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Metabolic Engineering and Synthetic Biology Volume 2

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A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Microbiology and Ecological Metabolomics".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 59989

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Prof. Dr. Lars M. Blank

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Guest Editor

Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
Interests: synthetic biology; metabolomics; metabolic engineering; metabolic flux analysis; bioeconomy

Dr. An N.T. Phan

E-Mail Website
Guest Editor

Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
Interests: Ustilago; metabolomics; metabolic engineering; metabolic flux analysis; mass spectrometry

Special Issue Information

Dear Colleagues,

In times of ever-increasing demand for chemicals and the subsequent increase of CO₂ in the atmosphere, we have to intensify our efforts to establish a circular (bio)economy. To reduce fossil resource use, alternative carbon sources including biomass and CO₂ itself need to be used. The (bio)catalysts of choice that are able to convert these carbon sources into valuable chemicals often have to be tailored to meet the industrial requirements in titer, rate, and yield, and, hence, ultimately in cost. While exciting examples exist, from vitamins to plastic monomers and bioplastics, the metabolic engineering of such biocatalysts is still time and cost consuming. With the improvement of genetic tools and ideas for genetic standardization, creating and/or building new whole-cell biocatalysts becomes an ever more rapid task. However, the two other aspects of the design/build/test cycle are to some extent still very cumbersome. While computational tools support whole-cell biocatalyst design, parallelization and miniaturization speed up the characterization of mutants. Still, the goal has to be a knowledge-based design and a high information content phenotyping.

In this Special Issue, we ask for contributions of metabolic engineering and synthetic biology that are driven by flux and/or metabolome approaches. We would like to emphasize the importance of sample preparation and data evaluation. Fluxes of all intracellular biochemical reaction steps are the ultimate outcome of genetic and environmental alterations. We are convinced that quantitative approaches in metabolite analysis will help to reduce the time required to establish an efficient whole-cell biocatalyst. While the concentrations of intracellular metabolites can highlight enzymatic bottlenecks, the intracellular fluxes might help decipher redox cofactor imbalances, futile cycles, and the use of alternative pathways. Thermodynamically feasible reaction conditions can not only explain the phenotype observed but may also lead to genetic targets for further strain improvement and to new biochemical network designs.

Prof. Dr. Lars M. Blank
Dr. An N. T. Phan
Guest Editors

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Keywords

metabolic engineering
synthetic biology
metabolomics
metabolic flux analysis
cell factory
bioeconomy

Published Papers (11 papers)

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Editorial

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3 pages, 177 KiB

Open AccessEditorial

Special Issue “Metabolic Engineering and Synthetic Biology Volume 2”

by An N. T. Phan and Lars M. Blank

Metabolites 2021, 11(1), 35; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11010035 - 06 Jan 2021

Viewed by 1700

Abstract

In times of ever-increasing demand for chemicals and the subsequent increase in CO₂ in the atmosphere, we have to intensify our efforts to establish a circular (bio) economy [...] Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

Research

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17 pages, 3061 KiB

Open AccessArticle

Streamlining the Analysis of Dynamic ¹³C-Labeling Patterns for the Metabolic Engineering of Corynebacterium glutamicum as l-Histidine Production Host

by André Feith, Andreas Schwentner, Attila Teleki, Lorenzo Favilli, Bastian Blombach and Ralf Takors

Metabolites 2020, 10(11), 458; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10110458 - 12 Nov 2020

Cited by 6 | Viewed by 2273

Abstract

Today’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream ¹³C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicuml-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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22 pages, 3933 KiB

Open AccessArticle

Photosynthetic Co-production of Succinate and Ethylene in a Fast-Growing Cyanobacterium, Synechococcus elongatus PCC 11801

by Annesha Sengupta, Prem Pritam, Damini Jaiswal, Anindita Bandyopadhyay, Himadri B. Pakrasi and Pramod P. Wangikar

Metabolites 2020, 10(6), 250; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10060250 - 16 Jun 2020

Cited by 31 | Viewed by 4155

Abstract

Cyanobacteria are emerging as hosts for photoautotrophic production of chemicals. Recent studies have attempted to stretch the limits of photosynthetic production, typically focusing on one product at a time, possibly to minimise the additional burden of product separation. Here, we explore the simultaneous production of two products that can be easily separated: ethylene, a gaseous product, and succinate, an organic acid that accumulates in the culture medium. This was achieved by expressing a single copy of the ethylene forming enzyme (efe) under the control of P_cpcB, the inducer-free super-strong promoter of phycocyanin β subunit. We chose the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801, as the host strain. A stable recombinant strain was constructed using CRISPR-Cpf1 in a first report of markerless genome editing of this cyanobacterium. Under photoautotrophic conditions, the recombinant strain shows specific productivities of 338.26 and 1044.18 μmole/g dry cell weight/h for ethylene and succinate, respectively. These results compare favourably with the reported productivities for individual products in cyanobacteria that are highly engineered. Metabolome profiling and ¹³C labelling studies indicate carbon flux redistribution and suggest avenues for further improvement. Our results show that S. elongatus PCC 11801 is a promising candidate for metabolic engineering. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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11 pages, 1021 KiB

Open AccessArticle

Heterologous Production of 6-Deoxyerythronolide B in Escherichia coli through the Wood Werkman Cycle

by R. Axayacatl Gonzalez-Garcia, Lars K. Nielsen and Esteban Marcellin

Metabolites 2020, 10(6), 228; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10060228 - 01 Jun 2020

Cited by 5 | Viewed by 2506

Abstract

Polyketides are a remarkable class of natural products with diverse functional and structural diversity. The class includes many medicinally important molecules with antiviral, antimicrobial, antifungal and anticancer properties. Native bacterial, fungal and plant hosts are often difficult to cultivate and coax into producing the desired product. As a result, Escherichia coli has been used for the heterologous production of polyketides, with the production of 6-deoxyerythronolide B (6-dEB) being the first example. Current strategies for production in E. coli require feeding of exogenous propionate as a source for the precursors propionyl-CoA and S-methylmalonyl-CoA. Here, we show that heterologous polyketide production is possible from glucose as the sole carbon source. The heterologous expression of eight genes from the Wood-Werkman cycle found in Propionibacteria, in combination with expression of the 6-dEB synthases DEBS1, DEBS2 and DEBS3 resulted in 6-dEB formation from glucose as the sole carbon source. Our results show that the Wood-Werkman cycle provides the required propionyl-CoA and the extender unit S-methylmalonyl-CoA to produce up to 0.81 mg/L of 6-dEB in a chemically defined media. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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15 pages, 1839 KiB

Open AccessArticle

Using Metabolomics to Identify Cell Line-Independent Indicators of Growth Inhibition for Chinese Hamster Ovary Cell-Based Bioprocesses

by Nicholas Alden, Ravali Raju, Kyle McElearney, James Lambropoulos, Rashmi Kshirsagar, Alan Gilbert and Kyongbum Lee

Metabolites 2020, 10(5), 199; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10050199 - 15 May 2020

Cited by 16 | Viewed by 4076

Abstract

Chinese hamster ovary (CHO) cells are widely used for the production of biopharmaceuticals. Efforts to improve productivity through medium design and feeding strategy optimization have focused on preventing the depletion of essential nutrients and managing the accumulation of lactate and ammonia. In addition to ammonia and lactate, many other metabolites accumulate in CHO cell cultures, although their effects remain largely unknown. Elucidating these effects has the potential to further improve the productivity of CHO cell-based bioprocesses. This study used untargeted metabolomics to identify metabolites that accumulate in fed-batch cultures of monoclonal antibody (mAb) producing CHO cells. The metabolomics experiments profiled six cell lines that are derived from two different hosts, produce different mAbs, and exhibit different growth profiles. Comparing the cell lines’ metabolite profiles at different growth stages, we found a strong negative correlation between peak viable cell density (VCD) and a tryptophan metabolite, putatively identified as 5-hydroxyindoleacetaldehyde (5-HIAAld). Amino acid supplementation experiments showed strong growth inhibition of all cell lines by excess tryptophan, which correlated with the accumulation of 5-HIAAld in the culture medium. Prospectively, the approach presented in this study could be used to identify cell line- and host-independent metabolite markers for clone selection and bioprocess development. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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13 pages, 2823 KiB

Open AccessArticle

Metabolomics Analysis Reveals Global Metabolic Changes in the Evolved E. coli Strain with Improved Growth and 1-Butanol Production in Minimal Medium

by Walter A. Laviña, Sana Subhan Memon Sakurai, Sammy Pontrelli, Sastia Prama Putri and Eiichiro Fukusaki

Metabolites 2020, 10(5), 192; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10050192 - 13 May 2020

Cited by 3 | Viewed by 3014

Abstract

Production of 1-butanol from microorganisms has garnered significant interest due to its prospect as a drop-in biofuel and precursor for a variety of commercially relevant chemicals. Previously, high 1-butanol titer has been reported in Escherichia coli strain JCL166, which contains a modified clostridial 1-butanol pathway. Although conventional and metabolomics-based strain improvement strategies of E. coli strain JCL166 have been successful in improving production in rich medium, 1-butanol titer was severely limited in minimal medium. To further improve growth and consequently 1-butanol production in minimal medium, adaptive laboratory evolution (ALE) using mutD5 mutator plasmid was done on JCL166. Comparative metabolomics analysis of JCL166 and BP1 revealed global perturbations in the evolved strain BP1 compared to JCL166 (44 out of 64 metabolites), encompassing major metabolic pathways such as glycolysis, nucleotide biosynthesis, and CoA-related processes. Collectively, these metabolic changes in BP1 result in improved growth and, consequently, 1-butanol production in minimal medium. Furthermore, we found that the mutation in ihfB caused by ALE had a significant effect on the metabolome profile of the evolved strain. This study demonstrates how metabolomics was utilized for characterization of ALE-developed strains to understand the overall effect of mutations acquired through evolution. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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15 pages, 2525 KiB

Open AccessArticle

In Vivo Rate of Formaldehyde Condensation with Tetrahydrofolate

by Hai He, Elad Noor, Perla A. Ramos-Parra, Liliana E. García-Valencia, Jenelle A. Patterson, Rocío I. Díaz de la Garza, Andrew D. Hanson and Arren Bar-Even

Metabolites 2020, 10(2), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10020065 - 12 Feb 2020

Cited by 14 | Viewed by 4155

Abstract

Formaldehyde is a highly reactive compound that participates in multiple spontaneous reactions, but these are mostly deleterious and damage cellular components. In contrast, the spontaneous condensation of formaldehyde with tetrahydrofolate (THF) has been proposed to contribute to the assimilation of this intermediate during growth on C₁ carbon sources such as methanol. However, the in vivo rate of this condensation reaction is unknown and its possible contribution to growth remains elusive. Here, we used microbial platforms to assess the rate of this condensation in the cellular environment. We constructed Escherichia coli strains lacking the enzymes that naturally produce 5,10-methylene-THF. These strains were able to grow on minimal medium only when equipped with a sarcosine (N-methyl-glycine) oxidation pathway that sustained a high cellular concentration of formaldehyde, which spontaneously reacts with THF to produce 5,10-methylene-THF. We used flux balance analysis to derive the rate of the spontaneous condensation from the observed growth rate. According to this, we calculated that a microorganism obtaining its entire biomass via the spontaneous condensation of formaldehyde with THF would have a doubling time of more than three weeks. Hence, this spontaneous reaction is unlikely to serve as an effective route for formaldehyde assimilation. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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Review

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20 pages, 1658 KiB

Open AccessReview

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae

by Hongting Tang, Yanling Wu, Jiliang Deng, Nanzhu Chen, Zhaohui Zheng, Yongjun Wei, Xiaozhou Luo and Jay D. Keasling

Metabolites 2020, 10(8), 320; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10080320 - 06 Aug 2020

Cited by 55 | Viewed by 9629

Abstract

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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23 pages, 2513 KiB

Open AccessEditor’s ChoiceReview

Machine Learning Applications for Mass Spectrometry-Based Metabolomics

by Ulf W. Liebal, An N. T. Phan, Malvika Sudhakar, Karthik Raman and Lars M. Blank

Metabolites 2020, 10(6), 243; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10060243 - 13 Jun 2020

Cited by 159 | Viewed by 15132

Abstract

The metabolome of an organism depends on environmental factors and intracellular regulation and provides information about the physiological conditions. Metabolomics helps to understand disease progression in clinical settings or estimate metabolite overproduction for metabolic engineering. The most popular analytical metabolomics platform is mass spectrometry (MS). However, MS metabolome data analysis is complicated, since metabolites interact nonlinearly, and the data structures themselves are complex. Machine learning methods have become immensely popular for statistical analysis due to the inherent nonlinear data representation and the ability to process large and heterogeneous data rapidly. In this review, we address recent developments in using machine learning for processing MS spectra and show how machine learning generates new biological insights. In particular, supervised machine learning has great potential in metabolomics research because of the ability to supply quantitative predictions. We review here commonly used tools, such as random forest, support vector machines, artificial neural networks, and genetic algorithms. During processing steps, the supervised machine learning methods help peak picking, normalization, and missing data imputation. For knowledge-driven analysis, machine learning contributes to biomarker detection, classification and regression, biochemical pathway identification, and carbon flux determination. Of important relevance is the combination of different omics data to identify the contributions of the various regulatory levels. Our overview of the recent publications also highlights that data quality determines analysis quality, but also adds to the challenge of choosing the right model for the data. Machine learning methods applied to MS-based metabolomics ease data analysis and can support clinical decisions, guide metabolic engineering, and stimulate fundamental biological discoveries. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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17 pages, 2178 KiB

Open AccessReview

Metabolic Engineering Design Strategies for Increasing Acetyl-CoA Flux

by Jason T. Ku, Arvin Y. Chen and Ethan I. Lan

Metabolites 2020, 10(4), 166; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10040166 - 23 Apr 2020

Cited by 29 | Viewed by 8284

Abstract

Acetyl-CoA is a key metabolite precursor for the biosynthesis of lipids, polyketides, isoprenoids, amino acids, and numerous other bioproducts which are used in various industries. Metabolic engineering efforts aim to increase carbon flux towards acetyl-CoA in order to achieve higher productivities of its downstream products. In this review, we summarize the strategies that have been implemented for increasing acetyl-CoA flux and concentration, and discuss their effects. Furthermore, recent works have developed synthetic acetyl-CoA biosynthesis routes that achieve higher stoichiometric yield of acetyl-CoA from glycolytic substrates. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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20 pages, 50537 KiB

Open AccessReview

Enzyme Assembly for Compartmentalized Metabolic Flux Control

by Xueqin Lv, Shixiu Cui, Yang Gu, Jianghua Li, Guocheng Du and Long Liu

Metabolites 2020, 10(4), 125; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10040125 - 26 Mar 2020

Cited by 17 | Viewed by 3978

Abstract

Enzyme assembly by ligand binding or physically sequestrating enzymes, substrates, or metabolites into isolated compartments can bring key molecules closer to enhance the flux of a metabolic pathway. The emergence of enzyme assembly has provided both opportunities and challenges for metabolic engineering. At present, with the development of synthetic biology and systems biology, a variety of enzyme assembly strategies have been proposed, from the initial direct enzyme fusion to scaffold-free assembly, as well as artificial scaffolds, such as nucleic acid/protein scaffolds, and even some more complex physical compartments. These assembly strategies have been explored and applied to the synthesis of various important bio-based products, and have achieved different degrees of success. Despite some achievements, enzyme assembly, especially in vivo, still has many problems that have attracted significant attention from researchers. Here, we focus on some selected examples to review recent research on scaffold-free strategies, synthetic artificial scaffolds, and physical compartments for enzyme assembly or pathway sequestration, and we discuss their notable advances. In addition, the potential applications and challenges in the applications are highlighted. Full article

(This article belongs to the Special Issue Metabolic Engineering and Synthetic Biology Volume 2)

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