Designer metalloenzymes for synthetic biology: Enzyme hybrids for catalysis

Combining organometallics and biology has generated broad interest from scientists working on applications from in situ drug release to biocatalysis. Engineered enzymes and biohybrid catalysts (also referred to as artificial enzymes) have introduced a wide range of abiotic chemistry into biocatalysis. Predominantly, this work has concentrated on using these catalysts for single step in vitro reactions. However, the promise of using these hybrid catalysts in vivo and combining them with synthetic biology and metabolic engineering is vast. This report will briefly review recent advances in artificial metalloenzyme design, followed by summarising recent studies that have looked at the use of these hybrid catalysts in vivo and in enzymatic cascades, therefore exploring their potential for synthetic biology.     

Evolutionary constraints permeate large metabolic networks

Background  

Metabolic networks show great evolutionary plasticity, because they can differ substantially even among closely related prokaryotes. Any one metabolic network can also effectively compensate for the blockage of individual reactions by rerouting metabolic flux through other pathways. These observations, together with the continual discovery of new microbial metabolic pathways and enzymes, raise the possibility that metabolic networks are only weakly constrained in changing their complement of enzymatic reactions.     

In silico,in vitro,and in vivo machine learning in synthetic biology and metabolic engineering

Among the main learning methods reviewed in this study and used in synthetic biology and metabolic engineering are supervised learning, reinforcement and active learning, and in vitro or in vivo learning.In the context of biosynthesis, supervised machine learning is being exploited to predict biological sequence activities, predict structures and engineer sequences, and optimize culture conditions.Active and reinforcement learning methods use training sets acquired through an iterative process generally involving experimental measurements. They are applied to design, engineer, and optimize metabolic pathways and bioprocesses.The nascent but promising developments with in vitro and in vivo learning comprise molecular circuits performing simple tasks such as pattern recognition and classification.     

Metabolomic profiling of permethrin-treated Drosophila melanogaster identifies a role for tryptophan catabolism in insecticide survival

Insecticides and associated synergists are rapidly losing efficacy in target insect pest populations making the discovery of alternatives a priority. To discover novel targets for permethrin synergists, metabolomics was performed on permethrin-treated Drosophila melanogaster. Changes were observed in several metabolic pathways including those for amino acids, glycogen, glycolysis, energy, nitrogen, NAD⁺, purine, pyrimidine, lipids and carnitine. Markers for acidosis, ammonia stress, oxidative stress and detoxification responses were also observed. Many of these changes had not been previously characterized after permethrin exposure. From the altered pathways, tryptophan catabolism was selected for further investigation. The knockdown of some tryptophan catabolism genes (vermilion, cinnabar and CG6950) in the whole fly and in specific tissues including fat body, midgut and Malpighian tubules using targeted RNAi resulted in altered survival phenotypes against acute topical permethrin exposure. The knockdown of vermilion, cinnabar and CG6950 in the whole fly also altered survival phenotypes against chronic oral permethrin, fenvalerate, DDT, chlorpyriphos and hydramethylnon exposure. Thus tryptophan catabolism has a previously uncharacterized role in defence against insecticides, and shows that metabolomics is a powerful tool for target identification in pesticide research.     

Emerging roles of secreted phospholipase A2 enzymes: An update

Phospholipase A₂ (PLA₂) enzymes catalyze the hydrolysis of the sn-2 position of glycerophospholipids to produce free fatty acids and lysophospholipids. More than one third of the mammalian PLA₂ enzymes belong to the secreted PLA₂ (sPLA₂) family, which consists of low molecular mass, Ca²⁺-requiring enzymes with a His–Asp catalytic dyad. Individual sPLA₂ enzymes exhibit unique tissue and cellular localizations and specific enzymatic properties, suggesting their distinct biological roles. The past decade has met a new era of the sPLA₂ research field toward deciphering their in vivo functions by developing several specific tools and methods. These include i) the production of transgenic and knockout mouse lines for several sPLA₂s, ii) the development of specific analytical tools including the production of large amounts of recombinant sPLA₂ proteins, and iii) applying mass spectrometry lipidomics to unveil their specific enzymatic properties occurring in vivo. It is now obvious that individual sPLA₂s are involved in diverse biological events through lipid mediator-dependent and -independent processes, act redundantly or non-redundantly in the context of physiology and pathophysiology, and may represent potential drug targets or novel bioactive molecules in certain situations. In this review, we will highlight the newest understanding of the biological roles of sPLA₂s in the past few years.     

Engineered biosynthetic pathways and biocatalytic cascades for sustainable synthesis

Nature exploits biosynthetic cascades to construct numerous molecules from a limited set of starting materials. A deeper understanding of biosynthesis and extraordinary developments in gene technology has allowed the manipulation of natural pathways and construction of artificial cascades for the preparation of a range of molecules, which would be challenging to access using traditional synthetic chemical approaches. Alongside these metabolic engineering strategies, there has been continued interest in developing in vivo and in vitro biocatalytic cascades. Advancements in both metabolic engineering and biocatalysis are complementary, and this article aims to highlight some of the most exciting developments in these two areas with a particular focus on exploring those that have the potential to advance both pathway engineering and more traditional biocatalytic cascade development.     

In vivo metabolite profiling as a means to identify uncharacterized lipase function: Recent success stories within the alpha beta hydrolase domain (ABHD) enzyme family

Genome sequencing efforts have identified many uncharacterized lipase/esterase enzymes that have potential to be drug targets for metabolic diseases such as obesity, diabetes, and atherosclerosis. However, sequence information and associated structural predictions provide only a loose framework for linking enzyme function to disease risk. We are now confronted with the challenge of functionally annotating a large number of uncharacterized lipases, with the goal of generating new therapies for metabolic diseases. This daunting challenge involves gathering not only sequence-driven predictions, but also more importantly structural, biochemical (substrates and products), and physiological data. At the center of such drug discovery efforts are accurately identifying physiologically relevant substrates and products of individual lipases, and determining whether newly identified substrates/products can modulate disease in appropriate preclinical animal model systems. This review describes the importance of coupling in vivo metabolite profiling to in vitro enzymology as a powerful means to assign lipase function in disease specific contexts using animal models. In particular, we highlight recent examples using this multidisciplinary approach to functionally annotate genes within the α/β hydrolase fold domain (ABHD) family of enzymes. These new discoveries within the ABHD enzyme family serve as powerful examples of linking novel lipase function to human disease. This article is part of a Special Issue entitled Tools to study lipid functions.     

Study of duplicated galU genes in Rhodococcus jostii and a putative new metabolic node for glucosamine-1P in rhodococci

BackgoundStudying enzymes that determine glucose-1P fate in carbohydrate metabolism is important to better understand microorganisms as biotechnological tools. One example ripe for discovery is the UDP-glucose pyrophosphorylase enzyme from Rhodococcus spp. In the R. jostii genome, this gene is duplicated, whereas R. fascians contains only one copy.MethodsWe report the molecular cloning of galU genes from R. jostii and R. fascians to produce recombinant proteins RjoGalU1, RjoGalU2, and RfaGalU. Substrate saturation curves were conducted, kinetic parameters were obtained and the catalytic efficiency (k_cat/K_m) was used to analyze enzyme promiscuity. We also investigated the response of R. jostii GlmU pyrophosphorylase activity with different sugar-1Ps, which may compete for substrates with RjoGalU2.ResultsAll enzymes were active as pyrophosphorylases and exhibited substrate promiscuity toward sugar-1Ps. Remarkably, RjoGalU2 exhibited one order of magnitude higher activity with glucosamine-1P than glucose-1P, the canonical substrate. Glucosamine-1P activity was also significant in RfaGalU. The efficient use of the phospho-amino-sugar suggests the feasibility of the reaction to occur in vivo. Also, RjoGalU2 and RfaGalU represent enzymatic tools for the production of (amino)glucosyl precursors for the putative synthesis of novel molecules.ConclusionsResults support the hypothesis that partitioning of glucosamine-1P includes an uncharacterized metabolic node in Rhodococcus spp., which could be important for producing diverse alternatives for carbohydrate metabolism in biotechnological applications.General significanceResults presented here provide a model to study evolutionary enzyme promiscuity, which could be used as a tool to expand an organism's metabolic repertoire by incorporating non-canonical substrates into novel metabolic pathways.     

Artificial intelligence for compound pharmacokinetics prediction

Optimisation of compound pharmacokinetics (PK) is an integral part of drug discovery and development. Animal in vivo PK data as well as human and animal in vitro systems are routinely utilised to evaluate PK in humans. In recent years machine learning and artificial intelligence (AI) emerged as a major tool for modelling of in vivo animal and human PK, enabling prediction from chemical structure early in drug discovery, and therefore offering opportunities to guide the design and prioritisation of molecules based on relevant in vivo properties and, ultimately, predicting human PK at the point of design. This review presents recent advances in machine learning and AI models for in vivo animal and human PK for small-molecule compounds as well as some examples for antibody therapeutics.     

A cell-free framework for rapid biosynthetic pathway prototyping and enzyme discovery

Speeding up design-build-test (DBT) cycles is a fundamental challenge facing biochemical engineering. To address this challenge, we report a new cell-free protein synthesis driven metabolic engineering (CFPS-ME) framework for rapid biosynthetic pathway prototyping. In our framework, cell-free cocktails for synthesizing target small molecules are assembled in a mix-and-match fashion from crude cell lysates either containing selectively enriched pathway enzymes from heterologous overexpression or directly producing pathway enzymes in lysates by CFPS. As a model, we apply our approach to n-butanol biosynthesis showing that Escherichia coli lysates support a highly active 17-step CoA-dependent n-butanol pathway in vitro. The elevated degree of flexibility in the cell-free environment allows us to manipulate physiochemical conditions, access enzymatic nodes, discover new enzymes, and prototype enzyme sets with linear DNA templates to study pathway performance. We anticipate that CFPS-ME will facilitate efforts to define, manipulate, and understand metabolic pathways for accelerated DBT cycles without the need to reengineer organisms.     

Physiological Role of Acyl Coenzyme A Synthetase Homologs in Lipid Metabolism in Neurospora crassa

Acyl coenzyme A (CoA) synthetase (ACS) enzymes catalyze the activation of free fatty acids (FAs) to CoA esters by a two-step thioesterification reaction. Activated FAs participate in a variety of anabolic and catabolic lipid metabolic pathways, including de novo complex lipid biosynthesis, FA β-oxidation, and lipid membrane remodeling. Analysis of the genome sequence of the filamentous fungus Neurospora crassa identified seven putative fatty ACSs (ACS-1 through ACS-7). ACS-3 was found to be the major activator for exogenous FAs for anabolic lipid metabolic pathways, and consistent with this finding, ACS-3 localized to the endoplasmic reticulum, plasma membrane, and septa. Double-mutant analyses confirmed partial functional redundancy of ACS-2 and ACS-3. ACS-5 was determined to function in siderophore biosynthesis, indicating alternative functions for ACS enzymes in addition to fatty acid metabolism. The N. crassa ACSs involved in activation of FAs for catabolism were not specifically defined, presumably due to functional redundancy of several of ACSs for catabolism of exogenous FAs.     

Contributions of Microorganisms to Industrial Biology

Life on earth is not possible without microorganisms. Microbes have contributed to industrial science for over 100 years. They have given us diversity in enzymatic content and metabolic pathways. The advent of recombinant DNA brought many changes to industrial microbiology. New expression systems have been developed, biosynthetic pathways have been modified by metabolic engineering to give new metabolites, and directed evolution has provided enzymes with modified selectability, improved catalytic activity and stability. More and more genomes of industrial microorganisms are being sequenced giving valuable information about the genetic and enzymatic makeup of these valuable forms of life. Major tools such as functional genomics, proteomics, and metabolomics are being exploited for the discovery of new valuable small molecules for medicine and enzymes for catalysis.     

Systematic phenome analysis of Escherichia coli multiple‐knockout mutants reveals hidden reactions in central carbon metabolism

Central carbon metabolism is a basic and exhaustively analyzed pathway. However, the intrinsic robustness of the pathway might still conceal uncharacterized reactions. To test this hypothesis, we constructed systematic multiple‐knockout mutants involved in central carbon catabolism in Escherichia coli and tested their growth under 12 different nutrient conditions. Differences between in silico predictions and experimental growth indicated that unreported reactions existed within this extensively analyzed metabolic network. These putative reactions were then confirmed by metabolome analysis and in vitro enzymatic assays. Novel reactions regarding the breakdown of sedoheptulose‐7‐phosphate to erythrose‐4‐phosphate and dihydroxyacetone phosphate were observed in transaldolase‐deficient mutants, without any noticeable changes in gene expression. These reactions, triggered by an accumulation of sedoheptulose‐7‐phosphate, were catalyzed by the universally conserved glycolytic enzymes ATP‐dependent phosphofructokinase and aldolase. The emergence of an alternative pathway not requiring any changes in gene expression, but rather relying on the accumulation of an intermediate metabolite may be a novel mechanism mediating the robustness of these metabolic networks.     

Early steps of metabolism evolution inferred by cladistic analysis of amino acid catabolic pathways

Among abiotic molecules available in primitive environments, free amino acids are good candidates as the first source of energy and molecules for early protocells. Amino acid catabolic pathways are likely to be one of the very first metabolic pathways of life. Among them, which ones were the first to emerge? A cladistic analysis of catabolic pathways of the sixteen aliphatic amino acids and two portions of the Krebs cycle is performed using four criteria of homology. The cladogram shows that the earliest pathways to emerge are not portions of the Krebs cycle but catabolisms of aspartate, asparagine, glutamate, glutamine, proline, arginine. Earliest enzymatic catabolic functions were deaminations and transaminations. Later on appeared enzymatic decarboxylations. The consensus tree allows to propose four time spans for catabolism development and corroborates the views of Cordón in 1990 about the evolution of catabolism.     

A Similarity-Based Method for Predicting Enzymatic Functions in Yeast Uncovers a New AMP Hydrolase

Despite decades of research and the availability of the full genomic sequence of the baker’s yeast Saccharomyces cerevisiae, still a large fraction of its genome is not functionally annotated. This hinders our ability to fully understand cellular activity and suggests that many additional processes await discovery. The recent years have shown an explosion of high-quality genomic and structural data from multiple organisms, ranging from bacteria to mammals. New computational methods now allow us to integrate these data and extract meaningful insights into the functional identity of uncharacterized proteins in yeast. Here, we created a database of sensitive sequence similarity predictions for all yeast proteins. We use this information to identify candidate enzymes for known biochemical reactions whose enzymes are unidentified, and show how this provides a powerful basis for experimental validation. Using one pathway as a test case we pair a new function for the previously uncharacterized enzyme Yhr202w, as an extra-cellular AMP hydrolase in the NAD degradation pathway. Yhr202w, which we now term Smn1 for Scavenger MonoNucleotidase 1, is a highly conserved protein that is similar to the human protein E5NT/CD73, which is associated with multiple cancers. Hence, our new methodology provides a paradigm, that can be adopted to other organisms, for uncovering new enzymatic functions of uncharacterized proteins.     

Thiamine in plants: Aspects of its metabolism and functions

Thiamine diphosphate (vitamin B₁) plays a fundamental role as an enzymatic cofactor in universal metabolic pathways including glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle. In addition, thiamine diphosphate has recently been shown to have functions other than as a cofactor in response to abiotic and biotic stress in plants. Recently, several steps of the plant thiamine biosynthetic pathway have been characterized, and a mechanism of feedback regulation of thiamine biosynthesis via riboswitch has been unraveled. This review focuses on these most recent advances made in our understanding of thiamine metabolism and functions in plants. Phenotypes of plant mutants affected in thiamine biosynthesis are described, and genomics, proteomics, and metabolomics data that have increased further our knowledge of plant thiamine metabolic pathways and functions are summarized. Aspects of thiamine metabolism such as catabolism, salvage, and transport in plants are discussed.     

Quantitation of wall teichoic acid in Staphylococcus aureus by direct measurement of monomeric units using LC-MS/MS

The emergence of methicillin-resistant Staphylococcus aureus (MRSA) has created an urgent need for new therapeutic agents capable of combating this threat. We have previously reported on the discovery of novel inhibitors targeting enzymes involved in the biosynthesis of wall teichoic acid (WTA) and demonstrated that these agents can restore β-lactam efficacy against MRSA. In those previous reports pathway engagement of inhibitors was demonstrated by reduction in WTA levels measured by polyacrylamide gel electrophoresis. To enable a more rigorous analysis of these inhibitors we sought to develop a quantitative method for measuring whole-cell reductions in WTA. Herein we describe a robust methodology for hydrolyzing polymeric WTA to the monomeric component ribitol-N-acetylglucosamine coupled with measurement by LC-MS/MS. Critical elements of the protocol were found to include the time and temperature of hydrofluoric acid-mediated hydrolysis of polymeric WTA and optimization of these parameters is fully described. Most significantly, the assay enabled accurate and reproducible measurement of depletion EC_50s for tunicamycin and representatives from the novel class of TarO inhibitors, the tarocins. The method described can readily be adapted to quantifying levels of WTA in tissue homogenates from a murine model of infection, highlighting the applicability for both in vitro and in vivo characterizations.     

Characterization and multi-step transketolase-ω-transaminase bioconversions in an immobilized enzyme microreactor (IEMR) with packed tube

The concept of de novo metabolic engineering through novel synthetic pathways offers new directions for multi-step enzymatic synthesis of complex molecules. This has been complemented by recent progress in performing enzymatic reactions using immobilized enzyme microreactors (IEMR). This work is concerned with the construction of de novo designed enzyme pathways in a microreactor synthesizing chiral molecules. An interesting compound, commonly used as the building block in several pharmaceutical syntheses, is a single diastereoisomer of 2-amino-1,3,4-butanetriol (ABT). This chiral amino alcohol can be synthesized from simple achiral substrates using two enzymes, transketolase (TK) and transaminase (TAm). Here we describe the development of an IEMR using His₆-tagged TK and TAm immobilized onto Ni-NTA agarose beads and packed into tubes to enable multi-step enzyme reactions. The kinetic parameters of both enzymes were first determined using single IEMRs evaluated by a kinetic model developed for packed bed reactors. The K_m(app) for both enzymes appeared to be flow rate dependent, while the turnover number k_cat was reduced 3 fold compared to solution-phase TK and TAm reactions. For the multi-step enzyme reaction, single IEMRs were cascaded in series, whereby the first enzyme, TK, catalyzed a model reaction of lithium-hydroxypyruvate (HPA) and glycolaldehyde (GA) to l-erythrulose (ERY), and the second unit of the IEMR with immobilized TAm converted ERY into ABT using (S)-α-methylbenzylamine (MBA) as amine donor. With initial 60 mM (HPA and GA each) and 6 mM (MBA) substrate concentration mixture, the coupled reaction reached approximately 83% conversion in 20 min at the lowest flow rate. The ability to synthesize a chiral pharmaceutical intermediate, ABT in relatively short time proves this IEMR system as a powerful tool for construction and evaluation of de novo pathways as well as for determination of enzyme kinetics.