Synthetic Pathway for Production of Five-Carbon Alcohols from Isopentenyl Diphosphate

ABSTRACTSynthetic biological pathways could enhance the development of novel processes to produce chemicals from renewable resources. On the basis of models that describe the evolution of metabolic pathways and enzymes in nature, we developed a framework to rationally identify enzymes able to catalyze reactions on new substrates that overcomes one of the major bottlenecks in the assembly of a synthetic biological pathway. We verified the framework by implementing a pathway with two novel enzymatic reactions to convert isopentenyl diphosphate into 3-methyl-3-butenol, 3-methyl-2-butenol, and 3-methylbutanol. To overcome competition with native pathways that share the same substrate, we engineered two bifunctional enzymes that redirect metabolic flux toward the synthetic pathway. Taken together, our work demonstrates a new approach to the engineering of novel synthetic pathways in the cell.

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General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways

Metabolites ◽

10.3390/metabo11060336 ◽

2021 ◽

Vol 11 (6) ◽

pp. 336

Author(s):

Boštjan Murovec ◽

Leon Deutsch ◽

Blaž Stres

Keyword(s):

16S Rrna ◽

Metabolic Pathways ◽

Large Scale ◽

Enzymatic Reactions ◽

Operational Taxonomic Units ◽

Biochemical Pathways ◽

Meaningful Information ◽

Novel Biomarkers ◽

Reproducible Analysis ◽

Microbiome Profiling

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

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In Silico Evolution of Early Metabolism

Artificial Life ◽

10.1162/artl_a_00021 ◽

2011 ◽

Vol 17 (2) ◽

pp. 87-108 ◽

Cited By ~ 8

Author(s):

Alexander Ullrich ◽

Markus Rohrschneider ◽

Gerik Scheuermann ◽

Peter F. Stadler ◽

Christoph Flamm

Keyword(s):

Metabolic Pathways ◽

Genetic System ◽

Simulation Tool ◽

Metabolic Evolution ◽

Metabolic System ◽

Evolution Of Metabolic Pathways ◽

Core Set ◽

Catalytically Active ◽

Almost Open ◽

In Silico Evolution

We developed a simulation tool for investigating the evolution of early metabolism, allowing us to speculate on the formation of metabolic pathways from catalyzed chemical reactions and on the development of their characteristic properties. Our model consists of a protocellular entity with a simple RNA-based genetic system and an evolving metabolism of catalytically active ribozymes that manipulate a rich underlying chemistry. Ensuring an almost open-ended and fairly realistic simulation is crucial for understanding the first steps in metabolic evolution. We show here how our simulation tool can be helpful in arguing for or against hypotheses on the evolution of metabolic pathways. We demonstrate that seemingly mutually exclusive hypotheses may well be compatible when we take into account that different processes dominate different phases in the evolution of a metabolic system. Our results suggest that forward evolution shapes metabolic network in the very early steps of evolution. In later and more complex stages, enzyme recruitment supersedes forward evolution, keeping a core set of pathways from the early phase.

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DIRECTED EVOLUTION OF METABOLIC PATHWAYS IN MICROBIAL POPULATIONS. I. MODIFICATION OF THE ACID PHOSPHATASE pH OPTIMUM IN S. CEREVISIAE

Genetics ◽

10.1093/genetics/70.1.59 ◽

1972 ◽

Vol 70 (1) ◽

pp. 59-73 ◽

Cited By ~ 2

Author(s):

J C Francis ◽

P E Hansche

Keyword(s):

Acid Phosphatase ◽

Metabolic Pathways ◽

Experimental System ◽

Microbial Populations ◽

Kinetic Properties ◽

Mutational Event ◽

Ph Optimum ◽

Functional Changes ◽

Evolution Of Metabolic Pathways ◽

Wide Range

ABSTRACT An experimental system for directing the evolution of enzymes and metabolic pathways in microbial populations is proposed and an initial test of its power is provided.—The test involved an attempt to genetically enhance certain functional properties of the enzyme acid phosphatase in S. cerevisiae by constructing an environment in which the functional changes desired would be "adaptive". Naturally occurring mutations in a population of 109 cells were automatically and continuously screened, over 1,000 generations, for their effect on the efficiency (Km) and activity of acid phosphatase at pH 6, and for their effect on the efficiency of orthophosphate metabolism.—The first adaptation observed, M1, was due to a single mutational event that effected a 30% increase in the efficiency of orthophosphate metabolism. The second, M2, effected an adaptive shift in the pH optimum of acid phosphatase and an increase in its activity over a wide range of pH values (an increment of 60% at pH 6). M2 was shown to result from a single mutational event in the region of the acid phosphatase structural gene. The third, M3, effected cell clumping, an adaptation to the culture apparatus that had no effect on phosphate metabolism.—The power of this system for directing the evolution of enzymes and of metabolic pathways is discussed in terms of the kinetic properties of the experimental system and in terms of the results obtained.

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Effects of microcompartmentation on flux distribution and metabolic pools in Chlamydomonas reinhardtii chloroplasts

eLife ◽

10.7554/elife.37960 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 8

Author(s):

Anika Küken ◽

Frederik Sommer ◽

Liliya Yaneva-Roder ◽

Luke CM Mackinder ◽

Melanie Höhne ◽

...

Keyword(s):

Experimental Data ◽

Chlamydomonas Reinhardtii ◽

Metabolic Pathways ◽

Metabolic Flux ◽

Flux Distribution ◽

Photosynthetic Performance ◽

Computational Approach ◽

Cellular Processes ◽

Diffusional Barrier ◽

Computational Strategy

Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.

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Chemical Mutagenesis and Fluorescence-Based High-Throughput Screening for Enhanced Accumulation of Carotenoids in a Model Marine Diatom Phaeodactylum tricornutum

Marine Drugs ◽

10.3390/md16080272 ◽

2018 ◽

Vol 16 (8) ◽

pp. 272 ◽

Cited By ~ 8

Author(s):

Zhiqian Yi ◽

Yixi Su ◽

Maonian Xu ◽

Andreas Bergmann ◽

Saevar Ingthorsson ◽

...

Keyword(s):

High Throughput ◽

Metabolic Pathways ◽

Phaeodactylum Tricornutum ◽

Mass Spectrometry Data ◽

Marine Diatom ◽

Chemical Mutagenesis ◽

Carotenoid Content ◽

Enzymatic Reactions ◽

Wild Type ◽

A Genome

Diatoms are a major group of unicellular algae that are rich in lipids and carotenoids. However, sustained research efforts are needed to improve the strain performance for high product yields towards commercialization. In this study, we generated a number of mutants of the model diatom Phaeodactylum tricornutum, a cosmopolitan species that has also been found in Nordic region, using the chemical mutagens ethyl methanesulfonate (EMS) and N-methyl-N′-nitro-N-nitrosoguanidine (NTG). We found that both chlorophyll a and neutral lipids had a significant correlation with carotenoid content and these correlations were better during exponential growth than in the stationary growth phase. Then, we studied P. tricornutum common metabolic pathways and analyzed correlated enzymatic reactions between fucoxanthin synthesis and pigmentation or lipid metabolism through a genome-scale metabolic model. The integration of the computational results with liquid chromatography-mass spectrometry data revealed key compounds underlying the correlative metabolic pathways. Approximately 1000 strains were screened using fluorescence-based high-throughput method and five mutants selected had 33% or higher total carotenoids than the wild type, in which four strains remained stable in the long term and the top mutant exhibited an increase of 69.3% in fucoxanthin content compared to the wild type. The platform described in this study may be applied to the screening of other high performing diatom strains for industrial applications.

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Selection of enzymatic mechanisms which account for simplicity in the evolution of metabolic pathways

World Congress of Nonlinear Analysts '92 ◽

10.1515/9783110883237.3291 ◽

1996 ◽

pp. 3291-3304

Keyword(s):

Metabolic Pathways ◽

Evolution Of Metabolic Pathways ◽

Enzymatic Mechanisms ◽

Selection Of

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Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis

Nucleic Acids Research ◽

10.1093/nar/gkz1123 ◽

2019 ◽

Vol 48 (2) ◽

pp. 996-1009 ◽

Cited By ~ 19

Author(s):

Yaokang Wu ◽

Taichi Chen ◽

Yanfeng Liu ◽

Rongzhen Tian ◽

Xueqin Lv ◽

...

Keyword(s):

Bacillus Subtilis ◽

Metabolic Pathways ◽

Metabolic Flux ◽

Target Genes ◽

Fine Tuning ◽

Dual Control ◽

Genetic Circuits ◽

Dynamic Regulation ◽

Batch Bioreactor ◽

Acetoin Production

Abstract Dynamic regulation is an effective strategy for fine-tuning metabolic pathways in order to maximize target product synthesis. However, achieving dynamic and autonomous up- and down-regulation of the metabolic modules of interest simultaneously, still remains a great challenge. In this work, we created an autonomous dual-control (ADC) system, by combining CRISPRi-based NOT gates with novel biosensors of a key metabolite in the pathway of interest. By sensing the levels of the intermediate glucosamine-6-phosphate (GlcN6P) and self-adjusting the expression levels of the target genes accordingly with the GlcN6P biosensor and ADC system enabled feedback circuits, the metabolic flux towards the production of the high value nutraceutical N-acetylglucosamine (GlcNAc) could be balanced and optimized in Bacillus subtilis. As a result, the GlcNAc titer in a 15-l fed-batch bioreactor increased from 59.9 g/l to 97.1 g/l with acetoin production and 81.7 g/l to 131.6 g/l without acetoin production, indicating the robustness and stability of the synthetic circuits in a large bioreactor system. Remarkably, this self-regulatory methodology does not require any external level of control such as the use of inducer molecules or switching fermentation/environmental conditions. Moreover, the proposed programmable genetic circuits may be expanded to engineer other microbial cells and metabolic pathways.

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