Discovery of a Biotin Synthase That Utilizes an Auxiliary 4Fe-5S Cluster for Sulfur Insertion.

Biotin synthase (BioB) is a member of the Radical SAM superfamily of enzymes that catalyzes the terminal step of biotin (vitamin B7) biosynthesis, in which it inserts a sulfur atom in desthiobiotin to form a thiolane ring. How BioB accomplishes this difficult reaction has been the subject of much controversy, mainly around the source of the sulfur atom. However, it is now widely accepted that the sulfur atom inserted to form biotin stems from the sacrifice of the auxiliary 2Fe-2S cluster of BioB. Here, we bioinformatically explore the diversity of BioBs available in sequence databases and find an unexpected variation in the coordination of the auxiliary iron-sulfur cluster. After in vitro characterization, including the determination of biotin formation and representative crystal structures, we report a new type of BioB utilized by virtually all obligate anaerobic organisms. Instead of a 2Fe-2S cluster, this novel type of BioB utilizes an auxiliary 4Fe-5S cluster. Interestingly, this auxiliary 4Fe-5S cluster contains a ligated sulfide that we propose is used for biotin formation. We have termed this novel type of BioB, Type II BioB, with the E. coli 2Fe-2S cluster sacrificial BioB representing Type I. This surprisingly ubiquitous Type II BioB has implications for our understanding of the function and evolution of Fe-S clusters in enzyme catalysis, highlighting the difference in strategies between the anaerobic and aerobic world.

How many Mutations are needed to Evolve the Chemical Makeup of a Synthetic Cell?

The chemical evolution of a synthetic cell endowed with a synthetic amino acid as building block, analog to tryptophan, required the emergence of key mutations in genes involved in, inter alia, the general stress response, amino acid metabolism, stringent response, and chemotaxis. Understanding adaptation mechanisms to non-canonical biomass components will inform strategies for engineering synthetic metabolic pathways and cells.

Metabolic engineering of Escherichia coli for high-level production of free lipoic acid.

L-Lipoic acid (LA) is an important antioxidant with various industrial applications as a nutraceutical and therapeutic. Currently, LA is produced by chemical synthesis. Cell factory development is complex as LA and its direct precursors only occur naturally in protein-bound forms. Here we report a rationally engineered LA cell factory and demonstrate de novo free LA production from glucose for the first time in E. coli. The pathway represents a significant challenge as the three key enzymes, native Octanoyltransferase (LipB) and Lipoyl Synthase (LipA), and heterologous Lipoamidase (LpA), are all toxic to overexpress in E. coli. To overcome the toxicity of LipB, functional metagenomic selection was used to identify a highly active and non-toxic LipB and LipA from S. liquefaciens. Using high throughput screening, we balanced translation initiation rates and dual, orthogonal induction systems for the toxic genes, LipA and LpA. The optimized strain yielded 2.5 mg free LA per gram of glucose in minimal media, expressing carefully balanced LipB and LipA, Enterococcus faecalis LpA, and a truncated, native, Dihydrolipoyllysine-residue acetyltransferase (AceF) lipoylation domain. When the optimized cell factory strain was cultivated in a fed-batch fermentation, a titer of 87 mg/L free LA in the supernatant was reached after 48 h. This titer is ∼3000-fold higher than previously reported free LA titer and ∼8-fold higher than the previous best total, protein-bound LA titer. The strategies presented here could be helpful in designing, constructing and balancing biosynthetic pathways that harbor toxic enzymes with protein-bound intermediates or products.

The Crucial Role of Methodology Development in Directed Evolution of Selective Enzymes.

Directed evolution of stereo-, regio-, and chemoselective enzymes constitutes a unique way to generate biocatalysts for synthetically interesting transformations in organic chemistry and biotechnology. In order for this protein engineering technique to be efficient, fast, and reliable, and also of relevance to synthetic organic chemistry, methodology development was and still is necessary. Following a description of early key contributions, this review focuses on recent developments. It includes optimization of molecular biological methods for gene mutagenesis and the design of efficient strategies for their application, resulting in notable reduction of the screening effort (bottleneck of directed evolution). When aiming for laboratory evolution of selectivity and activity, second-generation versions of Combinatorial Active-Site Saturation Test (CAST) and Iterative Saturation Mutagenesis (ISM), both involving saturation mutagenesis (SM) at sites lining the binding pocket, have emerged as preferred approaches, aided by in silico methods such as machine learning. The recently proposed Focused Rational Iterative Site-specific Mutagenesis (FRISM) constitutes a fusion of rational design and directed evolution. On-chip solid-phase chemical gene synthesis for rapid library construction enhances library quality notably by eliminating undesired amino acid bias, the future of directed evolution?

Regio- and Stereoselective Steroid Hydroxylation at C7 by Cytochrome†P450 Monooxygenase Mutants.

Steroidal C7ß alcohols and their respective esters have shown significant promise as neuroprotective and anti-inflammatory agents to treat chronic neuronal damage like stroke, brain trauma, and cerebral ischemia. Since C7 is spatially far away from any functional groups that could direct C-H activation, these transformations are not readily accessible using modern synthetic organic techniques. Reported here are P450-BM3 mutants that catalyze the oxidative hydroxylation of six different steroids with pronounced C7 regioselectivities and ß stereoselectivities, as well as high activities. These challenging transformations were achieved by a focused mutagenesis strategy and application of a novel technology for protein library construction based on DNA assembly and USER (Uracil-Specific Excision Reagent) cloning. Upscaling reactions enabled the purification of the respective steroidal alcohols in moderate to excellent yields. The high-resolution X-ray structure and molecular dynamics simulations of the best mutant unveil the origin of regio- and stereoselectivity.

tRNA Modification Profiles and Codon-Decoding Strategies in Methanocaldococcus jannaschii.

tRNAs play a critical role in mRNA decoding, and posttranscriptional modifications within tRNAs drive decoding efficiency and accuracy. The types and positions of tRNA modifications in model bacteria have been extensively studied, and tRNA modifications in a few eukaryotic organisms have also been characterized and localized to particular tRNA sequences. However, far less is known regarding tRNA modifications in archaea. While the identities of modifications have been determined for multiple archaeal organisms, Haloferax volcanii is the only organism for which modifications have been extensively localized to specific tRNA sequences. To improve our understanding of archaeal tRNA modification patterns and codon-decoding strategies, we have used liquid chromatography and tandem mass spectrometry to characterize and then map posttranscriptional modifications on 34 of the 35 unique tRNA sequences of Methanocaldococcus jannaschii A new posttranscriptionally modified nucleoside, 5-cyanomethyl-2-thiouridine (cnm5s2U), was discovered and localized to position 34. Moreover, data consistent with wyosine pathway modifications were obtained beyond the canonical tRNAPhe as is typical for eukaryotes. The high-quality mapping of tRNA anticodon loops enriches our understanding of archaeal tRNA modification profiles and decoding strategies.IMPORTANCE While many posttranscriptional modifications in M. jannaschii tRNAs are also found in bacteria and eukaryotes, several that are unique to archaea were identified. By RNA modification mapping, the modification profiles of M. jannaschii tRNA anticodon loops were characterized, allowing a comparative analysis with H. volcanii modification profiles as well as a general comparison with bacterial and eukaryotic decoding strategies. This general comparison reveals that M. jannaschii, like H. volcanii, follows codon-decoding strategies similar to those used by bacteria, although position 37 appears to be modified to a greater extent than seen in H. volcanii.

Site-Resolved Observation of Vibrational Energy Transfer Using a Genetically Encoded Ultrafast Heater.

Allosteric information transfer in proteins has been linked to distinct vibrational energy transfer (VET) pathways in a number of theoretical studies. Experimental evidence for such pathways, however, is sparse because site-selective injection of vibrational energy into a protein, that is, localized heating, is required for their investigation. Here, we solved this problem by the site-specific incorporation of the non-canonical amino acid ß-(1-azulenyl)-l-alanine (AzAla) through genetic code expansion. As an exception to Kasha's rule, AzAla undergoes ultrafast internal conversion and heating after S1 excitation while upon S2 excitation, it serves as a fluorescent label. We equipped PDZ3, a protein interaction domain of postsynaptic density protein 95, with this ultrafast heater at two distinct positions. We indeed observed VET from the incorporation sites in the protein to a bound peptide ligand on the picosecond timescale by ultrafast IR spectroscopy. This approach based on genetically encoded AzAla paves the way for detailed studies of VET and its role in a wide range of proteins.

Clarifying the Difference between Iterative Saturation Mutagenesis as a Rational Guide in Directed Evolution and OmniChange as a Gene Mutagenesis Technique.

A recent directed-evolution study by Schwaneberg and co-workers comparing the widely used iterative saturation mutagenesis (ISM) with the OmniChange version of saturation mutagenesis (SM) prompts us to point out some flaws in the conclusions presented therein. Most importantly, ISM is a semirational strategy in directed evolution that is independent of the particular type of SM that the experimenter may choose; this means that OmniChange should not be compared with ISM. When aiming to improve enzyme selectivity or activity by the ISM strategy, the state-of-the-art calls for SM at randomization sites lining the enzyme binding pocket as part of the combinatorial active-site saturation test (CAST). Our recent studies focusing on the refinement of CAST/ISM have shown that this approach works best when using multiresidue randomization sites as opposed to single-residue sites owing to the possibility of cooperative mutational effects. This advance was not considered by Schwaneberg and co-workers, thus leading to questionable conclusions when pitching CAST/ISM against OmniChange.

Beating Bias in the Directed Evolution of Proteins: Combining High-Fidelity on-Chip Solid-Phase Gene Synthesis with Efficient Gene Assembly for Combinatorial Library Construction.

Saturation mutagenesis (SM) constitutes a widely used technique in the directed evolution of selective enzymes as catalysts in organic chemistry and in the manipulation of metabolic paths and genomes, but the quality of the libraries is far from optimal due to the inherent amino acid bias. Herein, it is shown how this fundamental problem can be solved by applying high-fidelity solid-phase chemical gene synthesis on silicon chips followed by efficient gene assembly. Limonene epoxide hydrolase was chosen as the catalyst in the model desymmetrization of cyclohexene oxide with the stereoselective formation of (R,R)- and (S,S)-cyclohexane-1,2-diol. A traditional combinatorial PCR-based SM library, produced by simultaneous randomization at several residues by using a reduced amino acid alphabet, and the respective synthetic library were constructed and compared. Statistical analysis at the DNA level with massive sequencing demonstrates that, in the synthetic approach, 97 % of the theoretically possible DNA mutants are formed, whereas the traditional SM library contained only about 50 %. Screening at the protein level also showed the superiority of the synthetic library; many highly (R,R)- and (S,S)-selective variants being discovered are not found in the traditional SM library. With the prices of synthetic genes decreasing, this approach may point the way to future directed evolution.

Boosting the efficiency of site-saturation mutagenesis for a difficult-to-randomize gene by a two-step PCR strategy.

Site-saturation mutagenesis (SSM) has been used in directed evolution of proteins for a long time. As a special form of saturation mutagenesis, it involves individual randomization at a given residue with formation of all 19 amino acids. To date, the most efficient embodiment of SSM is a one-step PCR-based approach using NNK codon degeneracy. However, in the case of difficult-to-randomize genes, SSM may not deliver all of the expected 19 mutants, which compels the user to invest further efforts by applying site-directed mutagenesis for the construction of the missing mutants. To solve this problem, we developed a two-step PCR-based technique in which a mutagenic primer and a non-mutagenic (silent) primer are used to generate a short DNA fragment, which is recovered and then employed as a megaprimer to amplify the whole plasmid. The present two-step and older one-step (partially overlapped primer approach) procedures were compared by utilizing cytochrome P450-BM3, which is a "difficult-to-randomize" gene. The results document the distinct superiority of the new method by checking the library quality on DNA level based on massive sequence data, but also at amino acid level. Various future applications in biotechnology can be expected, including the utilization when constructing mutability landscapes, which provide semi-rational information for identifying hot spots for protein engineering and directed evolution.

Biocatalysis with Unnatural Amino Acids: Enzymology Meets Xenobiology.

The goal of xenobiology is to design biological systems endowed with unusual biochemical functions, whereas enzymology concerns the study of enzymes, the workhorses of biocatalysis. Biocatalysis employs enzymes and organisms to perform useful biotransformations in synthetic chemistry and biotechnology. During the past few years, the effects of incorporating noncanonical amino acids (ncAAs) into enzymes with potential applications in biocatalysis have been increasingly investigated. In this Review, we provide an overview of the effects of new chemical functionalities that have been introduced into proteins to improve various facets of enzymatic catalysis. We also discuss future research avenues that will complement unnatural mutagenesis with standard protein engineering to produce novel and versatile biocatalysts with applications in synthetic organic chemistry and biotechnology.

Analysis of Enantioselective Biotransformations Using a Few Hundred Cells on an Integrated Microfluidic Chip.

The investigation of stereoselective biocatalytic transformations at a single-cell level is to date an unsolved challenge. Here, we report the development of an integrated microfluidic device which enables the analytical characterization of enantioselective reactions at nanoliter scale by combining whole-cell catalyzed on-chip syntheses, chiral microchip electrophoresis, and label-free detection of enantiomers by deep UV time-resolved fluorescence. Using Escherichia coli expressing recombinant Aspergillus niger epoxide hydrolase as the model enzyme for various enantioselective reactions, we evaluated the approach for downscaling the reaction to a few hundred cells. Our work is thus an important step toward the analysis of single-cell stereoselective biocatalysis.

From essential to persistent genes: a functional approach to constructing synthetic life.

A central undertaking in synthetic biology (SB) is the quest for the 'minimal genome'. However, 'minimal sets' of essential genes are strongly context-dependent and, in all prokaryotic genomes sequenced to date, not a single protein-coding gene is entirely conserved. Furthermore, a lack of consensus in the field as to what attributes make a gene truly essential adds another aspect of variation. Thus, a universal minimal genome remains elusive. Here, as an alternative to defining a minimal genome, we propose that the concept of gene persistence can be used to classify genes needed for robust long-term survival. Persistent genes, although not ubiquitous, are conserved in a majority of genomes, tend to be expressed at high levels, and are frequently located on the leading DNA strand. These criteria impose constraints on genome organization, and these are important considerations for engineering cells and for creating cellular life-like forms in SB.

How Many Biochemistries Are Available To Build a Cell?

The manual experimental evolution of the bacterium Escherichia coli allowed the design of a noncanonical genetic code in which complete replacement of the endogenous building block tryptophan (left) by an exogenous one based on a thienylpyrrole (right) was achieved after 506 days of continuous culturing.

Hijacking nature--new approaches to unravel enzyme mechanisms and engineer improved biocatalysts.

The second EMBO conference on 'Catalytic Mechanisms by Biological Systems' took place in Groningen, the Netherlands, in October 2012. Structural, molecular and computational biologists, as well as chemists, biophysicists and engineers discussed technologies to improve our mechanistic understanding of enzymes, as well as the design of robust biocatalysts.

Bioorthogonal Enzymatic Activation of Caged Compounds.

Engineered cytochrome P450 monooxygenase variants are reported as highly active and selective catalysts for the bioorthogonal uncaging of propargylic and benzylic ether protected substrates, including uncaging in living E. coli. observed selectivity is supported by induced-fit docking and molecular dynamics simulations. This proof-of-principle study points towards the utility of bioorthogonal enzyme/protecting group pairs for applications in the life sciences.

Combining enzyme and metabolic engineering for microbial supply of therapeutic phytochemicals.

The history of pharmacology is deeply intertwined with plant-derived compounds, which continue to be crucial in drug development. However, their complex structures and limited availability in plants challenge drug discovery, optimization, development, and industrial production via chemical synthesis or natural extraction. This review delves into the integration of metabolic and enzyme engineering to leverage micro-organisms as platforms for the sustainable and reliable production of therapeutic phytochemicals. We argue that engineered microbes can serve a triple role in this paradigm: facilitating pathway discovery, acting as cell factories for scalable manufacturing, and functioning as platforms for chemical derivatization. Analyzing recent progress and outlining future directions, the review highlights microbial biotechnology's transformative potential in expanding plant-derived human therapeutics' discovery and supply chains.

Protein engineering using mutability landscapes: Controlling site-selectivity of P450-catalyzed steroid hydroxylation.

Directed evolution and rational design have been used widely in engineering enzymes for their application in synthetic organic chemistry and biotechnology. With stereoselectivity playing a crucial role in catalysis for the synthesis of valuable chemical and pharmaceutical compounds, rational design has not achieved such wide success in this specific area compared to directed evolution. Nevertheless, one bottleneck of directed evolution is the laborious screening efforts and the observed trade-offs in catalytic profiles. This has motivated researchers to develop more efficient protein engineering methods. As a prime approach, mutability landscaping avoids such trade-offs by providing more information of sequence-function relationships. Here, we describe an application of this efficient protein engineering method to improve the regio-/stereoselectivity and activity of P450BM3 for steroid hydroxylation, while keeping the mutagenesis libraries small so that they will require only minimal screening.

Learning Strategies in Protein Directed Evolution.

Synthetic biology is a fast-evolving research field that combines biology and engineering principles to develop new biological systems for medical, pharmacological, and industrial applications. Synthetic biologists use iterative "design, build, test, and learn" cycles to efficiently engineer genetic systems that are reliable, reproducible, and predictable. Protein engineering by directed evolution can benefit from such a systematic engineering approach for various reasons. Learning can be carried out before starting, throughout or after finalizing a directed evolution project. Computational tools, bioinformatics, and scanning mutagenesis methods can be excellent starting points, while molecular dynamics simulations and other strategies can guide engineering efforts. Similarly, studying protein intermediates along evolutionary pathways offers fascinating insights into the molecular mechanisms shaped by evolution. The learning step of the cycle is not only crucial for proteins or enzymes that are not suitable for high-throughput screening or selection systems, but it is also valuable for any platform that can generate a large amount of data that can be aided by machine learning algorithms. The main challenge in protein engineering is to predict the effect of a single mutation on one functional parameter-to say nothing of several mutations on multiple parameters. This is largely due to nonadditive mutational interactions, known as epistatic effects-beneficial mutations present in a genetic background may not be beneficial in another genetic background. In this work, we provide an overview of experimental and computational strategies that can guide the user to learn protein function at different stages in a directed evolution project. We also discuss how epistatic effects can influence the success of directed evolution projects. Since machine learning is gaining momentum in protein engineering and the field is becoming more interdisciplinary thanks to collaboration between mathematicians, computational scientists, engineers, molecular biologists, and chemists, we provide a general workflow that familiarizes nonexperts with the basic concepts, dataset requirements, learning approaches, model capabilities and performance metrics of this intriguing area. Finally, we also provide some practical recommendations on how machine learning can harness epistatic effects for engineering proteins in an "outside-the-box" way.