Structural and biochemical characterization of a trapped coenzyme A adduct of Caenorhabditis elegans glucosamine-6-phosphate N-acetyltransferase 1

Eliminating host-guest incompatibility via enzyme mining enables the high-temperature production of N-acetylglucosamine

The host-guest incompatibility between a production host and non-native enzymes has posed an arduous challenge for synthetic biology, particularly between mesophile-derived enzymes and a thermophilic chassis. In the present study, we develop a thermophilic enzyme mining strategy comprising an automated co-evolution-based screening pipeline (http://cem.sjtu.edu.cn), computation-based enzyme characterization, and gene synthesis-based function validation. Using glucosamine-6-phosphate acetyltransferase (GNA1) as an example, we successfully mined four novel GNA1s with excellent thermostabilities and catalytic performances. Calculation and analysis based on AlphaFold2-generated structures were also conducted to uncover the mechanism underlying their excellent properties. Finally, our mined GNA1s were used to enable the high-temperature N-acetylglucosamine (GlcNAc) production with high titers of up to 119.3 g/L, with the aid of systems metabolic engineering and temperature programming. This study demonstrates the effectiveness of the enzyme mining strategy, highlighting the application prospects of mining new enzymes from massive databases and providing an effective solution for tackling host-guest incompatibility.

Metabolic engineering of Corynebacterium glutamicum S9114 based on whole-genome sequencing for efficient N-acetylglucosamine synthesis

Glucosamine (GlcN) and its acetylated derivative N-acetylglucosamine (GlcNAc) are widely used in the pharmaceutical industries. Here, we attempted to achieve efficient production of GlcNAc via genomic engineering of Corynebacterium glutamicum. Specifically, we ligated the GNA1 gene, which converts GlcN-6-phosphate to GlcNAc-6-phosphate by transferring the acetyl group in Acetyl-CoA to the amino group of GlcN-6-phosphate, into the plasmid pJYW4 and then transformed this recombinant vector into the C. glutamicum ATCC 13032, ATCC 13869, ATCC 14067, and S9114 strains, and we assessed the GlcNAc titers at 0.5 g/L, 1.2 g/L, 0.8 g/L, and 3.1 g/L from each strain, respectively. This suggested that there were likely to be significant differences among the key genes in the glutamate and GlcNAc synthesis pathways of these C. glutamicum strains. Therefore, we performed whole genome sequencing of the S9114 strain, which has not been previously published, and found that there are many differences among the genes in the glutamate and GlcNAc synthesis pathways among the four strains tested. Next, nagA (encoding GlcNAc-6-phosphate deacetylase) and gamA (encoding GlcN-6-phosphate deaminase) were deleted in C. glutamicum S9114 to block the catabolism of intracellular GlcNAc, leading to a 54.8% increase in GlcNAc production (from 3.1 to 4.8 g/L) when grown in a shaker flask. In addition, lactate synthesis was blocked by knockout of ldh (encoding lactate dehydrogenase); thus, further increasing the GlcNAc titer to 5.4 g/L. Finally, we added a key gene of the GlcN synthetic pathway, glmS, from different sources into the expression vector pJYW-4-ceN, and the resulting recombinant strain CGGN2-GNA1-CgglmS produced the GlcNAc titer of 6.9 g/L. This is the first report concerning the metabolic engineering of C. glutamicum, and the results of this study provide a good starting point for further metabolic engineering to achieve industrial-scale production of GlcNAc.

Combinatorial pathway enzyme engineering and host engineering overcomes pyruvate overflow and enhances overproduction of N-acetylglucosamine in Bacillus subtilis

BACKGROUND

Glucosamine-6-phosphate N-acetyltransferase (GNA1) is the key enzyme that causes overproduction of N-acetylglucosamine in Bacillus subtilis. Previously, we increased GlcNAc production by promoting the expression of GNA1 from Caenorhabditis elegans (CeGNA1) in an engineered B. subtilis strain BSGN12. In this strain overflow metabolism to by-products acetoin and acetate had been blocked by mutations, however pyruvate accumulated as an overflow metabolite. Although overexpression of CeGNA1 drove carbon flux from pyruvate to the GlcNAc synthesis pathway and decreased pyruvate accumulation, the residual pyruvate reduced the intracellular pH, resulting in inhibited CeGNA1 activity and limited GlcNAc production.

RESULTS

In this study, we attempted to further overcome pyruvate overflow by enzyme engineering and host engineering for enhanced GlcNAc production. To this end, the key enzyme CeGNA1 was evolved through error-prone PCR under pyruvate stress to enhance its catalytic activity. Then, the urease from Bacillus paralicheniformis was expressed intracellularly to neutralize the intracellular pH, making it more robust in growth and more efficient in GlcNAc production. It was found that the activity of mutant CeGNA1 increased by 11.5% at pH 6.5-7.5, with the catalytic efficiency increasing by 27.5% to 1.25 s^-1 µM^-1. Modulated expression of urease increased the intracellular pH from 6.0 to 6.8. The final engineered strain BSGN13 overcame pyruvate overflow, produced 25.6 g/L GlcNAc with a yield of 0.43 g GlcNAc/g glucose in a shake flask fermentation and produced 82.5 g/L GlcNAc with a yield of 0.39 g GlcNAc/g glucose by fed-batch fermentation, which was 1.7- and 1.2-times, respectively, of the yield achieved previously.

CONCLUSIONS

This study highlights a strategy that combines pathway enzyme engineering and host engineering to resolve overflow metabolism in B. subtilis for the overproduction of GlcNAc. By means of modulated expression of urease reduced pyruvate burden, conferred bacterial survival fitness, and enhanced GlcNAc production, all of which improved our understanding of co-regulation of cell growth and metabolism to construct more efficient B. subtilis cell factories.

Statistical investigations of protein residue direct couplings

Protein Direct Coupling Analysis (DCA), which predicts residue-residue contacts based on covarying positions within a multiple sequence alignment, has been remarkably effective. This suggests that there is more to learn from sequence correlations than is generally assumed, and calls for deeper investigations into DCA and perhaps into other types of correlations. Here we describe an approach that enables such investigations by measuring, as an estimated p-value, the statistical significance of the association between residue-residue covariance and structural interactions, either internal or homodimeric. Its application to thirty protein superfamilies confirms that direct coupling (DC) scores correlate with 3D pairwise contacts with very high significance. This method also permits quantitative assessment of the relative performance of alternative DCA methods, and of the degree to which they detect direct versus indirect couplings. We illustrate its use to assess, for a given protein, the biological relevance of alternative conformational states, to investigate the possible mechanistic implications of differences between these states, and to characterize subtle aspects of direct couplings. Our analysis indicates that direct pairwise correlations may be largely distinct from correlated patterns associated with functional specialization, and that the joint analysis of both types of correlations can yield greater power. Data, programs, and source code are freely available at http://evaldca.igs.umaryland.edu.

Inferring joint sequence-structural determinants of protein functional specificity

Residues responsible for allostery, cooperativity, and other subtle but functionally important interactions remain difficult to detect. To aid such detection, we employ statistical inference based on the assumption that residues distinguishing a protein subgroup from evolutionarily divergent subgroups often constitute an interacting functional network. We identify such networks with the aid of two measures of statistical significance. One measure aids identification of divergent subgroups based on distinguishing residue patterns. For each subgroup, a second measure identifies structural interactions involving pattern residues. Such interactions are derived either from atomic coordinates or from Direct Coupling Analysis scores, used as surrogates for structural distances. Applying this approach to N-acetyltransferases, P-loop GTPases, RNA helicases, synaptojanin-superfamily phosphatases and nucleases, and thymine/uracil DNA glycosylases yielded results congruent with biochemical understanding of these proteins, and also revealed striking sequence-structural features overlooked by other methods. These and similar analyses can aid the design of drugs targeting allosteric sites.

Acetyl group coordinated progression through the catalytic cycle of an arylalkylamine N-acetyltransferase

The transfer of an acetyl group from acetyl-CoA to an acceptor amine is a ubiquitous biochemical transformation catalyzed by Gcn5-related N-acetyltransferases (GNATs). Although it is established that the reaction proceeds through a sequential ordered mechanism, the role of the acetyl group in driving the ordered formation of binary and ternary complexes remains elusive. Herein, we show that CoA and acetyl-CoA alter the conformation of the substrate binding site of an arylalkylamine N-acetyltransferase (AANAT) to facilitate interaction with acceptor substrates. However, it is the presence of the acetyl group within the catalytic funnel that triggers high affinity binding. Acetyl group occupancy is relayed through a conserved salt bridge between the P-loop and the acceptor binding site, and is manifested as differential dynamics in the CoA and acetyl-CoA-bound states. The capacity of the acetyl group carried by an acceptor to promote its tight binding even in the absence of CoA, but also its mutually exclusive position to the acetyl group of acetyl-CoA underscore its importance in coordinating the progression of the catalytic cycle.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes’ theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Protein sequence data, when gathered in great quantity, contain important but implicit biological information manifest as statistical correlations. Here we describe an approach to access this information by comprehensively modeling and characterizing the distribution of sequences belonging to a major protein superfamily. This approach takes as input a large set of unaligned sequences belonging to the superfamily. By applying the minimum description length principle, it seeks the statistical model that best explains the sequences while avoiding over-fitting the data. It concurrently aligns the sequences and, to model evolutionary divergence, partitions them into subgroups that are hierarchically-arranged based upon correlated residue patterns. Auxiliary routines create PyMOL scripts to visualize the locations of correlated residues within available structures. Because these correlations likely arise from structural and biochemical constraints, they can help elucidate protein properties important for functional specificity. Comparing and contrasting sequence and structural features in this way may therefore suggest, in the light of published studies, plausible biological hypotheses for experimental investigation. We illustrate this approach with N-acetyltransferases.

Structure and Functional Diversity of GCN5-Related N-Acetyltransferases (GNAT)

General control non-repressible 5 (GCN5)-related N-acetyltransferases (GNAT) catalyze the transfer of an acyl moiety from acyl coenzyme A (acyl-CoA) to a diverse group of substrates and are widely distributed in all domains of life. This review of the currently available data acquired on GNAT enzymes by a combination of structural, mutagenesis and kinetic methods summarizes the key similarities and differences between several distinctly different families within the GNAT superfamily, with an emphasis on the mechanistic insights obtained from the analysis of the complexes with substrates or inhibitors. It discusses the structural basis for the common acetyltransferase mechanism, outlines the factors important for the substrate recognition, and describes the mechanism of action of inhibitors of these enzymes. It is anticipated that understanding of the structural basis behind the reaction and substrate specificity of the enzymes from this superfamily can be exploited in the development of novel therapeutics to treat human diseases and combat emerging multidrug-resistant microbial infections.

Gleaning structural and functional information from correlations in protein multiple sequence alignments

The availability of vast amounts of protein sequence data facilitates detection of subtle statistical correlations due to imposed structural and functional constraints. Recent breakthroughs using Direct Coupling Analysis (DCA) and related approaches have tapped into correlations believed to be due to compensatory mutations. This has yielded some remarkable results, including substantially improved prediction of protein intra- and inter-domain 3D contacts, of membrane and globular protein structures, of substrate binding sites, and of protein conformational heterogeneity. A complementary approach is Bayesian Partitioning with Pattern Selection (BPPS), which partitions related proteins into hierarchically-arranged subgroups based on correlated residue patterns. These correlated patterns are presumably due to structural and functional constraints associated with evolutionary divergence rather than to compensatory mutations. Hence joint application of DCA- and BPPS-based approaches should help sort out the structural and functional constraints contributing to sequence correlations.

Human acetyl-CoA:glucosamine-6-phosphate N-acetyltransferase 1 has a relaxed donor specificity and transfers acyl groups up to four carbons in length

Glucosamine-6-phosphate N-acetyltransferase1 (GNA1) catalyses the transfer of an acetyl group from acetyl coenzyme A (AcCoA) to glucosamine-6-phosphate (GlcN6P) to form N-acetylglucosamine-6-phosphate (GlcNAc6P), which is an essential intermediate in UDP-GlcNAc biosynthesis. An analog of GlcNAc, N-butyrylglucosamine (GlcNBu) has shown healing properties for bone and articular cartilage in animal models of arthritis. The goal of this work was to examine whether GNA1 has the ability to transfer a butyryl group from butyryl-CoA to GlcN6P to form GlcNBu6P, which can then be converted to GlcNBu. We developed fluorescent and radioactive assays and examined the donor specificity of human GNA1. Acetyl, propionyl, n-butyryl, and isobutyryl groups were all transferred to GlcN6P, but isovaleryl-CoA and decanoyl-CoA did not serve as donor substrates. Site-specific mutants were produced to examine the role of amino acids potentially affecting the size and properties of the AcCoA binding pocket. All of the wild type and mutant enzymes showed activities of both acetyl and butyryl transfer and can therefore be used for the enzymatic synthesis of GlcNBu for biomedical applications.

Structural basis of cofactor-mediated stabilization and substrate recognition of the α-tubulin acetyltransferase αTAT1

The functions of microtubules are controlled in part by tubulin post-translational modification including acetylation of Lys⁴⁰ in α-tubulin. αTAT1 (α-tubulin acetyltransferase 1), an enzyme evolutionarily conserved among eukaryotes, has recently been identified as the major α-tubulin Lys⁴⁰ acetyltransferase, in which AcCoA (acetyl-CoA) serves as an acetyl group donor. The regulation and substrate recognition of this enzyme, however, have not been fully understood. In the present study, we show that AcCoA and CoA each form a stable complex with human αTAT1 to maintain the protein integrity both in vivo and in vitro. The invariant residues Arg¹³² and Ser¹⁶⁰ in αTAT1 participate in the stable interaction not only with AcCoA but also with CoA, which is supported by analysis of the present crystal structures of the αTAT1 catalytic domain in complex with CoA. Alanine substitution for Arg¹³² or Ser¹⁶⁰ leads to a drastic misfolding of the isolated αTAT1 catalytic domain in the absence of CoA and AcCoA but not in the presence of excess amounts of either cofactor. A mutant αTAT1 carrying the R132A or S160A substitution is degraded much faster than the wild-type protein when expressed in mammalian Madin-Darby canine kidney cells. Furthermore, alanine-scanning experiments using Lys⁴⁰-containing peptides reveal that α-tubulin Ser³⁸ is crucial for substrate recognition of αTAT1, whereas Asp³⁹, Ile⁴², the glycine stretch (amino acid residues 43-45) and Asp⁴⁶ are also involved. The requirement for substrate selection is totally different from that in various histone acetyltransferases, which appears to be consistent with the inability of αTAT1 to acetylate histones.

Structural insights into WcbI, a novel polysaccharide-biosynthesis enzyme

Capsular polysaccharides (CPSs) are protective structures on the surfaces of many Gram-negative bacteria. The principal CPS of the human pathogen and Tier 1 select agent Burkholderia pseudomallei consists of a linear repeat of --3)--2-O-acetyl-6-deoxy-β-d-manno-heptopyranose-(1-. This CPS is critical to the virulence of this emerging pathogen and represents a key target for the development of novel therapeutics. wcbI is one of several genes in the CPS biosynthetic cluster whose deletion leads to significant attenuation of the pathogen; unlike most others, it has no homologues of known function and no detectable sequence similarity to any protein with an extant structure. Here, the crystal structure of WcbI bound to its proposed product, coenzyme A, is reported at 1.38 Å resolution, solved using the halide-soak method with multiple anomalous dispersion. This structure reveals that WcbI incorporates a previously described 100-amino-acid subdomain into a novel, principally helical fold (310 amino acids). This fold adopts a cradle-like structure, with a deep binding pocket for CoA in the loop-rich cradle. Structural analysis and biophysical assays suggest that WcbI functions as an acetyltransferase enzyme, whilst biochemical tests suggest that another functional module might be required to assist its activity in forming the mature B. pseudomallei capsule.