Engineering of Metabolic Pathways Using Synthetic Enzyme Complexes

Smirnoff, Nicholas

doi:10.1104/pp.18.01280

Cited by 20 publications

(22 citation statements)

References 99 publications

(116 reference statements)

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“…The prevailing view of the cytosol is that it is dominated by random diffusion of enzymes and metabolic intermediates; however, work over the past four decades suggests that dynamic supramolecular assemblies of enzymes are prevalent [35][36][37] . Such assemblies are often called metabolons since they are assumed to mediate metabolite channeling; however, evidence suggests that the case is indeed relatively scarce and can be difficult to interpret 11,[38][39][40][41][42] . The strongest evidence for such studies is provided by the so-called dilution experiments, whereby labeled substrate is provided to a pathway and the labeling pattern in the pathway product is followed over time in response to the provision of unlabeled intermediates.…”

Section: Discussionmentioning

confidence: 99%

“…The dynamics of glycolytic enzyme assemblies were recently followed using fluorescence resonance energy transfer (FRET) 8 and fluorescence recovery after photobleaching in living human cells 9 , demonstrating that the first four enzymes of the glycolytic pathway each independently follows its own specific substrate gradient-providing an important insight into the potential mechanism of assembly of enzyme complexes 4,9,10 . Moreover, using fluorophore-tagged enzymes to follow movement in microfluidic devices, enzymes have been suggested to show chemotactic movement along their substrate gradient 11 . However, it is important to note that these studies remain somewhat controversial, with the argument being raised that the observations may be an artifact of the measurement method 11 .…”

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“…Moreover, using fluorophore-tagged enzymes to follow movement in microfluidic devices, enzymes have been suggested to show chemotactic movement along their substrate gradient 11 . However, it is important to note that these studies remain somewhat controversial, with the argument being raised that the observations may be an artifact of the measurement method 11 .…”

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A moonlighting role for enzymes of glycolysis in the co-localization of mitochondria and chloroplasts

et al. 2020

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Glycolysis is one of the primordial pathways of metabolism, playing a pivotal role in energy metabolism and biosynthesis. Glycolytic enzymes are known to form transient multi-enzyme assemblies. Here we examine the wider protein-protein interactions of plant glycolytic enzymes and reveal a moonlighting role for specific glycolytic enzymes in mediating the co-localization of mitochondria and chloroplasts. Knockout mutation of phosphoglycerate mutase or enolase resulted in a significantly reduced association of the two organelles. We provide evidence that phosphoglycerate mutase and enolase form a substrate-channelling metabolon which is part of a larger complex of proteins including pyruvate kinase. These results alongside a range of genetic complementation experiments are discussed in the context of our current understanding of chloroplast-mitochondrial interactions within photosynthetic eukaryotes.

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confidence: 99%

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A moonlighting role for enzymes of glycolysis in the co-localization of mitochondria and chloroplasts

et al. 2020

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“…As such, many aspects of engineering a microbe for overproducing a metabolite can be characterized as an optimization problem. Specifically, a key concern in metabolic engineering has been the selection of enzymes with high activity under a broad range of conditions, and strong promoters and ribosome binding sites, and the tuning of expression of multiple genes [1][2][3][4]. These goals could not be achieved through rational selection, but only with trial and error experimentation.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Potential of Applying Machine Learning Tools to Metabolic Pathway Optimization

Ng¹

2020

Preprint

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Successful engineering of a microbial host for efficient production of a target product from a given substrate can be viewed as an extensive optimization task. Such a task involves the selection of high activity enzymes as well as their gene expression regulatory control elements (i.e., promoters and ribosome binding sites). Finally, there is also the need to tune expression of multiple genes along a heterologous pathway to relieve constraints from rate-limiting step and help reduce metabolic burden on cells from unnecessary over-expression of high activity enzymes. While the aforementioned tasks could be performed through combinatorial experiments, such an approach incurs significant cost, time and effort, which is a handicap that can be relieved by application of modern machine learning tools. Such tools could attempt to predict high activity enzymes from sequence, but they are currently most usefully applied in classifying strong promoters from weaker ones as well as combinatorial tuning of expression of multiple genes. This perspective reviews the application of machine learning tools to aid metabolic pathway optimization through identifying challenges in metabolic engineering that could be overcome with the help of machine learning tools.

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“…Two further core SynBio technologies are protein engineering and directed evolution, both of which are reviewed by Engqvist and Rabe (2019). Another core technology is the construction of synthetic enzyme complexes, comprehensively reviewed by Smirnoff (2019) In closing their Update, Weber and Bar-Even (2019) quote Nobel Peace Prize winner Norman Borlaug: "Then I wake up and become disillusioned to find that mutation genetics programs are still engaged mostly in such minutiae as putting beards on wheat plants and taking off the hairs." Weber and Bar-Even then add on their own account, "we should leave the minutiae behind and reap the full potential of synthetic biology to overcome one of the major challenges of the 21st century, sustainably feeding a growing population without destroying the environment."…”

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Focus Issue Editorial: Synthetic Biology

et al. 2019

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Synthetic biology (SynBio) is a conceptual and operational revolution (Church et al., 2014) that's coming soon to a branch of plant science near you, if it's not there already (Liu and Stewart, 2015). The Synthetic Biology Focus Issue sets out to spread this disruptive news. SynBio is a transformative combination of DNA technology, engineering principles, and computational tools that makes it possible to design new life processes and to repurpose existing natural ones for useful purposes (Purnick and Weiss, 2009). SynBio will profoundly impact and empower how plant science is done and how plant science is used to sustainably solve global problems. SynBio is already creating new jobs and is likely to keep doing this for decades (Delebecque and Philp, 2015). SynBio is powerful for conceptual and operational reasons. The enormous conceptual power of SynBio is to open access to the vast "design space" that plants, and nature in general, have not explored (Bhatia et al., 2017). By discovering and deploying useful design space that evolution has "missed," SynBio enables plants: to make familiar compounds by new pathways, and make new-to-nature compounds; to supply genes needed to make high-value compounds in microorganisms; to manipulate familiar morphological structures, and build totally new-to-nature ones; to respond in new ways to old stimuli, and sense and respond to totally new stimuli; and to be managed based on weather forecasts and other predictions that plants cannot make themselves. The transformative operational power of SynBio lies in its drive to industrialize biology: that is, to replace highskill, slow, and costly artisanal work such as cloning and custom assays with computationally guided, automated, and standardized engineering procedures (Cameron et al., 2014; Chao et al., 2017). Although the industrialscale engineering potential of SynBio is far from fully realized at this point (Davies, 2019), it is very much here to stay and has begun to dictate major changes in biology education and training (National Research Council, 2015). Whether you are a trainee or a trainer, these trends are seriously worth considering for your future career's sake. A hallmark of SynBio is to rethink biological molecules, genes and proteins, as engineering "parts" that can be standardized, quantitatively characterized, and used to build a range of devices, much as standard resistors and capacitors are used as components in countless different electrical circuits (de Lorenzo and Schmidt, 2018). In the case of metabolic pathways, for instance, enzyme parts from plants or other organisms can be used as is and combined in novel ways to build

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Engineering of Metabolic Pathways Using Synthetic Enzyme Complexes

Cited by 20 publications

References 99 publications

A moonlighting role for enzymes of glycolysis in the co-localization of mitochondria and chloroplasts

A moonlighting role for enzymes of glycolysis in the co-localization of mitochondria and chloroplasts

Evaluating the Potential of Applying Machine Learning Tools to Metabolic Pathway Optimization

Focus Issue Editorial: Synthetic Biology

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