. niger strain for extreme variations in the glucose availability presents valuable information for the design of robust industrial microbial hosts.

Challenges of influencing cellular morphology by morphology engineering techniques and mechanical induced stress on filamentous pellet systems-A critical review

Filamentous microorganisms are main producers of organic acids, enzymes, and pharmaceutical agents such as antibiotics and other active pharmaceutical ingredients. With their complex cell morphology, ranging from dispersed mycelia to dense pellets, the cultivation is challenging. In recent years, various techniques for tailor-made cell morphologies of filamentous microorganisms have been developed to increase product formation and have been summarised under the term morphology engineering. These techniques, namely microparticle-enhanced cultivation, macroparticle-enhanced cultivation, and alteration of the osmolality of the culture medium by addition of inorganic salts, the salt-enhanced cultivation, are presented and discussed in this review. These techniques have already proven to be useful and now await further proof-of-concept. Furthermore, the mechanical behaviour of individual pellets is of special interest for a general understanding of pellet mechanics and the productivity of biotechnological processes with filamentous microorganisms. Correlating them with substrate uptake and finally with productivity would be a breakthrough not to be underestimated for the comprehensive characterisation of filamentous systems. So far, this research field is under-represented. First results on filamentous pellet mechanics are discussed and important future aspects, which the filamentous expert community should deal with, will be presented and critically discussed.

Biomolecular phenotyping and heterogeneity assessment of mesenchymal stromal cells using label-free Raman spectroscopy

Easy, quantitative measures of biomolecular heterogeneity and high-stratified phenotyping are needed to identify and characterise complex disease processes at the single-cell level, as well as to predict cell fate. Here, we demonstrate how Raman spectroscopy can be used in the difficult-to-assess case of clonal, bone-derived mesenchymal stromal cells (MSCs) to identify MSC lines and group these according to biological function (e.g., differentiation capacity). Biomolecular stratification is achieved using high-precision measures obtained from representative statistical sampling that also enable quantified heterogeneity assessment. Application to primary MSCs and human dermal fibroblasts shows use of these measures as a label-free assay to classify cell sub-types within complex heterogeneous cell populations, thus demonstrating the potential for therapeutic translation, and broad application to the phenotypic characterisation of other cells.

Understanding gradients in industrial bioreactors

Gradients in industrial bioreactors have attracted substantial research attention since exposure to fluctuating environmental conditions has been shown to lead to changes in the metabolome, transcriptome as well as population heterogeneity in industrially relevant microorganisms. Such changes have also been found to impact key process parameters like the yield on substrate and the productivity. Hence, understanding gradients is important from both the academic and industrial perspectives. In this review the causes of gradients are outlined, along with their impact on microbial physiology. Quantifying the impact of gradients requires a detailed understanding of both fluid flow inside industrial equipment and microbial physiology. This review critically examines approaches used to investigate gradients including large-scale experimental work, computational methods and scale-down approaches. Avenues for future work have been highlighted, particularly the need for further coordinated development of both in silico and experimental tools which can be used to further the current understanding of gradients in industrial equipment.

A model-driven approach towards rational microbial bioprocess optimization

Due to sustainability concerns, bio-based production capitalizing on microbes as cell factories is in demand to synthesize valuable products. Nevertheless, the nonhomogenous variations of the extracellular environment in bioprocesses often challenge the biomass growth and the bioproduction yield. To enable a more rational bioprocess optimization, we have established a model-driven approach that systematically integrates experiments with modeling, executed from flask to bioreactor scale, and using ferulic acid to vanillin bioconversion as a case study. The impacts of mass transfer and aeration on the biomass growth and bioproduction performances were examined using minimal small-scale experiments. An integrated model coupling the cell factory kinetics with the three-dimensional computational hydrodynamics of bioreactor was developed to better capture the spatiotemporal distributions of bioproduction. Full-factorial predictions were then performed to identify the desired operating conditions. A bioconversion yield of 94% was achieved, which is one of the highest for recombinant Escherichia coli using ferulic acid as the precursor.

FTIR micro-spectroscopy using synchrotron-based and thermal source-based radiation for probing live bacteria

Fourier transform infrared (FTIR) spectroscopy has proven to be a non-invasive tool to analyse cells without the hurdle of employing exogenous dyes or probes. Nevertheless, the study of single live bacteria in their aqueous environment has long remained a big challenge, due to the strong infrared absorption of water and the small size of bacteria compared to the micron-range infrared wavelengths of the probing photons. To record infrared spectra of bacteria in an aqueous environment, at different spatial resolutions, two setups were developed. A custom-built attenuated total reflection inverted microscope was coupled to a synchrotron-based FTIR spectrometer, using a germanium hemisphere. With such a setup, a projected spot size of 1 × 1 μm² was achieved, which allowed spectral acquisition at the single-cell level in the 1800-1300 cm^-1 region. The second setup used a demountable liquid micro-chamber with a thermal source-powered FTIR microscope, in transmission geometry, for probing clusters of a few thousands of live cells in the mid-IR region (4000-975 cm^-1). Both setups were applied for studying two strains of a model lactic acid bacterium exhibiting different cryo-resistances. The two approaches allowed the discrimination of both strains and revealed population heterogeneity among bacteria at different spatial resolutions. The multivariate analysis of spectra indicated that the cryo-sensitive cells presented the highest cell heterogeneity and the highest content of proteins with the α-helix structure. Furthermore, the results from clusters of bacterial cells evidenced phosphate and peptidoglycan vibrational bands associated with the cell envelope, as potential markers of resistance to environmental conditions. Graphical Abstract.

Development and characterization of Escherichia coli triple reporter strains for investigation of population heterogeneity in bioprocesses

Background

Today there is an increasing demand for high yielding robust and cost efficient biotechnological production processes. Although cells in these processes originate from isogenic cultures, heterogeneity induced by intrinsic and extrinsic influences is omnipresent. To increase understanding of this mechanistically poorly understood phenomenon, advanced tools that provide insights into single cell physiology are needed.

Results

Two Escherichia coli triple reporter strains have been designed based on the industrially relevant production host E. coli BL21(DE3) and a modified version thereof, E. coli T7E2. The strains carry three different fluorescence proteins chromosomally integrated. Single cell growth is followed with EmeraldGFP (EmGFP)-expression together with the ribosomal promoter rrnB. General stress response of single cells is monitored by expression of sigma factor rpoS with mStrawberry, whereas expression of the nar-operon together with TagRFP657 gives information about oxygen limitation of single cells. First, the strains were characterized in batch operated stirred-tank bioreactors in comparison to wildtype E. coli BL21(DE3). Afterwards, applicability of the triple reporter strains for investigation of population heterogeneity in bioprocesses was demonstrated in continuous processes in stirred-tank bioreactors at different growth rates and in response to glucose and oxygen perturbation simulating gradients on industrial scale. Population and single cell level physiology was monitored evaluating general physiology and flow cytometry analysis of fluorescence distributions of the triple reporter strains. Although both triple reporter strains reflected physiological changes that were expected based on the expression characteristics of the marker proteins, the triple reporter strain based on E. coli T7E2 showed higher sensitivity in response to environmental changes. For both strains, noise in gene expression was observed during transition from phases of non-growth to growth. Apparently, under some process conditions, e.g. the stationary phase in batch cultures, the fluorescence response of EmGFP and mStrawberry is preserved, whereas TagRFP657 showed a distinct response.

Conclusions

Single cell growth, general stress response and oxygen limitation of single cells could be followed using the two triple reporter strains developed in this study. They represent valuable tools to study population heterogeneity in bioprocesses significantly increasing the level of information compared to the use of single reporter strains.

Influence of Phenotypic Dissociation in Bacillus subtilis Strain ET-1 on Iturin A Production

Iturin A is a very important cyclic lipopeptide produced by several B. subtilis strains and has large commercial and therapeutic application potentials but its production on industrial scale has not been realized yet. In the present study, we have observed that the strain ET-1 of Bacillus subtilis, a producer of Iturin A, can present at least three different colony morphologies, which we arbitrarily called Rough, Smooth, and Mucoid morphotypes (R-, S-, and M-form). Performing HPLC analysis, a significant difference between the amounts of Iturin A produced by the three morphotypes was found. The morphotype R-form showed the highest productivity with yields about 10 and 100 times higher than morphotypes S and M, respectively. The results show that the production of Iturin A by B. subtilis could be strongly influenced by the phenotypic heterogeneity of cells within the inoculum. Indeed, we have observed that, pasteurizing the inoculum before seeding in order to improve the homogeneity removing the phenotypes less able to synthesize the Iturin A, its yields in a bench-scale production could be significantly improved. This can represent an important control factor also at industrial scale to improve the Iturin A yields, the robustness, the replicability, and consequently the cost-effectiveness of fermentation processes.

Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in Escherichia coli and Saccharomyces cerevisiae Chemostats

Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.

Engineering E. coli for improved microaerobic pDNA production

Escherichia coli strains W3110 and BL21 were engineered for the production of plasmid DNA (pDNA) under aerobic and transitions to microaerobic conditions. The gene coding for recombinase A (recA) was deleted in both strains. In addition, the Vitreoscilla hemoglobin (VHb) gene (vgb) was chromosomally inserted and constitutively expressed in each E. coli recA mutant and wild type. The recA inactivation increased the supercoiled pDNA fraction (SCF) in both strains, while VHb expression improved the pDNA production in W3110, but not in BL21. Therefore, a codon-optimized version of vgb was inserted in strain BL21recA^-, which, together with W3110recA^-vgb⁺, was tested in cultures with shifts from aerobic to oxygen-limited regimes. VHb expression lowered the accumulation of fermentative by-products in both strains. VHb-expressing cells displayed higher oxidative activity as indicated by the Redox Sensor Green fluorescence, which was more intense in BL21 than in W3110. Furthermore, VHb expression did not change pDNA production in W3110, but decreased it in BL21. These results are useful for understanding the physiological effects of VHb expression in two industrially relevant E. coli strains, and for the selection of a host for pDNA production.

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities

Isogenic bacterial populations are known to exhibit phenotypic heterogeneity at the single-cell level. Because of difficulties in assessing the phenotypic heterogeneity of a single taxon in a mixed community, the importance of this deeper level of organization remains relatively unknown for natural communities. In this study, we have used membrane-based microcosms that allow the probing of the phenotypic heterogeneity of a single taxon while interacting with a synthetic or natural community. Individual taxa were studied under axenic conditions, as members of a coculture with physical separation, and as a mixed culture. Phenotypic heterogeneity was assessed through both flow cytometry and Raman spectroscopy. Using this setup, we investigated the effect of microbial interactions on the individual phenotypic heterogeneities of two interacting drinking water isolates. Through flow cytometry we have demonstrated that interactions between these bacteria lead to a reduction of their individual phenotypic diversities and that this adjustment is conditional on the bacterial taxon. Single-cell Raman spectroscopy confirmed a taxon-dependent phenotypic shift due to the interaction. In conclusion, our data suggest that bacterial interactions may be a general driver of phenotypic heterogeneity in mixed microbial populations.IMPORTANCE Laboratory studies have shown the impact of phenotypic heterogeneity on the survival and functionality of isogenic populations. Because phenotypic heterogeneity plays an important role in pathogenicity and virulence, antibiotic resistance, biotechnological applications, and ecosystem properties, it is crucial to understand its influencing factors. An unanswered question is whether bacteria in mixed communities influence the phenotypic heterogeneity of their community partners. We found that coculturing bacteria leads to a reduction in their individual phenotypic heterogeneities, which led us to the hypothesis that the individual phenotypic diversity of a taxon is dependent on the community composition.

The effect of acetate on population heterogeneity in different cellular characteristics of Escherichia coli in aerobic batch cultures

Acetate as the major by-product in industrial-scale bioprocesses with Escherichia coli is found to decrease process efficiency as well as to be toxic to cells, which has several effects like a significant induction of cellular stress responses. However, the underlying phenomena are poorly explored. Therefore, we studied time-resolved population heterogeneity of the E. coli growth reporter strain MG1655/pGS20PrrnBGFPAAV expressing destabilized green fluorescent protein during batch growth on acetate and glucose as sole carbon sources. Additionally, we applied five fluorescent stains targeting different cellular properties (viability as well as metabolic and respiratory activity). Quantitative analysis of flow cytometry data verified that bacterial populations in the bioreactor are more heterogeneous in growth as well as stronger metabolically challenged during growth on acetate as sole carbon source, compared to growth on glucose or acetate after diauxic shift. Interestingly, with acetate as sole carbon source, significant subpopulations were found with some cells that seem to be more robust than the rest of the population. In conclusion, following batch cultures population heterogeneity was evident in all measured parameters. Our approach enabled a deeper study of heterogeneity during growth on the favored substrate glucose as well as on the toxic by-product acetate. Using a combination of activity fluorescent dyes proved to be an accurate and fast alternative as well as a supplement to the use of a reporter strain. However, the choice of combination of stains should be well considered depending on which population traits to aim for.

Clostridium butyricum population balance model: Predicting dynamic metabolic flux distributions using an objective function related to extracellular glycerol content

BACKGROUND

Extensive experimentation has been conducted to increment 1,3-propanediol (PDO) production using Clostridium butyricum cultures in glycerol, but computational predictions are limited. Previously, we reconstructed the genome-scale metabolic (GSM) model iCbu641, the first such model of a PDO-producing Clostridium strain, which was validated at steady state using flux balance analysis (FBA). However, the prediction ability of FBA is limited for batch and fed-batch cultures, which are the most often employed industrial processes.

RESULTS

We used the iCbu641 GSM model to develop a dynamic flux balance analysis (DFBA) approach to predict the PDO production of the Colombian strain Clostridium sp IBUN 158B. First, we compared the predictions of the dynamic optimization approach (DOA), static optimization approach (SOA), and direct approach (DA). We found no differences between approaches, but the DOA simulation duration was nearly 5000 times that of the SOA and DA simulations. Experimental results at glycerol limitation and glycerol excess allowed for validating dynamic predictions of growth, glycerol consumption, and PDO formation. These results indicated a 4.4% error in PDO prediction and therefore validated the previously proposed objective functions. We performed two global sensitivity analyses, finding that the kinetic input parameters of glycerol uptake flux had the most significant effect on PDO predictions. The other input parameters evaluated during global sensitivity analysis were biomass composition (precursors and macromolecules), death constants, and the kinetic parameters of acetic acid secretion flux. These last input parameters, all obtained from other Clostridium butyricum cultures, were used to develop a population balance model (PBM). Finally, we simulated fed-batch cultures, predicting a final PDO production near to 66 g/L, almost three times the PDO predicted in the best batch culture.

CONCLUSIONS

We developed and validated a dynamic approach to predict PDO production using the iCbu641 GSM model and the previously proposed objective functions. This validated approach was used to propose a population model and then an increment in predictions of PDO production through fed-batch cultures. Therefore, this dynamic model could predict different scenarios, including its integration into downstream processes to predict technical-economic feasibilities and reducing the time and costs associated with experimentation.

Efficient simulation of intrinsic, extrinsic and external noise in biochemical systems

Motivation

Biological cells operate in a noisy regime influenced by intrinsic, extrinsic and external noise, which leads to large differences of individual cell states. Stochastic effects must be taken into account to characterize biochemical kinetics accurately. Since the exact solution of the chemical master equation, which governs the underlying stochastic process, cannot be derived for most biochemical systems, approximate methods are used to obtain a solution.

Results

In this study, a method to efficiently simulate the various sources of noise simultaneously is proposed and benchmarked on several examples. The method relies on the combination of the sigma point approach to describe extrinsic and external variability and the τ-leaping algorithm to account for the stochasticity due to probabilistic reactions. The comparison of our method to extensive Monte Carlo calculations demonstrates an immense computational advantage while losing an acceptable amount of accuracy. Additionally, the application to parameter optimization problems in stochastic biochemical reaction networks is shown, which is rarely applied due to its huge computational burden. To give further insight, a MATLAB script is provided including the proposed method applied to a simple toy example of gene expression.

Availability and implementation

MATLAB code is available at Bioinformatics online.

Supplementary information

Supplementary data are available at Bioinformatics online.

Analysis of population structures of the microalga Acutodesmus obliquus during lipid production using multi-dimensional single-cell analysis

Microalgae bear a great potential to produce lipids for biodiesel, feed, or even food applications. To understand the still not well-known single-cell dynamics during lipid production in microalgae, a novel single-cell analytical technology was applied to study a well-established model experiment. Multidimensional single-cell dynamics were investigated with a non-supervised image analysis technique that utilizes data from epi-fluorescence microscopy. Reliability of this technique was successfully proven via reference analysis. The technique developed was used to determine cell size, chlorophyll amount, neutral lipid amount, and deriving properties on a single-cellular level in cultures of the biotechnologically promising alga Acutodesmus obliquus. The results illustrated a high correlation between cell size and chlorophyll amount, but a very low and dynamic correlation between cell size, lipid amount, and lipid density. During growth conditions under nitrogen starvation, cells with low chlorophyll content tend to start the lipid production first and the cell suspension differentiated in two subpopulations with significantly different lipid contents. Such quantitative characterization of single-cell dynamics of lipid synthesizing algae was done for the first time and the potential of such simple technology is highly relevant to other biotechnological applications and to deeper investigate the process of microalgal lipid accumulation.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Using Raman spectroscopy and chemometrics to identify the growth phase of Lactobacillus casei Zhang during batch culture at the single-cell level

Background

As microbial cultures are comprised of heterogeneous cells that differ according to their size and intracellular concentrations of DNA, proteins, and other constituents, the detailed identification and discrimination of the growth phases of bacterial populations in batch culture is challenging. Cell analysis is indispensable for quality control and cell enrichment.

Methods

In this paper, we report the results of our investigation on the use of single-cell Raman spectrometry (SCRS) for real-time analysis and prediction of cells in different growth phases during batch culture of Lactobacillus (L.) casei Zhang. A targeted analysis of defined cell growth phases at the level of the single cell, including lag phase, log phase, and stationary phase, was facilitated by SCRS.

Results

Spectral shifts were identified in different states of cell growth that reflect biochemical changes specific to each cell growth phase. Raman peaks associated with DNA and RNA displayed a decrease in intensity over time, whereas protein-specific and lipid-specific Raman vibrations increased at different rates. Furthermore, a supervised classification model (Random Forest) was used to specify the lag phase, log phase, and stationary phase of cells based on SCRS, and a mean sensitivity of 90.7% and mean specificity of 90.8% were achieved. In addition, the correct cell type was predicted at an accuracy of approximately 91.2%.

Conclusions

To conclude, Raman spectroscopy allows label-free, continuous monitoring of cell growth, which may facilitate more accurate estimates of the growth states of lactic acid bacterial populations during fermented batch culture in industry.

Engineered Control of Genetic Variability Reveals Interplay among Quorum Sensing, Feedback Regulation, and Biochemical Noise

Stochastic fluctuations in gene expression trigger both beneficial and harmful consequences for cell behavior. Therefore, achieving a desired mean protein expression level while minimizing noise is of interest in many applications, including robust protein production systems in industrial biotechnology. Here, we consider a synthetic gene circuit combining intracellular negative feedback and cell-to-cell communication based on quorum sensing. Accounting for both intrinsic and extrinsic noise, stochastic simulations allow us to analyze the capability of the circuit to reduce noise strength as a function of its parameters. We obtain mean expression levels and noise strengths for all species under different scenarios, showing good agreement with system-wide available experimental data of protein abundance and noise in Escherichia coli. Our in silico experiments, validated by preliminary in vivo results, reveal significant noise attenuation in gene expression through the interplay between quorum sensing and negative feedback and highlight the differential role that they play in regard to intrinsic and extrinsic noise.

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

Increased lignocellulosic inhibitor tolerance of Saccharomyces cerevisiae cell populations in early stationary phase

BACKGROUND

Production of second-generation bioethanol and other bulk chemicals by yeast fermentation requires cells that tolerate inhibitory lignocellulosic compounds at low pH. Saccharomyces cerevisiae displays high plasticity with regard to inhibitor tolerance, and adaptation of cell populations to process conditions is essential for reaching efficient and robust fermentations.

RESULTS

In this study, we assessed responses of isogenic yeast cell populations in different physiological states to combinations of acetic acid, vanillin and furfural at low pH. We found that cells in early stationary phase (ESP) exhibited significantly increased tolerance compared to cells in logarithmic phase, and had a similar ability to initiate growth in the presence of inhibitors as pre-adapted cells. The ESP cultures consisted of subpopulations with different buoyant cell densities which were isolated with flotation and analysed separately. These so-called quiescent (Q) and non-quiescent (NQ) cells were found to possess similar abilities to initiate growth in the presence of lignocellulosic inhibitors at pH 3.7, and had similar viabilities under static conditions. Therefore, differentiation into Q-cells was not the cause for increased tolerance of ESP cultures. Flow cytometry analysis of cell viability, intracellular pH and reactive oxygen species levels revealed that tolerant cell populations had a characteristic response upon inhibitor perturbations. Growth in the presence of a combination of inhibitors at low pH correlated with pre-cultures having a high frequency of cells with low pH_i and low ROS levels. Furthermore, only a subpopulation of ESP cultures was able to tolerate lignocellulosic inhibitors at low pH, while pre-adapted cell populations displayed an almost uniform high tolerance to the adverse condition. This was in stark contrast to cell populations growing exponentially in non-inhibitory medium that were uniformly sensitive to the inhibitors at low pH.

CONCLUSIONS

ESP cultures of S. cerevisiae were found to have high tolerance to lignocellulosic inhibitors at low pH, and were able to initiate growth to the same degree as cells that were pre-adapted to inhibitors at a slightly acidic pH. Carbon starvation may thus be a potential strategy to prepare cell populations for adjacent stressful environments which may be beneficial from a process perspective for fermentation of non-detoxified lignocellulosic substrates at low pH. Furthermore, flow cytometry analysis of pH_i and ROS level distributions in ESP cultures revealed responses that were characteristic for populations with high tolerance to lignocellulosic inhibitors. Measurement of population distribution responses as described herein may be applied to predict the outcome of environmental perturbations and thus can function as feedback for process control of yeast fitness during lignocellulosic fermentation.

First principle-based models in plant suspension cell cultures: a review

In this work, the development and application of published models for describing the behavior of plant cell cultures is reviewed. The structure of each type of model is analyzed and the new tendencies for the modeling of biotechnological processes that can be applied in plant cell cultures are presented. This review is a tool for clarifying the main features that characterize each type of model in the field of plant cell cultures and can be used as a support on the selection of the more suitable model type, taking into account the purpose of specific research.

Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities

Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called in silico communities, which allow us to explore the possibilities of bacterial flow cytometry data using supervised machine learning techniques. We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic (i.e., in vitro) communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general.

Exploring the potential of the glycerol-3-phosphate dehydrogenase 2 (GPD2) promoter for recombinant gene expression in Saccharomyces cerevisiae

A control point for keeping redox homeostasis in Saccharomyces cerevisiae during fermentative growth is the dynamic regulation of transcription for the glycerol-3-phosphate dehydrogenase 2 (GPD2) gene. In this study, the possibility to steer the activity of the GPD2 promoter was investigated by placing it in strains with different ability to reoxidise NADH, and applying different environmental conditions. Flow cytometric analysis of reporter strains expressing green fluorescent protein (GFP) under the control of the GPD2 promoter was used to determine the promoter activity at the single-cell level. When placed in a gpd1Δgpd2Δ strain background, the GPD2 promoter displayed a 2-fold higher activity as compared to the strong constitutive glyceraldehyde-3-phosphate dehydrogenase (TDH3). In contrast, the GPD2 promoter was found to be inactive when cells were cultivated in continuous mode at a growth rate of 0.3 h⁻¹ and in conditions with excess oxygen (i.e. with an aeration of 2.5 vvm, and a stirring of 800 rpm). In addition, a clear window of operation where the gpd1Δgpd2Δ strain can be grown with the same efficiency as wild type yeast was identified. In conclusion, the flow cytometry mapping revealed conditions where the GPD2 promoter was either completely inactive or hyperactive, which has implications for its implementation in future biotechnological applications such as for process control of heterologous gene expression.

Making a big thing of a small cell--recent advances in single cell analysis

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.