Estimating effects of yeast extract compositions on Escherichia coli growth by a metabolomics approach

Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy

BACKGROUND

To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible.

RESULTS

We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples.

SIGNIFICANCE

The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.

Effect of yeast extract on microbiologically influenced corrosion of X70 pipeline steel by Desulfovibrio bizertensis SY-1

Microbiologically influenced corrosion (MIC) is a complicated process that happens ubiquitously and quietly in many fields. As a useful nutritional ingredient in microbial culture media, yeast extract (YE) is a routinely added in the MIC field. However, how the YE participated in MIC is not fully clarified. In the present work, the effect of YE on the growth of sulfate reducing prokaryotes (SRP) Desulfovibrio bizertensis SY-1 and corrosion behavior of X70 pipeline steel were studied. It was found that the weight loss of steel coupons in sterile media was doubled when YE was removed from culture media. However, in the SRP assays without YE the number of planktonic cells decreased, but the attachment of bacteria on steel surfaces was enhanced significantly. Besides, the corrosion rate of steel in SRP assays increased fourfold after removing YE from culture media. MIC was not determined for assays with planktonic SRP but only for biofilm assays. The results confirm the effect of YE on D. bizertensis SY-1 growth and also the inhibitory role of YE on MIC.

Dynamic flux balance analysis of high cell density fed-batch culture of Escherichia coli BL21 (DE3) with mass spectrometry-based spent media analysis

Dynamic flux balance analysis (FBA) allows estimation of intracellular reaction rates using organism-specific genome-scale metabolic models (GSMM) and by assuming instantaneous pseudo-steady states for processes that are inherently dynamic. This technique is well-suited for industrial bioprocesses employing complex media characterized by a hierarchy of substrate uptake and product secretion. However, knowledge of exchange rates of many components of the media would be required to obtain meaningful results. Here, we performed spent media analysis using mass spectrometry coupled with liquid and gas chromatography for a fed-batch, high-cell density cultivation of Escherichia coli BL21(DE3) expressing a recombinant protein. Time course measurements thus obtained for 246 metabolites were converted to instantaneous exchange rates. These were then used as constraints for dynamic FBA using a previously reported GSMM, thus providing insights into how the flux map evolves through the process. Changes in tri-carboxylic acid cycle fluxes correlated with the increased demand for energy during recombinant protein production. The results show how amino acids act as hubs for the synthesis of other cellular metabolites. Our results provide a deeper understanding of an industrial bioprocess and will have implications in further optimizing the process.

Metabolome analysis of metabolic burden in Escherichia coli caused by overexpression of green fluorescent protein and delta-rhodopsin

Overexpression of proteins by introducing a DNA vector is among the most important tools for the metabolic engineering of microorganisms such as Escherichia coli. Protein overexpression imposes a burden on metabolism because metabolic pathways must supply building blocks for protein and DNA synthesis. Different E. coli strains have distinct metabolic capacities. In this study, two proteins were overexpressed in four E. coli strains (MG1655(DE3), W3110(DE3), BL21star(DE3), and Rosetta(DE3)), and their effects on metabolic burden were investigated. Metabolomic analysis showed that E. coli strains overexpressing green fluorescent protein had decreased levels of several metabolites, with a positive correlation between the number of reduced metabolites and green fluorescent protein expression levels. Moreover, nucleic acid-related metabolites decreased, indicating a metabolic burden in the E. coli strains, and the growth rate and protein expression levels were improved by supplementation with the five nucleosides. In contrast, two strains overexpressing delta rhodopsin, a microbial membrane rhodopsin from Haloterrigena turkmenica, led to a metabolic burden and decrease in the amino acids Ala, Val, Leu, Ile, Thr, Phe, Asp, and Trp, which are the most frequent amino acids in the delta rhodopsin protein sequence. The metabolic burden caused by protein overexpression was influenced by the metabolic capacity of the host strains and the sequences of the overexpressed proteins. Detailed characterization of the effects of protein expression on the metabolic state of engineered cells using metabolomics will provide insights into improving the production of target compounds.

Precision fermentation with mass spectrometry-based spent media analysis

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

Yeast Extract: Characteristics, Production, Applications and Future Perspectives

Yeast extract is a product prepared mainly from waste brewer's yeast, which is rich in nucleotides, proteins, amino acids, sugars and a variety of trace elements, and has the advantages of low production cost and abundant supply of raw material. Consequently, yeast extracts are widely used in various fields as animal feed additives, food flavoring agents and additives, cosmetic supplements, and microbial fermentation media; however, their full potential has not yet been realized. To improve understanding of current research knowledge, this review summarizes the ingredients, production technology, and applications of yeast extracts, and discusses the relationship between their properties and applications. Developmental trends and future prospects of yeast extract are also previewed, with the aim of providing a theoretical basis for the development and expansion of future applications.

Enhanced recombinant carbonic anhydrase in T7RNAP-equipped Escherichia coli W3110 for carbon capture storage and utilization (CCSU)

Sulfurihydrogenibium yellowstonense carbonic anhydrase (SyCA) is a well-known thermophilic CA for carbon mineralization. To broaden the applications of SyCA, the activity of SyCA was improved through stepwise engineering and in different cultural conditions, as well as extended to co-expression with other enzymes. The engineered W3110 strains with 4 different T7 RNA polymerase levels were employed for SyCA production. As a result, the best strain WT7L cultured in modified M9 medium with temperature shifted from 37 to 30 °C after induction increased SyCA activity to 9122 U/mL. The SyCA whole-cell biocatalyst was successfully applied for carbon capture and storage (CCS) of CaCO₃. Furthermore, SyCA was applied for low-carbon footprint synthesis of 5-aminolevulinic acid (5-ALA) and cadaverine (DAP) by coupling with ALA synthetase (ALAS) and lysine decarboxylase (CadA), suppressing CO₂ release to -6.1 g-CO₂/g-ALA and -2.53 g-CO₂/g-DAP, respectively. Harnessing a highly active SyCA offers a complete strategy for CCSU in a green process.

Efficient molasses utilization for low-molecular-weight poly-γ-glutamic acid production using a novel Bacillus subtilis stain

Background

Poly-γ-glutamic acid (γ-PGA) is a biopolymer and has various applications based on its biocompatibility, non-toxicity, and edibility. Low-molecular-weight (Mw)-γ-PGA has promising applications in agriculture and pharmaceuticals. It is traditionally produced by enzymatic hydrolysis. Cost-effective bioproduction of low-Mw-γ-PGA is essential for commercial application of γ-PGA.

Results

Bacillus subtilis 242 is a newly isolated low-Mw-γ-PGA-producing strain. To develop cost-effective production of γ-PGA using this newly isolated strain, cane molasses and corn steep liquor were used to produce γ-PGA. The concentration of cane molasses was optimized and 100 g/L cane molasses resulted in high γ-PGA production. The effects of yeast extract and corn steep liquor on γ-PGA yield were investigated. High concentration of γ-PGA was obtained in the medium with corn steep liquor. A concentration of 32.14 g/L γ-PGA was achieved in fed-batch fermentation, with a productivity of 0.67 g/L/h and a percentage yield (g_γ-PGA/g_glutamate) of 106.39%. The Mw of γ-PGA was 27.99 kDa.

Conclusion

This study demonstrated the potential application of B. subtilis 242 for cost-effective production of low-Mw-γ-PGA from cane molasses.

Machine learning modeling of the effects of media formulated with various yeast extracts on heterologous protein production in Escherichia coli

In microbial manufacturing, yeast extract is an important component of the growth media. The production of heterologous proteins often varies because of the yeast extract composition. To identify why this reduces protein production, the effects of yeast extract composition on the growth and green fluorescent protein (GFP) production of engineered Escherichia coli were investigated using a deep neural network (DNN)-mediated metabolomics approach. We observed 205 peaks from the various yeast extracts using gas chromatography-mass spectrometry. Principal component analyses of the peaks identified at least three different clusters. Using 20 different compositions of yeast extract in M9 media, the yields of cells and GFP in the yeast extract-containing media were higher than those in the control without yeast extract by approximately 3.0- to 5.0-fold and 1.5- to 2.0-fold, respectively. We compared machine learning models and found that DNN best fit the data. To estimate the importance of each variable, we performed DNN with a mean increase error calculation based on a permutation algorithm. This method identified the significant components of yeast extract. DNN learning with varying numbers of input variables provided the number of significant components. The influence of specific components on cell growth and GFP production was confirmed with a validation cultivation.

A Strategy to Improve Production of Recombinant Proteins in Escherichia coli Based on a Glucose-Glycerol Mixture and Glutamate

Enzymes have a wide range of applications in many sectors of the industry, and the market value has skyrocketed in recent years. Glucose and glycerol are two renewable carbon sources of importance. Therefore, it is appealing to produce recombinant enzymes with these carbon substrates on the basis of economic viability. In this study, glycerol metabolism and glucose metabolism in Escherichia coli (E. coli) were manipulated in a systematic way. In addition, glutamate (Glu) was used for replacement of yeast extract to reduce the cost and the quality-variation problem. A strategy was further developed to incorporate Glu into the central metabolism. The engineered E. coli strain finally enabled efficient co-utilization of glucose and glycerol and improved biomass and protein production by 4.3 and 8.2-folds, respectively. The result illustrates that this proposed approach is promising for effective production of recombinant proteins.

Detailed small-scale characterization and scale-up of active YFP inclusion body production with Escherichia coli induced by a tetrameric coiled coil domain

During heterologous protein production with Escherichia coli, the formation of inclusion bodies (IBs) is often a major drawback as these aggregated proteins are usually inactive. However, different strategies for the generation of IBs consisting of catalytically active proteins have recently been described. In this study, the archaeal tetrameric coiled-coil domain of the cell-surface protein tetrabrachion was fused to a target reporter protein to produce fluorescent IBs (FIBs). As the cultivation conditions severely influence IB formation, the entire cultivation process resulting in the production of FIBs were thoroughly studied. First, the cultivation process was scaled down based on the maximum oxygen transfer capacity, combining online monitoring technologies for shake flasks and microtiter plates with offline sampling. The evaluation of culture conditions in complex terrific broth autoinduction medium showed strong oxygen limitation and leaky expression. Furthermore, strong acetate formation and pH changes from 6.5 to 8.8 led to sub-optimal cultivation conditions. However, in minimal Wilms-MOPS autoinduction medium, defined culture conditions and a tightly controlled expression were achieved. The production of FIBs is strongly influenced by the induction strength. Increasing induction strengths result in lower total amounts of functional protein. However, the amount of functional FIBs increases. Furthermore, to prevent the formation of conventional inactive IBs, a temperature shift from 37 °C to 15 °C is crucial to generate FIBs. Finally, the gained insights were transferred to a stirred tank reactor batch fermentation. Hereby, 12 g/L FIBs were produced, making up 43 % (w/w) of the total generated biomass.