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Omega transaminases: discovery, characterization and engineering Palacio, Cyntia Marcela

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Download date: 01-10-2021 Omega transaminases: discovery, characterization and engineering

Cyntia Marcela Palacio

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ISBN (printed version): 978-94-034-1559-8 ISBN (electronic version): 978-94-034-1558-1

The research described in this thesis was carried out in the ‘Groningen Biotechnology and Bimolecular Science Institute’ of the University of Groningen and was financially supported by EuroTANGO II (Project funded by the European Commission), by BIONEXGEN FP7, and by the BE-Basic Foundation.

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The research reported in this dissertation was financially supportedE\WKH1DWLRQDOΖQVWLWXWHIRU 3XEOLF+HDOWKDQGWKH(QYLURQPHQW 5Ζ90, SPR program Health Economics) and Tilburg University.

&RYHUGHVLJQE\Douwe Oppewal /D\RXWDQGGHVLJQE\Douwe Oppewal 3ULQWHGE\ΖSVNDPS3ULQWLQJ Omega transaminases: discovery, characterization and engineering

PhD thesis

to obtain the degree of PhD at the University of Groningen on the authority of the Rector Magnificus Prof. E. Sterken and in accordance with the decision by the College of Deans.

This thesis will be defended in public on

Friday 26 April 2019 at 12.45 hours

by

Cyntia Marcela Palacio

born on 11 August 1987 in Buenos Aires, Argentina

3 Supervisor Prof. D.B. Janssen

Assessment committee Prof. P. Berglund Prof. D.J. Slotboom Prof. G.J.W. Euverink

4 TABLE OF CONTENTS

Chapter 1: Introduction 7

Chapter 2: Characterization of the caprolactam degradation 39 pathway in Pseudomonas jessenii using mass spectrometry-based proteomics

Chapter 3: Biochemical properties of a Pseudomonas 63 aminotransferase involved in caprolactam metabolism

Chapter 4: Enhancing thermal stability of Pseudomonas jessenii 87 transaminase by computational library design

Chapter 5: Enzymatic network for production of ether amines 113 from alcohols

Chapter 6: Summary and perspectives 133

Chapter 7: Samenvatting en perspectief 145

Acknowledgements 157

5 1Introduction

Cyntia M. Palacio, Dick B. Jansen

7 8 INTRODUCTION

PLP-DEPENDENT ENZYMES Pyridoxal-5’-phosphate (PLP) is the biologically active phosphorylated derivative of 1 pyridoxine, also called vitamin B6 (Scheme 1). It occurs as cofactor in many biochemical reactions, especially in the metabolism of amino acids. In PLP-dependent enzymes, the cofactor is covalently bound through formation of a Schiff base linkage between its reactive aldehyde group and the ε-amino group of an active site lysine, which is topologically conserved within homologous PLP enzymes. An essential catalytic feature of PLP enzymes is imine exchange with the amino group of a substrate replacing the lysine ε-amino in the Schiff base linkage. This allows delocalization of negative charge during subsequent reactions of the PLP-bound substrate moiety. This reaction may be proton abstraction, decarboxylation, or an elimination reaction at the Cα, Cβ or Cγ of the substrate, Cα being the carbon atom carrying the amine group that is coupled to PLP (1, 2). After this, different reprotonation and addition reactions may occur and finally the Schiff base linkage is hydrolyzed or cleaved by imine exchange to release product. Accordingly, enzymes that use PLP as cofactor catalyze a wide variety of conversions including transamination, decarboxylation, β- and γ-elimination, aldol cleavage and racemization (3, 4). This diversity of functions seems to have emergenced early in evolution (1). PLP-dependent enzymes have been classified by reaction type, substrate range, sequence similarity, and by structural features. The widely used EC classification system groups them by reaction and substrate type. However, this does not correlate well to phylogenetic classification and structural conservation. Based on sequence similarities, Mehta et al. (5) in an early paper about aminotransferase classification proposed to divide aminotransferases in 4 subgroups (AT-I, AT-II, AT-III and AT-IV; we use the prefix AT to avoid confusion with PLP fold type). Papers on aminotransferases still quite often refer to this classification. Alexander et al. (6) grouped PLP-enzymes into α, β, and γ families depending on whether the bond that is formed or cleaved involves a Cα, Cβ or Cγ of the amino acid substrate. Another and more complete classification system suggested by Grishin et al. (4) is based on three dimensional structures and sequence similarities among a large group of PLP enzymes. It classifies them into five fold types (I to V), each encompassing enzymes with diverse catalytic profiles but evolutionary and structurally related. Since sequence homology and structural similarities coincide, the Grishin classification is similar to the one proposed by Jansonius et al. (7), who grouped the enzymes in superfamilies by structural similarities and named the superfamilies after the PLP enzyme of which the crystal structure was determined first. The PLP fold-type classification system of Grishin et al. is now most commonly adopted (1, 8), whereas the numbering in AT subgroups has become confusing (see Schiroli and Peracchi et al. (9), for a detailed explanation). Recently, two more fold types (VI and VII) were mentioned by Peracchi and coworkers (http:// bioinformatics.unipr.it/cgi-bin/bioinformatics/B6db/fold.pl). In the discussion below, we adopt the system of Grishin et al. (4) as also used by Schiroli et al. (9).

9 CHAPTER 1

1

Scheme 1. Pyridoxine and phosphorylated derivatives.

Fold type I PLP enzymes, or the asparate aminotransferase superfamily, encompasses the largest number of biochemically investigated PLP enzymes and the widest variety of activities, including aminotransferases, decarboxylases, and enzymes catalyzing elimination reactions. These are usually dimeric enzymes, with each subunit composed of two domains. The domain organisation and topological position of the PLP group are conserved. In each subunit, an active site with bound PLP is located in a cleft between the two domains (10). Typical conserved motifs along the sequence of these PLP enzymes are a glycine rich loop forming the binding site for the phosphate group of PLP, a conserved aspartate interacting with the pyridoxal nitrogen, and not far from the C-terminus the invariant lysine forming a covalent bond with the PLP (4, 6). The functional diversity included in the fold type I PLP enzymes is larger than that in other fold types discussed below. The old subgroup AT-I (later divided in class I and class II ATs by Grishin et al. (4), AT-II (later called class III aminotransferases (4)), and AT-IV (later class V ATs (4)) distinguished by Mehta et al. (5) all belong to the fold type I PLP enzymes (4). The subgroup AT-I contains the classical aspartate aminotransferase from chicken mitochondria of which several structures have been solved (e.g. pdb 9AAT), providing important mechanistic insight (11), and also alanine-, tyrosine-, histidinol- phosphate-, and phenylalanine/tyrosine aminotransferases (e.g. from E. coli, pdb 3FSL). Subgroup AT-II (class III ATs) includes acetylornithine-, ornithine-, 4‑aminobutyrate- and also succinyldiaminopimelate aminotransferase (12), and the β-amino acid aminotransferases studied earlier in our laboratory (13, 14). These class III enzymes are sometimes called ω-aminotransferases to indicate that they accept amino acids but preferably not α-amino acids. Subgroup AT-IV of the fold type I PLP enzymes includes serine and phosphoserine aminotransferases. Fold type II PLP enzymes include all known members of the β family of PLP enzymes (acting on a bond of the Cβ carbon of the substrate) and is also called the tryptophan synthase β superfamily, after the β subunit of tryptophan synthase, which dehydrates and couples serine with indole in a β-elimination/addition reaction. These enzymes are also homodimers comprised of two domains, but unlike in the PLP fold type I enzymes, the lysine forming the Schiff base with PLP is positioned closer to the N-terminus than to the C-terminus. Furthermore, a serine residue rather than an aspartate interacts with

10 INTRODUCTION the pyridoxal nitrogen of PLP. Besides the enzymes of the β-family, most members of this fold type II act on α-carbon bonds. Examples are O-acetylserine sulfhydrylase 1 (Thermotoga maritima pdb 1O58), threonine deaminase (e.g. from E. coli, pdb 1TDJ), L-serine dehydratase (e.g. Legionella pneumophila, pdb 4RQO), D-serine dehydratase (e.g. E. coli, pdb 3SS7) and cysteine synthase (e.g. Brucella suis, pdb 5I7W). Several racemases and decarboxylases are grouped in the fold type III PLP enzymes, which is also named alanine racemase superfamily (15). Like fold type I and II enzymes, these proteins are homodimers with subunits composed of two domains. However, the structures are clearly different. The lysine forming the Schiff base linkage is situated close to the C-terminus in a loop connecting a strand and a helix, and binding of the pyridine nitrogen is via an arginine residue, indicating that the nitrogen is deprotonated (10). The group of fold type IV PLP enzymes encompasses several aminotransferases with known 3D structure, including the subgroup AT-III aminotransferases of Mehta et al. (5) (called class IV ATs by Grishin et al. (4)) termed D-amino acid aminotransferase (DAAT, pdb 1DAA) (16, 17), 4-amino-4-deoxychorismate lyase (18), and branched-chain amino acid aminotransferase (19). Most of these enzymes are homodimers folded into a two- domain structure, except the branched amino acid aminotransferases which in most cases form hexamers. The active site is shaped by residues from both subunits and a glutamic acid interacts with the nitrogen from the PLP pyridine. Although the fold of these enzymes is completely different from that of other PLP-dependent enzymes, the catalytic site somewhat resembles a mirror image of the active site of the typical PLP fold type I aspartate aminotransferase (10). Glycogen phosphorylase (20, 21) is a member of the fold type V PLP enzymes. This enzyme uses the PLP cofactor in a very different way. Despite a Schiff base with the ε-amino of a lysine being formed, the PLP does not participate in the catalytic cycle by acting as an electron sink like in aminotransferases (22). Instead, according to the mechanism proposed by Helmreich and coworkers (23–25), the phosphate group of PLP plays a role in acid/base catalysis. The nitrogen of the pyridine ring also lacks the hydrogen bonds with residues in the active site, whereas other PLP-enzymes form hydrogen bonds with aspartic acid, serine, glutamic acid or arginine as discussed above (10).

AMINOTRANSFERASES

As mentioned above, the aminotransferases of fold type I PLP proteins can be further classified into subgroups (5) or classes (4) (AT-I/Class I & II, AT-II/Class III and AT-IV/Class V), based on the degree of similarity in their primary (and three-dimensional) structures (9, 26). All fold type I PLP aminotransferases bind the cofactor at a topologically conserved position and share four invariant residues: Glu314 (numbering of the pig cytosolic aspartate transaminase, pdb 1AJR), located in a turn at the interface of the dimer;

11 CHAPTER 1

Lys385, which forms a Schiff base with PLP; Asp340, interacting with the nitrogen of 1 the pyridoxal ring; and Arg562, which interacts with the α-carboxylate group of the substrate (2, 5). Furthermore, the transaminases of subgroups AT-I, AT-II, and AT-IV have a similar organization of the active site, and a distinguishing feature is that the conserved lysine involved in abstracting the proton from the aldimine intermediate points towards the Si face of the C4’ of the PLP (usually called the Si face of the PLP ring) (26, 27). The substrate selectivity of aminotransferases only partially coincides with the division in these subgroups. Aminotransferases of subgroup AT-I tend to have a broad substrate scope and accept L-alanine, aromatic L-amino acids, and also dicarboxylic amino acids (28). The substrate range of AT-II enzymes is even more diverse, including acetylornithine, ornithine, ω-amino acids, 4-aminobutyrate and diaminopelargonate. Sequence analysis indicates that this subgroup includes enzymes catalyzing other reactions, such as decarboxylation. Several of these PLP fold type I subgroup AT-II enzymes have been studied in detail (9). Activity with L-α-amino acids is often lacking. Some members accept molecules that contain two amino groups of which one reacts, e.g. L-lysine ε-aminotransferase. Also the well-studied aminotransferases from Chromobacterium violaceum (CvAT) (29) and Vibrio fluvialis (VfAT) (30), which poorly accept L-α-amino acids, belong to this AT-II subgroup. The latter transaminases have been the subject of multiple studies during the last decade, mainly because of their use in biocatalytic processes toward enantiopure compounds (31). They show high preference for aromatic amines, such as benzylamine and (S)-methylbenzylamine (32). CvAT and VfAT both are (S)-enantioselective with aryl-subsituted substrates and lack detectable activity with (R)-enantiomers of the same compounds (32–34). Aliphatic amines and most of the α-amino acids, except for L-alanine, give very poor activity and pyruvate is the only amino aceptor showing good activity (30, 32, 35). The β-amino acid aminotransferases investigated in our laboratory also belong the subgroup AT-II enzymes (13, 14). Within the fold type I PLP enzymes, the subgroup AT-IV enzymes catalyze the transamination of substrates with related chemical structures such as L-serine and 3-phospho-L-serine, utilizing 2-oxoglutarate or pyruvate as amino acceptors (4, 5). The subgroup III aminotransferases (AT-III) do not group with the fold type I PLP enzymes; instead they belong to the fold type IV PLP enzymes (4, 5). A comparison between the structures of the dimeric D-amino acid aminotransferase from Bacillus sp. (16) (pdb 1DAA) and the hexameric branched chain amino acid aminotransferase from E. coli (pdb 1A3G, (19)) shows that the same fold type can occur in different multimeric assemblies. The stereochemical preference of some of these enzymes is opposite that of the fold type I enzymes, which is explained by the inverted way of PLP binding, i.e. with the Re face of the PLP C4’ towards the β-barrel present in the N-terminal domain of the protein (36). The conserved lysine forming the Schiff base in the internal aldimine thus points towards the Re face of the C4’ of the external aldimine intermediate (37). Enzymes of subgroup III accept a variety of substrates, including 4-aminobutyrate, branched amino acids, and D-alanine.

12 INTRODUCTION

Transaminase discovery Early studies on transaminases used whole cells, cell-free extracts, and enzymes isolated 1 from microbial cultures or tissue. More than 50 years ago, Rudman et al. (38) reported a transamination reaction between aliphatic amino acids and α-ketoglutarate catalyzed by cell extracts from E. coli, and Campbell et al. (39) described the transamination of amino acids catalyzed by a Pseudomonas strain. The latter paper reported the production of glycine from glyoxylic acid utilizing aspartic acid, glutamic acid, asparagine and glutamine as amino donors (40). Later studies employed microbiological enrichment cultures with a substrate of interest as a strategy to find desired transaminases. The target substrate is added as a sole source of nitrogen or/and carbon. This selection method requires expression of the enzyme under the applied cultivation conditions, which may be the case both in fungi and bacteria. Fincham et al. (41) reported an increase of the transaminase production by Neurospora crassa when valine and isoleucine were added to the culture medium. Similarly, transaminase activity towards taurine and α-ketoglutarate was enhanced when Achromobacter superficialis and Achromobacter polymorph were cultured in medium containing β-alanine (42). It was found that to detect aminotransferase activity in cell lysates of such cultures, the cofactor pyridoxal phosphate often had to be added (40), which suggested that loss of the cofactor under enzyme preparation and assay conditions can easily occur (41). Soil samples are often used as a source of microbial diversity in aminotransferase enrichment experiments. For example, the well- known ω-aminotransferase from V. fluvialis was found by selective enrichment with (S)- methylbenzylamine as the sole source of nitrogen and with soil as inoculum (33, 43). New tools have delivered additional and faster procedures for the discovery of aminotransferases. Functional or sequence-based analysis of metagenomic libraries, genome sequencing of microbial isolates, and bioinformatics mining of genomic databases can reduce the number of steps necessary for identifying and expressing a new enzyme. Bioinformatics can be used for selecting enzymes that are expected to exhibit a certain performance, such as substrate range or thermostability. For example, the well-studied aminotransferase from C. violaceum DSM30191 was found through sequence analysis of the genome, based on homology to the published sequence of the aminotransferase from V. fluvialis (32). Furthermore, Wilding et al. (44) reported the identification of 14 aminotransferases from Pseudomonas AAC, a strain from a collection of soil and water bacteria. Eleven of these enzymes could be expressed in E. coli and 3 of them showed activity with 12-aminododecanoic acid, indicating that they could be promising biocatalyst for the production of nylon precursors. Computational methods to predict aminotransferase selectivity and to design variants have been explored. Höhne et al. described the discovery of 17 (R)-selective aminotransferases by a computational approach which included structure analysis to predict amino acid motifs and a subsequent in-silico screening of sequence databases to identify those

13 CHAPTER 1

variants carrying the key motifs (45). This indicated that approaches which combine 1 rational design and computational screening will gain importance for the discovery and engineering of aminotransferases with specific substrate preferences (45).

Aminotransferase mechanism Aspartate aminotransferase from chicken mitochondria (AATA, pdb 1AAT) is a mechanistically well-studied PLP-dependent enzyme. The enzyme belongs to subgroup AT-I (fold type I) and catalyzes the reversible transfer of an amino group from L-aspartate to 2-oxoglutarate, producing oxaloacetate and L-glutamate (Scheme 2). As most of the fold type I aminotransferases, it is a homodimer composed of two subunits of ca. 45 kDa with the active site at the dimer interface. Its crystal structure was the first aminotransferase structure to be elucidated (11) and it served as model to study the reaction mechanism of PLP enzymes. More than 30 years ago Kirsch et al. (46) described the catalytic cycle in detail, including the role of the PLP cofactor acting as an electron sink. The catalytic cycle of aminotransferases consists of several steps, which can be grouped in 2 half reactions. The first half reaction includes a series of steps in which the substrate amino group is transferred to PLP, yielding the pyridoxamine enzyme (PMP) and the keto product (3). In the second half reaction, the amino group of PMP is transferred to a keto (or aldehyde) acceptor, yielding an amine and regenerating the PLP in the pyridoxal form. Mechanistically, the second half reaction is the reverse of the first half reaction, so it also involves multiple steps (Scheme 3).

Scheme 2. Transamination of aspartic acid catalyzed by aspartate aminotransferase.

In the substrate-free form of an aminotransferase, the ε-amino group of the conserved lysine has formed a Schiff base linkage with the aldehyde group of PLP (47). This invariable complex in the holoenzyme is known as the internal aldimine, the formation of which involves several intermediates and the release of one molecule of water. After formation of a Michaelis complex by substrate binding, in the first chemical step of the first half reaction the internal aldimine is converted into an external aldimine, in which the substrate amine group forms a Schiff base linkage with PLP and the side chain ε-amino group of the lysine is released. Next, a proton is abstracted from the α-carbon of the substrate-PLP complex, resulting in the formation of the quinonoid

14 INTRODUCTION intermediate by transfer and delocalization of negative charge to the pyridine ring. Subsequently, the ketimine intermediate is formed through protonation of the former 1 aldehyde carbon (C4’) of the coenzyme. This conversion of the quinonoid to the ketimine intermediate is a critical step in the reaction mechanism of aminotransferases, since subsequent hydrolysis of the ketimine yields the keto product. In racemases, the quinonoid intermediate can be reprotonated on the opposite face of the substrate carbon, in which case racemisation occurs upon hydrolysis at the PLP 4’ carbon. Since different intermediates may be generated from the quinonoid by transfer of protons, the particular configuration of acid and basic residues in the active site seems to determine the substrate specificity and the type of PLP-dependent reaction that is catalyzed (26). Hydrolysis of the ketimine is accompanied by deamination of the substrate and conversion of the PLP to a pyridoxamine, which in turn can transfer the amino group to a ketoacid or another carbonyl compound that acts as acceptor. In case of aspartate aminotransferase, the acceptor is 2-oxoglutarate and the enzyme produces L-glutamate. The mechanism is similar in many other aminotransferases, including other fold type I enzymes, and within that group similarities are high enough to identify residues involved in cofactor binding and catalysis from sequence- or structural alignments (47). Furthermore, the overall mechanistic features are conserved in aminotransferases from other fold types.

15 CHAPTER 1

1

Scheme 3. Catalytic mechanism of PLP-dependent aminotransferases. Only the PLP-amination reaction with an L-amino acid as donor is shown. Transfer of the amino group from the pyridoxamine phosphate intermediate to a keto acceptor follows the inverse sequence of reactions.

Function of aminotransferases Scientitfic interest in aminotransferases not only stems from their mechanistic features and evolutionary origins, but is also stimulated by their industrial relevance and important functions in biology. Aminotransferases are key enzymes of central amino acid metabolism, e.g. by catalyzing the deamination reaction during the catabolism of amino acids (3). As mentioned above, aspartate aminotransferase transfers the α-amino group to α-ketoglutarate producing glutamate, connecting central intermediates of carbon metabolism to amino acid metabolism (Scheme 2). Transamination provides the nitrogen group for the synthesis of various amino acids (48). Glutamate is a key component of amino acid metabolism because it plays two important roles: it is the nitrogen donor for the synthesis of most amino acids, and it acts as the precursor for the synthesis of proline and arginine (3, 49). Aminotransferases also carry out the deamination of branched-chain amino acids during catabolism. In humans, these amino acids need to be acquired through the diet since they cannot be synthesized endogenously. When taken in excess they are metabolized with the deamination

16 INTRODUCTION reaction catalyzed by aminotransferases (48). In bacteria, aminotransferases also have a crucial role in the amino acid catabolism, for example in the conversion of β-alanine 1 and L-tryptophan (50). Many synthetic pathways towards amino acids and other aminated compounds in bacteria, animals and plants include aminotransferases as crucial enzymes for the amination of keto-precursors. In bacteria, the last step of the synthesis of the aromatic amino acids phenylalanine and tyrosine is the aminotransferase-catalyzed amination of the precursors phenylpyruvate and p-hydroxyphenylpyruvate, respectively, using glutamate as the amino donor. A tyrosine aminotransferase is involved in the biosynthesis of leucine, phenylalanine and tyrosine (51–55). An aspartate amino­transferase catalyses the amination of oxaloacetate to produce aspartate (54, 56) and the aminotransferase B is involved in the synthesis of the branched-chain amino acids leucine, isoleucine, and valine (3, 57). During our studies on the enzymes responsible for the biodegradation of caprolactam described in Chapter 3, a new ω-aminotransferase was found and characterized in Pseudomonas jessenii. It is involved in the transamination of 6-oxohexanoate to produce 6-aminohexanoic acid and represents one enzyme in the caprolactam degradation pathway that remained unidentified so far (57).

SYNTHESIS OF AMINES

I. Chemical synthesis Amines can be synthesized via many chemical methods, with alkylation and reduction as the main reactions. In case of synthesis of amines by alkylation, ammonia or an organic amine acts as a nucleophile and reacts with a haloalkane or an alcohol to give a primary amine product. The disadvantage of this process is the low purity of the product, which is caused by the reactivity of the amine product as a nucleophile. This may lead to subsequent reactions that produce secondary, tertiary and quaternary amines or ammonium salts (Scheme 4).

Scheme 4. Synthesis of amines by alkylation with alcohols. During the first steps, a primary amine is formed. This two-step sequence may continue, forming secondary, tertiary and quaternary amines (58).

17 CHAPTER 1

The second most used method is the reductive amination of aldehydes and ketones, 1 which comprises two steps. In the first step, an amine undergoes condensation with a carbonyl compound to produce an imine. In the second step, the imine double bond is reduced by catalytic hydrogenation. This process can be carried out as one-pot reaction with the reducing agent triacetoxyborohydride or with hydrogen in industrial processes (59) (Scheme 5). An example of a synthetic pathway involving both alkylation of an organic halide and reductive amination is the route towards the drug fentanyl, a compound used to induce anesthesia for surgery and to treat pain (Scheme 6).

Scheme 5. Reductive amination of ketones and aldehydes. Adapted from Abdel-Magid et al. (59).

Scheme 6. Synthesis of fentanyl, a commercial drug containing a piperidine moiety. C-N bond formation (amination) occurs by alkylation of an organobromide, and by a condensation reaction followed by reduction (60).

18 INTRODUCTION

Two reductive methods often used for the preparation of amines are the reduction of amide moieties and the reduction of nitriles. The carbonyl group of an amide is reduced 1 by lithium aluminum hydride to give an amine. This reaction produces primary amines from N-unsubstituted amides, secondary amines from monosubstituted amides, and tertiary amines from disubstituted amides (61) (Scheme 7A). Lithium aluminum hydride is also used as the reducing agent for the reduction of nitriles where the triple carbon- nitrogen bond is reduced to give a primary amine (Scheme 7B). Metal catalysts such as rhodium (62) and lithium (63) can also serve to reduce the nitrile moiety.

A

B

Scheme 7. A. Amine reduction with lithium aluminum hydride. B. Preparation of amines by reduction of nitriles.

II. Aminotransferases for the production of chiral and non-chiral amines Biocatalysis offers alternative methods for the production of amines, especially primary amines. These enzyme-mediated conversions often are environmentally friendly and can avoid the necessity to use potentially toxic heavy metal catalysts. Enzymatic reactions can be carried at room temperature and atmospheric pressure, thereby decreasing energy usage and avoiding problems such as molecular rearrangement of substrates and products (64). Additionally, enzymes are regio-, chemo- and enantioselective catalysts. These important features allow selective conversion of target compounds in complex mixtures, like it happens in living cells. As described above, aminotransferases catalyze the transfer of an amino group from an amino donor to an amino acceptor (an aldehyde or a ketone). Therefore, these enzymes are widely explored for the production of amines. Attractive features are the broad substrate specificity covered by the diversity of known aminotransferases, the often observed excellent stereoselectivity, and the high turnover rates. Furthermore, unlike with dehydrogenases, no (reducing) external cofactor is needed. Thus, aminotransferases are employed in the synthesis of fine chemicals including building blocks for the pharmaceutical industry (65).

19 CHAPTER 1

During enzymatic asymmetric synthesis, amines might be produced starting from 1 a ketone with the desired carbon skeleton. In the presence of a good amine donor and biocatalyst, conversion can proceed to near 100% product yield. Not surprisingly, aminotransferase-mediated ketone amination has become a highly attractive step in synthetic routes for the production of non-enantiopure and enantiopure amines (35, 66). One famous example is the synthesis of sitagliptin, the active ingredient of Januvia, an oral medicine for the treatment of type 2 diabetes (67). When this compound is synthesized via an enzymatic step catalyzed by an enantioselective aminotransferase (Scheme 8, right branch) two time- and resource-consuming steps part of the chemical synthesis route (Scheme 8, left branch) are eliminated. The aminotransferase catalyzed reaction is performed under mild conditions and fewer steps are needed to obtain the desired product. Although less intensively studied, aminotransferases also have potential as catalysts for the production of non-chiral amines. Simon et al. (68), described the preparation of pyrrolidines and piperidines via the amination of diketones to produce cyclic amines (Scheme 9). Several ω-aminotransferases, including CvAT (32) and VfAT (28), showed excellent conversion of 1,5-diketones to amino-ketones. These molecules are valuables precursors for the synthesis of the alkaloids dihydropinidine and epi-dihydropinidine (69); both are naturally occurring defense compounds produced by certain plants to repel predator insects or animals. Furthermore, due to their regioselectivity, aminotransferases are useful catalysts for the synthesis of non-chiral products when using as substrates with two equal functional groups, as in 1,5-diketones. An example of this is the production of 2,6-disubstituted piperidines in one-pot cascade reactions, described by France et al. (70). Aminotransferases appeared promising for the production of aromatic pyrazines, using 4-phenyl-2-butanone as amino acceptor and 1,2-aminodiamines as amino donors (Scheme 10) (71).

20 INTRODUCTION

1

Scheme 8. Routes for the synthesis of sitagliptin. Left: chemocatalytic route. Right: biocatalytic route with an engineered aminotransferase. Adapted from Desai et al. (67).

21 CHAPTER 1

1

Scheme 9. Enzymatic monoamination of diketones catalyzed by ω‑aminotransferases in the synthesis of 2,6-disubstituted pyridines. Adapted from Simon et al. (68).

Besides the possibility of using aminotransferases as isolated enzymes in single or multi-enzyme reactions, they also may play an important role in the in vivo synthesis of amines, e.g. in artificial pathways constructed by metabolic engineering. An example is the assembled pathway for the production of 6-aminohexanoic acid utilizing an aminotransferase from Bacillus subtilis (72). This product is the precursor in the synthesis of nylon-6, one of the most used polymers for manufacturing of fibers, utensils, mechanical parts and household products.

Scheme 10. Enzymatic amination of ketones utilizing 1,2-diamines as amino donors. Based on Payer et al. (71).

III. Alternative enzymes for the production of amines Besides aminotransferases, hydrolases and oxidoreductases have been used for the preparation of enantiopure amines. The most important group of hydrolases used in biocatalysis are the lipases, enzymes with a broad substrate spectrum which catalyze the cleavage of esters and occasionally also of amides. The high activity in organic solvent makes lipases attractive for the conversion or production of compounds that are poorly water soluble (73). The lipase from Candida antarctica (CALB) is an efficient biocatalyst for the enantioselective acylation of amines (74–76). González-Sabín et. al. (77) reported an enzymatic resolution of (±)-trans- and (±)-cis-2-phenylcyclopentanamine by CALB which catalyzed an aminolysis reaction (Scheme 11).

22 INTRODUCTION

1

Scheme 11. Enzymatic kinetic resolution of (±)-trans-2-phenylcyclopentanamine by lipase CALB- catalyzed aminolysis of esters into amides. Trans-2-phenylcyclopentanamine is an antidepressant, and can be used for the synthesis of compounds with hypoglycemic activity. Modified from González-Sabín et al. (77).

Oxidoreductases, including imine reductases, amine dehydrogenases and amine oxidases, also can be efficient catalysts for the production of enantiopure amines (78). Imine reductases are NADPH-dependent enzymes which catalyze the reduction of imine moieties to amines. Huber et al. (79) reported the enzymatic reduction of 3,4-dihydroisoquinolines and 3,4-dihydro-β-carbolines by the S-selective imine reductases from Streptomyces sp. GF3546 and Streptomyces aurantiacus (Scheme 12).

Scheme 12. Reduction of 3,4-dihydroisoquinoline and 3,4-dihydro-β-carboline catalysed by imine reductases. A cofactor regeneration system to recycle the reducing cofactor was set up with glucose dehydrogenase (79).

Amine dehydrogenases are also enantioselective enzymes of the oxidoreductase family. They catalyze the reductive amination of ketones, in particular ketoacids, to produce chiral amines using NADPH as electron donor. As for the imine reductases, the cofactor regenaration system can be a glucose dehydrogenase or a formate dehydrogenase, both accepting cheap substrates as electron source (80, 81). Abrahamson et al. (82) altered

23 CHAPTER 1

the substrate specificity of a leucine dehydrogenase fromBacillus stereothermophilus in 1 order to create a novel amine dehydrogenase that is independent of the presence of a carboxylate functionality in the substrate. This enzyme reduces the carbonyl function of methyl isobutyl ketone (Scheme 13).

Scheme 13. Reduction of methyl isobutyl ketone by an engineered leucine dehydrogenase converted to an amine dehydrogenase (82).

The final group of enzymes of the oxidoreductase family with the potential to produce enantiopure amines mentioned here are the amine oxidases. These enzymes catalyze the oxidation of amines to imines with the simultaneous reduction of oxygen to hydrogen peroxide. Alexeeva et al. (83) and coworkers reported the deracemization of α-amino acids by D- and L-amino acid oxidases. A cycle of oxidation of the amine to imine catalyzed by the amine oxidase and the nonselective reduction by a strong reducing agent, as an amine-borane complex, is repeated until a stereoinversion of one enantiomer to the other is reached (84) (Scheme 14).

Scheme 14. Stereoinversion of D- to L-alanine by the porcine kidney D-amino acid oxidase and

sodium tetrahydroborate (NaBH4). Adapted from Beard et al. (84).

24 INTRODUCTION

ENZYMATIC CASCADE FOR THE BIOTRANSFORMATION OF ALCOHOLS TO AMINES 1

Alcohols are widely available for industrial usage since they can be conveniently produced either from renewable resources or via petrochemistry, both on large scale. Due to the low cost of many alcohols and the large production scale, alcohols would be suitable substrates for the production of amines. The chemical production of amines from alcohols and ammonia can occur at high temperature and pressure in the presence of a catalyst to form primary amines (85). Such chemical amination processes take place under harsh conditions and make use of organic solvents and metal-based catalysts because alcohols are not very reactive (86–88). The use of metal catalysts such as ruthenium, copper (89), iron (90) and palladium (91) in combination with high pressure and temperature and the long reaction times often cause formation of side products, i.e. secondary and tertiary amines (92–95). Therefore, the chemical production of amines with alcohols as starting compounds suffers from unfavorable sustainability characteristics, which justify a search for more efficient alternatives, including biocatalysis. Advantages of the use of enzymes for alcohol amination may not immediately be evident since most aminating enzymes do not act on alcohols but on aldehydes or ketones. Enzymatic processes for alcohol amination thus imply substrate oxidation (hydroxy to oxo), followed either by amination with an organic amine catalyzed by an aminotransferase or by amination with ammonia catalyzed by amino acid (or amine) dehydrogenase. The use of a combination of enzymes is attractive, especially in case of an alcohol dehydrogenase and an amine dehydrogenase, where the overall reaction is redox neutral. Chemical conversion of oxo compounds to amines is also possible, but as a side reaction the substrate’s carbonyl group might be hydrogenated forming alcohols at the expense of substrate (95). Furthermore, both in chemical and enzymatic processes the carbonyl substrate might react with the amine product, forming unwanted imines or amines (96). This causes the need of extra purification steps, which can be expensive and technically difficult to perform. Biocatalytic cascade reactions of alcohols to amines via aldehydes or ketones may be feasible if the problems described above can be avoided, especially through a high selectivity of enzymes and rapid turnover of reactive intermediates. Therefore, enzymatic cascade reactions where two or more enzymes are used in a single mixture can be attractive. Multienzymatic systems can achieve high yields, increase reaction rates, and avoid purification steps. This reduces production costs and decreases the amount of waste that is produced (97, 98). The keto intermediates that undergo amination reaction in enzymatic cascades may be formed by dehydrogenases and/or transketolases (99, 100). Sehl et al. (101) proposed a combination of reactions resulting in a recycling cascade, meaning that the deaminated product of the aminotransferase served as substrate for the transketolase.

25 CHAPTER 1

This one-pot two-step process included a pyruvate decarboxylase that formed (R)- 1 phenylacetylcarbinol ((R)-1-hydroxy-1-phenylacetone) from pyruvate and benzaldehyde. This product was transformed by aminotransferase activity either to (1R,2R)-nor(pseudo) ephedrine or (1R,2S)-nor(pseudo)ephedrine, dependent on the enantioselectivity of the used aminotransferase; Aspergillus terreus AT, or Chromobacterium violaceum AT, respectively. The transamination was driven by L-alanine, and the formed pyruvate could be used directly or via enzymatic formation of acetolactate as a substrate for the transketolase reaction. To avoid unwanted side reactions the aminotransferases were added after the synthesis of the keto intermediate was completed. Another example that employs a pyruvate decarboxylase as a carboligase in order to synthesize the amine acceptor was recently reported for the synthesis of a tetrahydroquinoline (Scheme 15). In the three-enzyme cascade, the transaminase step was catalyzed by the enzyme from C. violaceum with isopropylamine as amine donor (102). The tetrahydroisoquinoline moiety occurs in a number of bioactive compounds with therapeutic applications.

Scheme 15. Synthesis of a tetrahydroquinoline by a three-enzyme cascade (102). Piclet- Spenglerase is a norcoclaurine synthase from plant benzyl-isoquinoline alkaloid biosynthesis.

Both in single-enzyme reactions and in multi-enzyme systems that involve an aminotransferase step, an unfavorable reaction equilibrium may be an issue. Dependent on the properties of the amine donor and acceptor, thermodynamics may favor the aminotransferase reaction in the direction towards the ketone form of the substrate

26 INTRODUCTION rather than to the amine product of interest (43, 103). Besides this equilibrium issue, kinetics of enzymatic transamination may be problematic, especially due to product 1 inhibition. Shin and Kim (104) demonstrated that, although thermodynamically favorable, the kinetic resolution of (R,S)-α-methylbenzylamine with the ω-transaminase of Vibrio fluvialis did not reach completion due to the inhibition of the enzyme by the products alanine and acetophenone formed during conversion. A possible strategy to shift the unfavorable equilibrium of aminotransferase reactions towards production of a desired amine is to couple the reaction to a thermodynamically more favorable conversion (105, 106). In an early paper, Bartsch et al. (107) reported the synthesis of the herbicide L-phosphinothricin by a two-enzyme process of a glutamate:oxaloacetate aminotransferase and a 4-aminobutyrate:2-ketoglutarate aminotransferase (Scheme 16). The proposed conversion is a one-pot reaction in which glutamate, the primary amino donor, is regenerated from aspartate, the secondary amino donor, obtaining oxaloacetic acid as by-product. Oxaloacetate decarboxylates spontaneously to pyruvate, forcing the equilibrium towards the synthesis of the desired product, L-phosphinothricin. When both transaminases were coupled in a two-step reaction the yield was significantly higher in comparison with an earlier one-enzyme reaction.

Scheme 16. A glutamate:oxalacetate aminotransferase used together with a 4‑amino­butyrate:2-ketoglutarate aminotransferase for the production of L‑phosphinothricin [L-homoalanin-4-yl-(methyl)phosphinic acid], the active ingredient of the herbicide Basta (AgrEvo GmbH). Adapted from Bartsch et al. (107).

27 CHAPTER 1

When using alanine as the amino donor in aminotransferase reactions, a feasible strategy 1 to shift the equilibrium is the addition of an enzymatic step for the removal of the deaminated product pyruvate. Enzymatic cascades employing two or three enzymes have been designed to produce amines using this strategy. One possibility to remove pyruvate is by adding a pyruvate decarboxylase (Scheme 17) (108). Another option is to use a lactate dehydrogenase that reduces pyruvate to lactate with regeneration of the required reduced nicotinamide cofactor by addition of a glucose dehydrogenase (Scheme 18) (109–111). The use of a dehydrogenase to shift the equilibrium was also described by Cassimjee et al. (112), in this case for the oxidative removal of acetone formed when isopropylamine was used as the amine donor, with cofactor regeneration by formate dehydrogenase. Occasionally, an amine donor may be used that rearranges upon being converted to a ketone, forming a compound that cannot act as amine acceptor and preventing any reverse reaction. This principle was demonstrated with 3-aminocyclohexa-1,5-dienecarboxylic, accepted as donor by a variant of C. violaceum aminotransferase (113).

Scheme 17. Removal of pyruvate in the amino transferase reaction by a pyruvate decarboxylase. The product of the pyruvate decarboxylation is acetaldehyde, a volatile compound which together

with the production of gaseous CO2 makes the reaction irreversible. Adapted from Höhne et al. (108).

28 INTRODUCTION

Other possible strategies for shifting the aminotransferase reaction towards the amine product are the removal of the amine product by continuous extraction with 1 an organic solvent at alkaline pH (114, 115), the removal of acetone by evaporation when 2-propylamine is used as amino donor (116), and the addition of an excess of the amino donor (43). Shin et al. (117) performed a kinetic resolution of sec-butylamine under reduced pressure, driving the reaction to higher yields through the removal of the inhibitory deaminated product 2-butanone. When adding one substrate in excess it needs to be considered that very high concentrations might not be tolerated by the aminotransferases. The ATs are known to be sensitive to substrate inhibition (118), which can be explained by binding of the amino donor to the pyridoxamine intermediate instead of the ketone.

Scheme 18. Enzymatic cascade reaction including an aminotransferase, a lactate dehydrogenase and a glucose dehydrogenase (109).

Besides the advantages of cascade reactions related to more environmental friendly reaction conditions and the shifting reaction equilibria, there is a third reason to explore cascades for alcohol amination. The necessity to first convert alcohols to keto compounds or aldehydes that can undergo the actual amination reaction implies an oxidative step preceding amination. A transketolase reaction will also yield a keto substrate that may

29 CHAPTER 1

act as acceptor (discussed above), but that changes the carbon skeleton and starts with a 1 keto compound. Although oxidase reactions for alcohol oxidation which use molecular oxygen and generate hydrogen peroxide are possible, most alcohol oxidation reactions employ dehydrogenases that use an electron-accepting nicotinamide as cofactor. Cofactor recycling is then a must, which can be done by coupling to an reductive conversion or mediated by an oxidase activity (126, 127). Strategies to overcome enzyme-related kinetic or stability problems in amino­ transferases are directed evolution and rational redesign (119). Impressive studies aimed at engineering more stable and active aminotransferases for use in production processes have appeared in recent years. For example, Savile and coworkers (120) used multiple rounds of directed evolution to drastically widen the substrate range of a PLP fold type IV aminotransferase from Arthrobacter. The enzyme active site was gradually widened to allow binding of a bulky ketoamide shown in Scheme 18, which is not at all accepted by the wild-type enzyme. Resistance to harsh process conditions was also improved. The result was an aminotransferase that can be used for the production of the antidiabetic compound sitagliptin. Engineering studies aimed at broadening the aminotransferases of the PLP fold type I enzymes have also been carried out. Prominent examples are the engineering of the selectivity of the aminotransferases from V. fluvialis to obtain an enzyme for the synthesis of the neuroactive compound imagabalin, which is a potential drug for treating anxiety disorders (121). The V. fluvialis AT was engineered by the group of Bornscheuer (122) who also investigated a somewhat related AT from Ruegeria (123). Remarkable progress also has been made with respect to stability improvement. Whereas single mutations discovered by FoldX energy calculations gave some improvement of a β-amino acid aminotransferase from Variovorax paradoxus that was studied earlier in our lab (124), larger increases in stability were achieved by introducing mutations that improve cofactor binding in a Fold type I class III AT that was discovered in a metagenomic library (125). Such stabilized enzymes may be more suitable than wild-type variants in cascade reactions employing high concentrations of amine donor to shift reaction equilibria. The use of high substrate concentrations is challenging but important for success in many biocatalytic conversion processes.

30 INTRODUCTION

AIMS AND OUTLINE OF THIS THESIS 1 Aminotransferases are highly useful enzymes for the production of non-chiral and chiral amines. Many potential advantages are associated with the use of enzymes as catalysts in amination reactions, such as benign process conditions and high catalytic selectivity. The implementation of aminotransferases in industrial processes can also reduce the number of required purification steps and waste production, increasing the yield and contributing to overall process efficiency. As with other biocatalytic processes, the screening of existing enzymes and the discovery or engineering of known enzymes are key steps in the development of new conversions. The work described in this thesis aims to identify and characterize novel aminotransferase activity, to explore computation-supported engineering of an aminotransferase for improving stability, and to gain insight in the application of aminotransferases in an enzymatic cascade reaction for alcohol amination. The work is devoted to ω-aminotransferases that act on aldehydes, which poses additional challenges because of their reactivity. Chapter 2 of this thesis describes an exploration of the caprolactam degradation pathway. Microbiological enrichment of soil organisms with caprolactam as growth substrate was performed to find organisms possessing a degradation pathway that includes ω-aminotransferase activity. Two novel enzymes involved in the caprolactam degradation were identified in a strain of Pseudomonas jessenii that grows on caprolactam. The activity and putative function of both enzymes are discussed. Chapter 3 is dedicated to a detailed biochemical characterization of the PLP fold type I aminotransferase from the caprolactam degradation pathway found in P. jessenii described in Chapter 2. The substrate profile of the novel enzyme was studied and the crystal structure was elucidated. A computational approach to improve the stability of the aminotransferase of P. jessenii is presented in Chapter 4. Because of the low storage and operational stability of the enzyme at higher temperatures and high salt concentrations, the FRESCO protocol was applied to find stabilizing mutations. Although variants with improved stability were found, the strategy is not yet optimal. In Chapter 5 we examine the thermodynamic aspects of an ammonia-driven enzymatic cascade, which includes the aminotransferase of Chromobacterium violaceum. Equilibrium calculations were carried out finding that the cofactor recycling reaction and high ammonia concentration drive the overall conversion of ether alcohols towards the aminated product. Finally, in Chapter 6 a summary of the results obtained in this thesis is presented. We discuss the importance of aminotransferases in industrial processes and the features of the enzymes which still need further improvement.

31 CHAPTER 1

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35 CHAPTER 1

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36 Characterization of the caprolactam 2degradation pathway in Pseudomonas jessenii using mass spectrometry-based proteomics

Marleen Otzen, Cyntia M. Palacio, and Dick B. Janssen

This work was published in Appl Microbiol Biotechnol (2018) 102:6699-6711

39 ABSTRACT

Some bacterial cultures are capable of growth on caprolactam as sole carbon and nitrogen source, but the enzymes of the catabolic pathway have not been described. We isolated a caprolactam-degrading strain of Pseudomonas jessenii from soil and identified proteins and genes putatively involved in caprolactam metabolism using quantitative mass spectrometry-based proteomics. This led to the discovery of a caprolactamase and an aminotransferase that are involved in the initial steps of caprolactam conversion. Additionally, various proteins were identified that likely are involved in later steps of the pathway. The caprolactamase consists of two subunits and demonstrated high sequence identity to the 5-oxoprolinases. Escherichia coli cells expressing this caprolactamase did not convert 5-oxoproline but were able to hydrolyze caprolactam to form 6-aminocaproic acid in an ATP-dependent manner. Characterization of the aminotransferase revealed that the enzyme deaminates 6-aminocaproic acid to produce 6-oxohexanoate with pyruvate as amino acceptor. The amino acid sequence of the aminotransferase showed high similarity to subgroup II ω-aminotransferases of the PLP-fold type I proteins. Finally, analyses of the genome sequence revealed the presence of a caprolactam catabolism gene cluster comprising a set of genes involved in the conversion of caprolactam to adipate.

40 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

INTRODUCTION

Caprolactam is a large-volume industrial compound mainly used in the production of Nylon 6, a versatile synthetic polymer applied in fabrics, utensils, mechanical parts, etc. Synthesis of Nylon 6 is achieved by ring-opening polymerization of caprolactam at 2 high temperatures. During this process, several side products are generated, including 6-aminocaproic acid (6-aminohexanoic acid (6-ACA)) unreacted monomers, as well as dimers, cyclic dimers, and oligomers of 6-ACA. Caprolactam and these by-products are present as contaminants in waste water of nylon production plants (1–3). The toxic nature of these chemicals, including mutagenic effects and plant growth inhibition, has been shown in different studies (4, 5). Several microorganisms are able to degrade caprolactam and/or these by-products, including strains of Pseudomonas, Alcaligenes, and Acinetobacter (6–8). Previously, a caprolactam degradation pathway was proposed (9). It starts with a caprolactam-ring cleavage to form 6-ACA, followed by the deamination to 6-oxohexanoate and subsequent oxidation to yield adipate. Adipate can be further converted via β-oxidation reactions of the fatty acid metabolism pathway. Whereas this pathway seems straightforward, information about the proteins involved in bacterial caprolactam degradation is rare. At first sight, one would expect a hydrolytic enzyme involved in lactam ring opening. The conversion of the related D,L-α-amino-ε-caprolactam by a combination of a racemase and a L-amino acid lactam hydrolase to yield L-lysine has been described (10–13). Additionally, a putative hydrolase and aminotransferase have been reported for caprolactam metabolism. Recent work suggests that a dehydrogenase may oxidize 6-oxohexanoate to adipate in Arthrobacter sp. KI72 and in Acinetobacter sp. NCIMB 9871. Subsequently, an aminotransferase might catalyze the conversion of 6-ACA to 6-oxohexanoate in the cell (14, 15). The environmental relevance of caprolactam, and the importance to understand the biodegradation pathway of this synthetic compound, prompted us to investigate the biochemistry of the early degradation steps. In this paper, we describe a newly isolated caprolactam degrading strain of Pseudomonas jessenii. To investigate the pathway, and identify the enzymes involved, we used label-free quantitative mass spectrometry based proteomics (16–18). From the various caprolactam-induced proteins, we further examined an unexpected ATP-dependent caprolactamase that forms 6-ACA and a class-II omega-aminotransferase that converts 6-ACA to 6-oxohexanoate. The activities of the enzymes were examined with heterologously expressed proteins. Furthermore, a caprolactam degradation gene cluster containing all genes for the conversion of caprolactam to adipate was detected by genome sequencing.

41 CHAPTER 2

MATERIALS AND METHODS

Growth conditions Escherichia coli C41 (DE3) cells (Lucigen, Halle-Zoersel, Belgium) were grown at 37°C in 2 an LB medium (19). When required, ampicillin (50 μg/ mL) was added. The caprolactam- degrader P. jessenii GO3 was cultured at 30 °C in nitrogen-free minimal medium (MM) (20), supplemented with caprolactam (4 mM) as carbon and nitrogen source. For the

preparation of agar plates, the medium was supplemented with 2% agar or 1.6% H2O- rinsed agarose. To determine the caprolactam tolerance of P. jessenii GO3, cells were precultured in MM supplemented with 0.1% caprolactam at 30 °C. Cells from these precultures were diluted 50- to 100-fold in 200 μL fresh medium supplemented with varying concentrations of caprolactam (0.05 to 1.2%). Subsequently, growth was monitored by measuring the absorbance at 600 nm using a microplate spectrophotometer (PowerWave, BioTek, Winooski, VT, USA).

Enrichment of caprolactam-degrading bacteria For the isolation of bacterial strains, 1 g of residential grassland soil from Groningen (The Netherlands) was used to inoculate 50 mL nitrogen-free MM supplemented with 0.2% glucose and 0.5 mM caprolactam as sole carbon and nitrogen source. Cultures were incubated for 7 days in an orbital shaker at 30 °C. Subsequently, cells were transferred two times to fresh liquid medium after which pure cultures were isolated on MM agarose plates supplemented with 0.2% glucose and 0.5 mM caprolactam. To confirm growth of the resulting pure cultures on caprolactam, cells were reinoculated in selective liquid MM. Identification of isolated organisms was based on the analyses of the 16S rRNA gene sequence, received from the partial genome sequence obtained in this study, using the online EzTaxon database (21). P. jessenii strain GO3 is deposited at DSMZ (Braunschweig, Germany) under accession number DSM 106008.

Genome sequencing and annotation In order to obtain a partial genome sequence, total DNA from P. jessenii GO3 cells was isolated essentially as described previously (19, 22). The resulting genomic DNA was subjected to paired end sequencing by BaseClear BV (Leiden, The Netherlands). The genome sequencing was done using a HiSeq2500 system (Illumina Inc., Eindhoven, The Netherlands). Sequencing of the GO3 genome yielded 1.7 million reads of ~100 bp in length. These were assembled by BaseClear, using the CLC Genomics Workbench version 7.0.4 (Qiagen, Venlo, TheNetherlands), resulting in 1274 contigs with a total length of 7 mega base pairs (Mb). This whole genome project has been deposited at DDBJ/ENA/GenBank under the accession PDLL00000000. The version described in this paper is PDLL01000000. Subsequently, all generated contigs were used for automated annotation using the RAST server (23).

42 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

Molecular techniques Standard recombinant DNA techniques were performed essentially as described previously (19). Restriction enzymes and polymerase were used according to the instructions of the supplier (New England Biolabs, Ipswich, MA, USA). Primers used in this study are listed in Table 1. 2

Table 1: Primers used.

ATfw TTCCTTCTCTAGAATGAACCAGTCAGTATCCTCGC ATrev TTCCTGAATTCTTAATGATGATGATGATGATGGCCGCCCGGACCAACCCACTGAGTGGTGTC OPfw ATCAAGCTTAATGAACACAGTAGACCCGATC OPrev AAGGAAAAAAGCGGCCGCTCAATGACCGGGAGTCAGTTC

Plasmid constructions For the purification of a 6-ACA aminotransferase Pj( AT), plasmid pET-PjAT was constructed containing an in-frame fusion of the PjAT-encoding gene to a hexahistidine tag, behind the T7 promoter region. For this purpose, the PjAT gene was amplified using P. jessenii GO3 chromosomal DNA and primers ATfw and ATrev. The resulting 1419 base pair product was then digested with NdeI/EcoRI and ligated into NdeI/ EcoRI-digested pET20b+ (Novagen-Merck, Amsterdam, The Netherlands). For the expression of caprolactamase subunits α and β, plasmid pET-OP was constructed containing both genes, behind the T7 promoter region. Since both genes are likely located in one operon, they were amplified together using P. jessenii GO3 chromosomal DNA and primers OPfw and OPrev. The resulting 3871 base pair fragment was then digested using HindIII and NotI and ligated into HindIII/ NotI-digested pET20b+.

Proteomics by mass spectrometry Pseudomonas jessenii GO3 cells were cultured in 50 mL MM supplemented with 0.2% glucose and 5 mM (NH4)2SO4 or with 4 mM caprolactam. When the culture reached the late exponential growth phase cells were harvested by centrifugation a 3000×g for 15 min. Cell pellets were washed once with 50 mM potassium phosphate buffer, pH 7.8, and stored at -20 °C prior to use. For mass spectrometry, cell pellets were resuspended in 50 mM potassium phosphate buffer, pH 7.8, and lysed using a Vibra Cell sonicator (Sonics, Newtown, CT, USA) at 0 °C. To remove unbroken cells and cell debris, the samples were centrifuged at 17,000×g for 60 min at 4 °C. Soluble protein was precipitated by the addition of 20% trichloroacetic acid (TCA). After incubating the samples for 1 h on ice, samples were centrifuged at 17,000×g for 30 min at 4 °C. Protein pellets were washed with ice-cold acetone to remove residual TCA. Dry protein extracts were then resuspended in 50 μL 50 mM NaOH. Reduction of the samples was performed with 5 μL of 500 mM dithiothreitol (DTT) in 350 μL 100 mM NH4HCO3 for 30 min at 25 °C, followed by derivatization of sulfhydryls by 30 min

43 CHAPTER 2

incubation at room temperature with 10 μL of 550 mM iodoacetamide. Trypsin digestion was performed overnight at 37 °C by addition of 4 μg trypsin gold (mass spectrometry grade, Promega (Leiden, The Netherlands)), followed by a second trypsin digestion for 3 h at 37 °C using 1 μg trypsin gold. Samples were prepared for injection by addition of 2 2.5% formic acid. For LC-MS, peptides were first trapped on a precolumn (EASY-Column C18, 100 μm × 20 mm, 5 μm particle size, Thermo Scientific, Ermelo, The Netherlands) and separated on a capillary column (C18 PepMap 300, 75 μm × 100 mm, 3-μm particle size, Thermo Scientific) mounted on a Proxeon Easy-nLCII system (Thermo Scientific). Solutions of 0.1% formic acid in water, and 0.1% formic acid in 100% acetonitrile, were used as the mobile phases. A gradient from 5 to 40% acetonitrile was performed at a flow rate of 300 nL/min. Eluted peptides were analyzed using a linear ion trap Orbitrap hybrid mass spectrometer (LTQ-Orbitrap XL, ThermoScientific). MS scans were acquired in the range from 300 to 2000 m/z. The five most intense ions per scan were selected for MS/MS fragmentation (35% normalized collision energy) and detected in the linear ion trap. Peak lists were obtained from raw data files using Proteome Discoverer (version 1.1, Thermo Fisher Scientific). Mascot (version 2.1, Matrix Science, London, UK) was used for searching against the annotated P. jessenii GO3 genomic DNA sequence. Peptide tolerance was set to 10 ppm and the fragment ion tolerance to 2.0 Da, using semitrypsin as protease specificity and allowing for up to two missed cleavages. Oxidation of methionine residues, deamidation of asparagine and glutamine, and S-carboamidomethylation of cysteines were specified as variable modifications. The MS/ MS-based peptide and protein identifications were further validated with the program Scaffold (version 4.6.1, Proteome Software Inc., Portland, OR, USA). Peptide identifications were accepted when the probability was greater than 95%. Protein identifications were based on at least two unique peptides identified by MS/MS, each with a confidence of identification probability higher than 99%. For each growth condition, at least two replicates of two independent cultures were analyzed. Normalized intensity based absolute quantification (iBAQ) values from Scaffold were used as a measure for the abundance of the identified proteins. Average iBAQ values were calculated for the different samples and subsequently log2 transformed. In case the protein was not detected, the log2-transformed iBAQ value was manually set to 8.5, 2.5- fold below the approximate limit of detection. The effect of growth conditions on specific protein amounts was calculated by dividing the average log2 iBAQ value for each protein in extracts from caprolactam grown cells by the corresponding iBAQ value in protein extracts from control cells. A protein was considered upregulated when the log2-fold ratio was more than two and downregulated when the log2-fold ratio was less than 0.5. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (24) partner repository with the data set identifier PXD008544 and https://doi.org/10.6019/PXD008544.

44 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

Expression and purification The aminotransferase PjAT and caprolactamase were both produced in E.coli C41 cells under control of the T7 promoter. PjAT was expressed and purified as previously described for related aminotransferases (25). For the expression of the α and β subunits of caprolactamase, 0.5 mL of an overnight 2 grown LB culture of pET-OP transformed cells was transferred to 50 mL auto induction medium (ForMedium) containing ampicillin and incubated for 48 h in a rotary shaker at 17 °C. To prepare cell-free extracts, cells were washed in buffer A (50 mM ammonium bicarbonate, pH 8.5, 10 mM MgCl2), resuspended in buffer A, and lysed using a Sonics Vibra Cell sonicator at 0 °C. To remove unbroken cells and cell debris, the samples were centrifuged at 17,000×g for 30 min.

Enzyme kinetics To analyze aminotransferase activity in cell-free extracts, reactions were followed using HPLC analyses. Cell-free extracts were prepared in 50 mM potassium phosphate buffer (pH 8) containing 0.3 mM pyridoxal 5’-phosphate (PLP). Standard reaction mixtures contained 50 mM potassium phosphate buffer (pH 8), 2 mM amine acceptor (pyruvate or α-ketoglutarate), 5 mM 6-ACA, 0.3 mM PLP, and cell-free extract, in a total volume of 300 μL. Reactions were carried out at 28 °C. With different time intervals, 50 μL samples were taken and quenched by the addition of 50 μL 2 M HCl. After incubating the samples for 10 min on ice, samples were centrifuged for 10 min at 17,000×g and neutralized using 100 μL 1 M NaOH. Amino acids (6-ACA, alanine, glutamate) in the reaction mixtures were quantified by precolumno -phthalaldehyde (OPA) derivatization and subsequent HPLC analyses. To this purpose, 10-μL sample was mixed with 40 μL 0.4 M boric acid (pH 9.7) and 10 μL OPA solution (Fisher Scientific) and incubated for 20 min at 30 °C. Then, 3 μL of the reaction sample were injected by an autosampler and analyzed by HPLC using a C18 OPA Adsorbosphere column connected to a Jasco FP-920 detector (excitation 350 nm; emission 450 nm). Compounds were eluted using a linear gradient (eluent A, 20 mM sodium acetate, pH 7.2, 0.5% (vol/vol) tetrahydrofuran, 0.018% (vol/vol) TEA and eluent B, 90% acetonitrile) at a flow rate of 0.5 mL/min. The activity of purified PjAT with pyruvate as the amine acceptor was estimated by coupling the reaction to alanine dehydrogenase and measuring the increase in NADH absorbance that occurs as a result of oxidative deamination of the produced alanine. Since pyruvate is a competitive inhibitor of alanine dehydrogenase, low pyruvate concentrations were used to minimize the lag time of the reaction. The concentration of alanine dehydrogenase in the assays was in excess (5 units/mL), to give aminotransferase-dependent velocities. Standard reaction mixtures contained 100 mM potassium phosphate buffer (pH 8), 5 U/mL alanine dehydrogenase, 2 mM NAD+, 0.05 mM PLP, 2 mM substrate, 0.2 mM pyruvate, and varying concentrations of enzyme in a total volume of 300 μL in flat-bottom 96-well microtiter plates. Reactions were carried

45 CHAPTER 2

out at 30°C and analyzed using a microtiterplate reader (Synergy Mx Microplate Reader, BioTek Instruments, Bad Friedrichshall, Germany). Reaction mixtures lacking pyruvate (150 μL) were prewarmed before the reaction was initiated by the addition of 150-μL pyruvate solution. Each reaction was analyzed in triplicate. Initial rates were used to 2 determine specific activities in units per mg protein (μmol/min/mg). Protein content was determined using the Bradford method, with bovine serum albumin as the standard. The amination of 6-oxohexanoate with alanine as donor was also followed by coupling to alanine dehydrogenase. The reaction mixtures contained 100 mM potassium phosphate buffer (pH 8), 2 mM substrate, 0.1 mM NADH, 0.05 mM PLP, 8 U/mL alanine dehydrogenase, 5 mM ammonium bicarbonate, 5 mM L-alanine, and varying concentrations of enzyme in a total volume of 300 μL. Reactions were initiated by addition of 150 μL of L-Ala and carried out as described previously. Conversion was followed by measuring NADH depletion at 340 nm. Caprolactamase activity was determined by analyzing reaction mixtures using an Acquity TQD mass spectrometer (Waters, Etten-Leur, The Netherlands). Standard reaction mixtures contained 2 mM substrate (caprolactam or 5-oxoproline), 5 mM

ATP, 10 mM MgCl2, and cell-free extract, in 50 mM ammonium bicarbonate, pH 8.5. Samples were taken and quenched by the addition of 2% formic acid. Separation of the reaction content was performed by UPLC using a Waters Acquity UPLC HSS T3 Column (1.8 μm, 2.1×150 mm) and a linear gradient (eluent A: water, 0.1% formic acid; eluent B: 100 acetonitrile, 0.1% formic acid). The samples were analyzed in positive ion mode. To determine substrate reduction and product formation, multiple reaction monitoring (MRM) was performed, measuring the following fragments: caprolactam m/z = 96; 6-ACA m/z = 114; 5-oxoproline m/z = 84; glutamate m/z = 102.

RESULTS

Isolation of bacterial strains using caprolactam as a sole nitrogen source In order to isolate a bacterial strain possessing a caprolactam metabolism pathway, soil microorganisms were enriched for the ability to grow on caprolactam as sole nitrogen source. A pure culture was obtained by repeated transfer to fresh medium plates. The bacterial strain that was growing best on selective medium was used to study caprolactam metabolism in detail and was designated strain GO3. Growth analyses revealed that strain GO3 was able to use caprolactam both as a sole nitrogen and carbon source. Interestingly, 6-aminohexanoic acid (6-ACA), a described intermediate in caprolactam degradation (26), was not a possible growth substrate for this strain. In mineral medium (MM) supplemented with 0.05% caprolactam as sole carbon and nitrogen source, the calculated μmax was 0.37 h−1. Growth analyses using different

46 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS concentrations of caprolactam in MM revealed that the μmax is reduced by higher concentration of caprolactam, with a calculated critical caprolactam concentration of 0.46% (Fig. 1).

0.4 2

0.3 ) - 1 (h 0.2 max μ

0.1

0 0 0.2 0.4 0.6 Caprolactam (%)

Fig. 1 Specific growth rates of P. jessenii GO3 in media supplemented with different concentrations of caprolactam.

Draft genome sequence After paired end sequencing of the genomic DNA from strain GO3, genome assembly resulted in 1274 contigs (N50: 10,682 bp), covering 6,993,317 bp. The GC content is 60% with 6231 predicted coding sequences. Among these predicted genes, 4754 were assigned a predicted function (76%). Furthermore, 3 rRNA and 61 tRNA genes were identified in the draft genome. Analyses of the 16S rRNA gene revealed that the organism is a Pseudomonas species closely related to P. jessenii CIP 105274 (99.5% identity). The draft genome was compared to related Pseudomonas species of which the complete sequence is published, including the caprolactam-degrading organism Pseudomonas mosselii SJ10 (27) (Table 2). Previous studies showed that in other caprolactam-utilizing Pseudomonas strains, the genes involved in caprolactam metabolism are plasmid localized (28). Using gel electrophoresis of DNA extracts, we did not find a plasmid in P. jessenii GO3 (data not shown), suggesting a chromosomal location of the catabolic genes.

47 CHAPTER 2

Table 2: General genomic features of various Pseudomonas species.

General features Pj GO3 Pb NFM421B Pk 1855-344 Pm SJ10 Size (Mb) 7.0 6.8 6.8 6.2 GC (%) 60.0 60.8 60.7 63.4 2 CDS 6,231 6,097 5,856 5,413 Protein with predicted function (%) 76.3 The genome data are adopted from the original papers. These numbers may differ from numbers obtained with updated annotations. CDS, coding sequences; Pb, Pseudomonas brassicacearum NFM421 (29); Pk, Pseudomonas kilonensis 1855-344 (30); Pm, P. mosselii SJ10 (27).

Identification of caprolactam degradation enzymes A hypothetical caprolactam degradation pathway (31) involves two unidentified enzymes: the ring cleavage enzyme, presumably a hydrolase, and the enzyme involved in the deamination reaction, which could be an aminotransferase, an oxidase, or an amine dehydrogenase, all three producing an ω-ketoacid. To identify the enzymes involved in the pathway, the P. jessenii GO3 proteome was examined for caprolactam-induced proteins. To this purpose, P. jessenii cells were grown in minimal medium supplemented with caprolactam (4 mM), or glucose plus ammonium sulfate. Cell-free extracts were prepared from both cultures and subjected to quantitative proteome analysis using a label-free approach. A total of 137 different proteins were identified in the combined independent replicate experiments, corresponding to 2.2% of the predicted P. jessenii proteome. Among these, 109 proteins were identified in both experiments and were subjected to further bioinformatic analysis (Fig. 2a). Seventeen of these proteins showed at least a 2-fold increase in log2 protein abundance in the caprolactam-grown cells as compared to the glucose cultures (Fig. 2b and Table 2). Interestingly, some proteins are highly induced on caprolactam, while others are just above the level of detection (LOD ~21, Fig. 2c). Conversely, in glucose-grown cells, these proteins were below the level of detection (iBAQ <21, data not shown).

48 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

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20 ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF ORF 4270 4271 4266 2532 4278 1114 3301 4265 4282 1056 4187 4279 4150 3044 3504 4277 5740 ! Fig.Fig. 2:2: ProteomicProteomic analysisanalysis ofof PP.. jessenii jessenii GO3 GO3 cells, cells, obtained obtained from from two two independent independent replicate replicatecultures. cultures. A) Number A) Numberof P. jessenii of P. proteins jessenii identified proteins identified by mass byspectrometry mass spectrometry in replicate in culture 1 (red) and replicate culture 2 (blue). The overlapping region represents the number of proteins replicate culture 1 (red) and replicate culture 2 (blue). The overlapping region identified in both experiments (purple). B) Bar graph representing the total number of identified representsP. jessenii proteinsthe number (green), of proteins including identified several in caprolactam-inducedboth experiments (purple). proteins B) Bar(red) graph and several representingcaprolactam-repressed the total number proteins of (blue).identified A protein P. jessenii was proteinsconsidered (green upregulated), including when several the protein level in caprolactam-induced cells divided by the protein level in non-induced cells was larger caprolactamthan 2; a protein-induced was proteins considered (red) down-regulated and several caprolactam when this- repressedratio was smaller proteins than (blue 0.5.). C) Bar Agraph protein representing was considered the average upregulated iBAQ log2 when protein the amounts protein levelof the in identified caprolactam upregulated-induced proteins in caprolactam-grown cells. For all these hits the protein amounts in non-induced cells were cells divided by the protein level in non-induced cells was larger than 2; a protein was below the level of detection (not depicted in this plot). considered down-regulated when this ratio was smaller than 0.5. C) Bar graph representing the average iBAQ log2 protein amounts of the identified upregulated proteins in caprolactam-grown cells. For all these hits the protein amounts in non- induced cells were below the level of detection (not depicted in this plot).

49 CHAPTER 2

Hypothetical caprolactam degradation pathway Based on the identified caprolactam-induced proteins (Table 3), in combination with previous data (31), a complete putative P. jessenii caprolactam degradation pathway was built, including all enzymes that play a role in the pathway (Fig. 3). To enable growth 2 on caprolactam as sole carbon and nitrogen source, an active uptake of caprolactam might be needed, which may be dependent on ABC transporter proteins. Four ABC transporter substrate binding proteins are significantly induced during growth on caprolactam, including ORF1056, ORF3044, ORF1114, and ORF2532 (Table 3). Database searches demonstrated homology to various ABC transporters, including the spermidine/putrescine binding proteins (ORF1056 and ORF3044), the branched chain amino acid binding proteins (ORF1114), and the amino acid binding proteins (ORF2532). Interestingly, ORF1114 and ORF2532 were predominantly induced when the cells were grown on caprolactam as sole carbon and nitrogen source (Fig. 2c). Possibly, one or several of these protein(s) are involved in the uptake of caprolactam. Inside the cell caprolactam is most likely converted to 6-ACA. This conversion might be dependent on a caprolactamase, catalyzing the opening of the lactam ring. Inspection of the caprolactam-induced proteins for a lactamase-related protein resulted in the identification of two distinct polypeptides, ORF4270 and ORF4271. Database searches revealed identity to subunits A and B of the hydantoinase from Pseudomonas sp. (Table 3, respectively, 32 and 30% identity) and to the putative 5-oxoprolinase subunits A and B from Pseudomonas putida (OplA, 78% identity and OplB, 86% identity). The ORF4270 and ORF4271 encoded sequences also displayed weak similarity to eukaryotic 5-oxoprolinases which are known to catalyze the ATP dependent hydrolytic decyclization of 5-oxoproline, producing L-glutamate (Saccharomyces cerevisiae OXP1/YKL215c, 22 and 23% identity, respectively) (32). Since 5-oxoproline, hydantoin, and caprolactam share a lactam moiety, it is likely that proteins encoded by these two ORFs are involved in the caprolactamase reaction. Further conversion of 6-ACA can proceed through deamination catalyzed by an aminotransferase, producing 6-oxohexanoate. Inspection of the caprolactam-induced proteins resulted in the identification of a protein with homology to the Vibrio fluvialis ω-amino acid aminotransferase (ORF4266, 43% identity). The well-characterized V. fluvialis enzyme catalyzes the pyruvate-dependent transamination of ω-amino acids and other amines to aldehydes or ketones (33).

50 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

2

Fig. 3 Proposed pathway for the biodegradation of caprolactam in P. jessenii cells. A) conversion of caprolactam to adipate; B) the first steps of β-fatty acid degradation.

51 CHAPTER 2

The product 6-oxohexanoate would then be converted to adipate. In Acinetobacter, this reaction is catalyzed by a 6-oxohexanoate dehydrogenase (15). Among the caprolactam- induced proteins, one protein (ORF4265) was identified with homology to the E. coli succinate semialdehyde dehydrogenase. In E. coli, this enzyme converts succinate 2 semialdehyde to succinate, which is part of the biodegradation of 4-aminobutyric acid (34). Since succinate-semialdehyde and 6-oxohexanoate are structurally similar, it is plausible that this enzyme is involved in the conversion of 6-oxohexanoate. Additionally, this protein has 38% sequence identity to the Acinetobacter 6-oxohexanoate dehydrogenase. Finally, adipate most likely enters the β-oxidation pathway for degradation of fatty acids, which consists of multiple reactions (35). First adipate needs to be activated by CoA, resulting in adipyl-CoA. This reaction might be achieved by the caprolactam-induced protein with homology to the E. coli acetyl-CoA:oxalate CoA-transferase (ORF4277). In E. coli, this enzyme catalyzes the reversible conversion of oxalate and acetyl-CoA to oxalyl- CoA and acetate. Then, adipyl-CoA can be converted in a multistep process by means of an adipyl-CoA dehydrogenase (ORF4282), an enoyl-CoA hydratase, an 3-hydroxyadipyl- CoA dehydrogenase (ORF4279), and a 3-ketoadipyl-CoA thiolase (ORF4278). Homologs of all of these proteins were clearly induced in caprolactam-grown cells, where the enoyl-CoA hydratase function might be performed by a protein with homology to the Pseudomonas fragi fatty acid oxidation complex α subunit (ORF4150). In Pseudomonas, this complex catalyzes multiple reactions of the beta fatty acid oxidation, including the enoyl-CoA hydratase and the 3-hydroxyacyl-CoA dehydrogenase (36).

52 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

Table 3: Caprolactam-induced proteins.

Seq. identity to known EC Accession Name Contig Size (bp) Enzyme proteins (%, organism) number number Succinate- 4265 5 1451 semialdehyde 81, E. coli 1.2.1.24 3JZ4 dehydrogenase 2 Omega 4266 5 1367 aminotransferase 43, V. fluvialis 2.6.1.18 3NUI Hydantoin utilization 4270 5 2114 protein A 32, Pseudomonas sp. 3.5.2.- Q01262 Hydantoin utilization 4271 5 1745 protein B 30, Pseudomonas sp. 3.5.2.- Q01262 Acetyl-CoA:oxalate 4277 5 1238 CoA-transferase 39, E. coli 2.8.3.19 4HL6 Acetyl- 4278 5 1202 CoA acetyltransferase 41, Ralstonia eutropha 2.3.1.9 4O99 3-Hydroxyacyl-CoA 4279 5 1541 dehydrogenase 39, R. eutropha 1.1.1.35 4PZC Acyl-CoA 4282 5 1154 dehydrogenase 42, Thermus thermophilus 1.3.99.2 2DVL ABC transporter, 2532 28 1031 amino acid binding 59, Brucella ovis 4Z9N protein 3504 39 1922 Serine protein kinase 77, E. coli 2.7.11.1 P0ACY5 4.2.1.17 Fatty acid oxidation 5.3.3.8 4150 48 2147 complex α subunit 94, P. fragi 1.1.1.35 1WDK 5.1.2.3 ABC transporter, 1056 157 1112 putrescine binding 75, P. aeruginosa 3TTM protein ABC transporter, branched-chain 1114 161 1133 amino acid binding 51, Agrobacterium fabrum 3IP5 protein ABC transporter, Spermidine/ 31, Streptococcus 3044 330 2549 putrescine binding pneumoniae 4EQB protein Putative enzyme of 3301 363 344 the cupin superfamily 98, Pseudomonas sp. WP_084317822 4187 485 1325 Isocitrate lyase 82, E. coli 4.1.3.1 1IGW Histone H1-like protein 5740 814 905 HC2 43, Chlamydia pneumoniae Q9Z8F9

Gene organization The sequence information for most caprolactam-induced proteins was found on contig 5, a large segment of 40,376 bp containing 36 putative open reading frames (ORF4261 to ORF4296). The genetic context of this contig was analyzed using the RAST server. This revealed that contig 5 comprises two gene clusters involved in the caprolactam degradation.

53 CHAPTER 2

The first gene cluster contains the genes putatively involved in the conversion of caprolactam to adipate, including both subunits of the proposed caprolactam-induced caprolactamase (ORF4270, ORF4271), the omega aminotransferase (ORF4266), and a 6-oxohexanoate dehydrogenase (ORF4265) (Fig. 4a). In between these genes, three 2 other ORFs are located (Fig. 4a, Pj, in blue). BLAST searches revealed that these open reading frames encode proteins with high homology to the L-2-hydroxyglutarate oxidase LhgO of E. coli (ORF4267, 72% identity), the starvation induced protein CsiD of P. putida (ORF4268, 75%), and the transcriptional regulator CsiR from E. coli (ORF4269, 59%). In E. coli, these genes cluster together with gabD, gabT, and gabP involved in the conversion of γ-aminobutyrate to succinate. The gabD gene encodes a succinate-semialdehyde dehydrogenase (DH), gabT a γ-aminobutyrate aminotransferase (AT) and gabP a γ-aminobutyratepermease. GabT and GabD represent similar catalytic activities as the P. jessenii omega aminotransferase (ORF4266) and the 6-oxohexanoate dehydrogenase (ORF4265), respectively. Clear differences between both gene clusters include (1) the absence of a homolog of the γ-aminobutyrate permease gabP in P. jessenii, which might explain why P. jessenii is not able to grow on minimal medium supplemented with 6-ACA as sole nitrogen source; (2) the absence of a homolog of the caprolactamase genes ORF4270 and 4271 in E. coli, which appeared to be involved in the first step in caprolactam degradation in P. jessenii (Fig. 4a, genes labeled with *). The second gene cluster includes genes involved in the fatty acid β-oxidation, including the caprolactam-induced acetyl-CoA:oxalate CoA-transferase (ORF4277), acetyl-CoA acetyltransferase (ORF4278), 3-hydroxyacyl-CoA dehydrogenase (ORF4279), and butyryl-CoA dehydrogenase (ORF4282). In between these genes, two more open reading frames are located which according to BLAST searches encode for proteins with high homology to an enoyl-CoA hydratase from Mus musculus (ORF4280, 47% identity) and an IclR family transcriptional regulator from Pseudomonas testosteroni (ORF4281, 36%). A similar gene cluster containing homologs of all six genes is present in the genome of other bacteria (e.g., Pseudomonas aeruginosa PAO1), suggesting a wider occurrence of adipate metabolism by the same pathway.

54 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

A

2

B

Fig. 4 Schematic representation of the gene organization of contig 5, containing most of the caprolactam-induced genes, analyzed using the RAST server. A) Gene cluster comprising the genes putatively involved in the conversion of caprolactam to adipate in P. jessenii (Pj), and a similar gene cluster with the genes involved in the conversion of γ-aminobutyrate in E. coli (Ec). Genes marked with an asterisk indicate clear differences between the P. jessenii and E. coli gene clusters. B) Gene cluster comprising the genes putatively involved in the fatty acid β-degradation of adipate. Genes represented in blue: P. jessenii genes encoding proteins that were not significantly upregulated.

ATP-dependent caprolactamase To confirm the presence of an ATP-dependent caprolactamase activity in P. jessenii, a cell- free extract of caprolactam induced cells was prepared. Subsequently, the extract was incubated in the presence of caprolactam, ATP, and MgCl2, and the production of 6-ACA was examined by UPLC-MS. This revealed that caprolactam is indeed enzymatically converted to 6-ACA. When a similar assay was performed using the cell-free extract of glucose-grown P. jessenii cells, no conversion of caprolactam to 6-ACA was detected. This confirmed that the caprolactamase activity present in P. jessenii cells is induced during growth on caprolactam. Additionally, to study the ATP dependence of the putative caprolactamase in P. jessenii cells, cell-free extracts of caprolactam-grown cells containing MgCl2 were prepared and tested for the formation of 6-ACA in the absence of ATP. No 6-ACA formation was detected, demonstrating that ATP indeed is required for the enzymatic hydrolyses of caprolactam to 6-ACA. To confirm the role of the putative caprolactamase (ORF4270, ORF4271) in the conversion of caprolactam, the genes were expressed in E. coli C41. To express both subunits (CapA, CapB) simultaneously, the entire operon including the 36-bp intergenic region (Fig. 4) was cloned under control of a single T7 promoter. Expression in E. coli resulted in the high level production of two proteins of the expected size, of which approximately 60% was present in the soluble fraction. UPLC-MS analysis was performed to detect the formation of 6-ACA in a mixture containing caprolactam, ATP, MgCl2, and

55 CHAPTER 2

E. coli cell-free extract. Time course analyses demonstrated that 6-ACA levels increased and caprolactam levels decreased in time. A specific activity of 0.14 U/mg was calculated for the E. coli cell-free extract (Fig. 5). In reaction mixtures containing caprolactam, ATP,

MgCl2, and E. coli extract from cells not producing the caprolactamase, no detectable 2 6-ACA was observed even after 3 h of incubation. Thus, the caprolactamase activity detected in the induced E. coli (pETOP) extract originates from the expressed α and β subunits of the caprolactamase. Since the sequence of the α and β subunits showed homology to enzymes annotated as 5-oxoprolinase, reaction mixtures containing

5-oxoproline, ATP, MgCl2, and E. coli cell-free extract were tested for the production of glutamate. UPLC-MS analyses demonstrated no detectable glutamate even after 3 h of incubation. This revealed that 5-oxoproline is not a substrate for the identified P. jessenii caprolactamase.

Characterization of the omega aminotransferase Most omega aminotransferases are PLP-fold type I enzymes that catalyze the transfer of an amino group from a β-, γ- or other ω-amino acid or an amine to pyruvate or α-ketoglutarate (37). In order to confirm the presence of 6-ACA ω-aminotransferase activity in P. jessenii GO3, a protein extract of caprolactam-induced cells was prepared and incubated with 6-ACA and pyruvate or α-ketoglutarate, and levels of 6-ACA and produced alanine or glutamate were determined using OPA derivatization and HPLC. This revealed that caprolactam was indeed enzymatically converted with pyruvate as the amino acceptor. In the absence of pyruvate, no conversion of 6-ACA was detected. When a similar assay was performed using cell-free extract of glucose-grown P. jessenii cells, no conversion of 6-ACA or pyruvate was found. This confirmed the presence of a caprolactam-inducible ω-transaminase activity in P. jessenii GO3 cells.

3.0

2.5

2.0

1.5

1.0 Concentration (mM) Concentration 0.5

0.0 0 20 40 60 80 100 120 Time (min) Fig. 5 UPLC-MS analyses monitoring the formation of 6-ACA (black line, triangles) and the degradation of caprolactam (grey line, closed circles). The reaction mixtures contained 2 mM

caprolactam, 5 mM ATP, 10 mM MgCl2 and 75 μg/mL cell-free extract, in 50 mM ammonium bicarbonate, pH 8.5.

56 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

To establish if this ORF4266-encoded putative ω-amino acid aminotransferase (PjAT) is responsible for the conversion of 6-ACA, activity assays were performed using E. coli expressed PjAT. Since E. coli contains multiple aminotransferases, PjAT was equipped with a C-terminal hexahistidine-tag, and the enzyme was purified using a Ni-NTA resin. This yielded ca. 30–35 mg purified enzyme/L of culture. The activity of the enzyme 2 was examined in both directions, so with 6-oxohexanoate or with 6-ACA as substrate, together with L-alanine or pyruvate as amino acceptor. Activities were obtained by coupling the reaction to that of alanine dehydrogenase and following production or consumption of NADH spectrophotometry at 340 nm. This revealed a specific activity of 0.2 U/mg using 6-ACA and pyruvate as the substrates and an activity of 4.5 U/mg using 5-oxohexanoate and alanine as the substrates. These activities would suffice to enable strain GO3 to use caprolactam as a nitrogen source for growth.

DISCUSSION

In this work, we explored the caprolactam degradation pathway in the bacterium P. jessenii strain GO3. Previous studies suggested an overall catabolic pathway for caprolactam metabolism, but the enzymes catalyzing the first two steps, i.e., conversion of caprolactam to 6-oxohexanoate, remained unknown. Using proteomic studies, we identified an ATP dependent lactamase involved in the conversion of caprolactam to 6-ACA and an ω-aminotransferase responsible for the subsequent conversion of 6-ACA to 6-oxohexanoate. Additionally, we identified various other enzymes and genes putatively involved in the caprolactam catabolic pathway. The ATP-dependent lactamase catalysing caprolactam ring opening was identified by proteomic studies, sequence comparison to known proteins with lactamase activity, and functional expression in E. coli. Sequence comparison indicated similarity to proteins annotated as 5-oxoprolinase or hydantoinase. Oxoprolinases catalyze the ATP- dependent hydrolysis of 5-oxoproline to glutamate (EC 3.5.2.9). The sequence of only four oxoprolinases with confirmed activity has been reported, including the enzymes from rat and cow (38, 39), S. cerevisiae (40), and the human enzyme. The latter can harbor mutations of medical relevance (41). The eukaryotic 5-oxoprolinases are homodimers with subunits of approximately 137 kDa, whereas the P. putida 5-oxoprolinase, of which the sequence is not reported, consists of two different subunits of approximately 75 and 63 kDa (42, 43). Subunit A, which is homologous to the N-terminal part of the 137 kDa subunit of the eukaryotic enzymes, catalyzes the phosphorylation of enzyme- bound 5-oxoproline, whereas subunit B, which is homologous to the C-terminal part of eukaryotic oxoprolinase, is required for hydrolysis of the phosphorylated hydroxypyrrole. Other enzymes with significant sequence similarity to the caprolactamase are the ATP- dependent hydantoinases. Only the N-terminal sequences of the two subunits of the

57 CHAPTER 2

enzyme isolated from P. putida 77 have been reported (44), but BLAST searches allow retrieval of complete sequences from Marinobacterium profundum (WP_067296627.1 and WP_067296623.1). Sequence alignments show that in addition to the A and B subunits of the bacterial oxoprolinases mentioned previously, also the A and B 2 subunits of these putative hydantoinases and the α and β subunits of caprolactamase described here correspond to the N-terminal part and C-terminal part, respectively, of the eukaryotic oxoprolinases. All these ATP-dependent hydrolases belong to InterPro families IPR002821 and IPR003692. We demonstrated the ATP dependence of the caprolactamase activity using enzyme expressed in E. coli. Within the families, there are clear differences. For example, the substrate range of the P. jessenii caprolactamase lacks 5-oxoprolinase activity. It seems possible that many bacterial genes annotated in GenBank as 5-oxoprolinase actually are (capro)lactamase genes or cyclic dipeptide hydrolase genes, since there is a higher sequence similarity to the CapA and CapB ORFs than to confirmed oxoprolinases. Based on sequence and structural analysis, these lactamases can be further grouped with the ATP-dependent carboxylases/lactamase superfamily, which includes carboxylases acting on acetone and acetophenone (45). The structure of the acetophenone carboxylase from Aromatoleum aromaticum EbN1 was recently solved (pdb 519w), revealing its quaternary structure as (αα’βγ) 2. Sequence motifs indicative of ATP binding are conserved between the α subunit of the carboxylase and the α subunit of caprolactamase (ORF4270), and the β subunit of the carboxylase is homologous to the β subunit of caprolactamase (ORF4271). Thus, the elucidation of the caprolactam catabolism described here adds a new member to this diverse group of ATP-dependent hydrolytic enzymes. By similarity to oxoprolinase and hydantoinase, caprolactam hydrolysis by the caprolactamase is expected to proceed by phosphorylation of the enol (lactim) tautomer mediated by the α subunit, followed by its hydrolysis with a role for the β subunit. Structures of lactamases that would provide detailed insight are lacking, however. The 6-aminohexanoate aminotransferase (PjAT) catalyzing the second step in caprolactam catabolism was also identified by proteomic studies, sequence similarities, and functional overexpression in E. coli. BLAST searches using the protein sequence of the PjAT demonstrated relatedness to the fold type I PLP enzymes, more in particular to the subgroup II aminotransferases, which are now often grouped as class III aminotransferases (37, 46). These enzymes catalyze conversion of ω-aminoacids to aldehydes (EC 2.6.1.18). In vitro characterization of PjAT confirmed the expected deamination of 6-ACA to 6-oxohexanoate. The enzyme was also active in the reverse reaction: L-alanine-dependent amination of 6-aminohexanoate. This conversion is of potential interest for a biosynthetic 6-ACA production pathway that was recently engineered into E. coli (47). Comparison with the V. fluvialis aminotransferase, which is the closest well studied homolog, revealed conservation of several residues important

58 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS for proper activity (PDB code 4E3Q; (48)). The lysine required for the formation of the internal aldimine (Schiff base) with the PLP cofactor is present at a conserved position. Further work on the biocatalytic and structural properties of the enzyme is ongoing. The PjAT aminotransferase has 27.3% pairwise sequence identity with the NylD1 aminotransferase recently described in the nylon oligomer degrader Arthrobacter sp. 2 KI72 (14). The closest homolog of the latter enzyme in the P. jessenii genome is ORF2380 (48.6% pairwise identity), but an upregulation of this protein was not detected by proteomic analysis of caprolactam-grown P. jessenii cultures. Previously, the full genome of P. mosselii, another caprolactam degrading organism isolated from wastewater of a nylon producing industrial complex in Korea, was sequenced by (27). Interestingly, BLAST searches using the sequences of the genes that were found here to be involved in caprolactam degradation against the full P. mosselii genome sequence revealed genes with high similarity to these proteins (aminotransferase 100%, CapA 99.6%, and CapB 99.3% sequence identity). This suggests the same caprolactam degradation pathways in both Pseudomonas species. Additionally, BLAST searches against the non-redundant protein database revealed highly similar open reading frames in annotated sequences of various other Pseudomonas strains, indicating that the ability to hydrolyze lactams or cyclic peptides may not be unusual in Pseudomonas. Other nylon side products that can be degraded by microorganisms include 6-ACA dimers, cyclic dimers, and oligomers. Metabolism is dependent on hydrolases, such as NylA, NylB, and NylC, which have different specificities (49). NylA catalyzes the hydrolysis of 6-ACA cyclic dimer, resulting in the formation of the 6-ACA dimer, which can be converted by NylB, generating 6-ACA. NylC catalyzes the hydrolysis of 6-ACA oligomers. BLAST searches using Flavobacterium sp. NylA, B, and C revealed that P. jessenii contains homologs of NylA and NylB, but not of NylC, suggesting the absence of a complete pathway for metabolism of 6-ACA polymers.

AUTHOR CONTRIBUTIONS

MO performed the proteomic and genomic studies. MO and CMP performed bioinformatic analysis and expression experiments. MO, CMP and DJ wrote the paper.

59 CHAPTER 2

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60 CHARACTERIZATION OF THE CAPROLACTAM DEGRADATION PATHWAY IN PSEUDOMONAS JESSENII USING MASS SPECTROMETRY-BASED PROTEOMICS

26. Caspi R, Altman T, Billington R, Dreher K, Foerster H, Fulcher CA, Holland TA, Keseler IM, Kothari A, Kubo A, Krummenacker M, Latendresse M, Mueller LA, Ong Q, Paley S, Subhraveti P, Weaver DS, Weerasinghe D, Zhang P, Karp PD. 2014. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/ Genome Databases. Nucleic Acids Res 42:459–471. 27. Park GS, Chu JH, Hong SJ, Kwak Y, Khan AR, Jung BK, Ullah I, Shin JH. 2014. Complete genome sequence of the caprolactam-degrading bacterium Pseudomonas mosselii SJ10 isolated from wastewater of a nylon 6 production plant. J Biotechnol 192:263–264. 28. Boronin AM, Naumova RP, Grishchenkov VG, Ilijinskaya ON. 1984. Plasmids specifying ε-caprolactam degradation 2 in Pseudomonas strains. FEMS Microbiol Lett 22:167–170. 29. Ortet P, Barakat M, Lalaouna D, Fochesato S, Barbe V, Vacherie B, Santaella C, Heulin T AW. 2011. 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61 3Biochemical properties of a Pseudomonas aminotransferase involved in caprolactam metabolism

Cyntia M. Palacio, Henriëtte J. Rozeboom, Elisa Lanfranchi, Marleen Otzen, Dick B. Janssen

Submitted for publication

63 ABSTRACT

The biodegradation of the nylon-6 precursor caprolactam by a strain of Pseudomonas jessenii proceeds via ATP-dependent hydrolytic ring-opening to 6-aminohexanoate. This non-natural ω‑amino acid is converted to 6-oxohexanoic acid by an aminotransferase (PjAT) belonging to the fold type I PLP enzymes. To understand the structural basis of 6-aminohexanoatate conversion, we solved different crystal structures and determined the substrate scope with a range of aliphatic and aromatic amines. Comparison with the homologous aminotransferases from Chromobacterium violaceum (CvAT) and

Vibrio fluvialis (VfAT) showed that the PjAT enzyme has the lowest KM values (highest affinity) and highest specificity constantcat (k /KM) with the caprolactam degradation intermediates 6-aminohexanoate and 6-oxohexanoic acid, in accordance with its proposed in vivo function. Five distinct three-dimensional structures of PjAT were solved by protein crystallography. The structure of the aldimine intermediate formed from 6-aminohexanoate and the PLP cofactor explains the high activity and selectivity of the PjAT with 6-aminohexanoate. The results suggest that the degradation pathway for caprolactam has recruited an aminotransferase that is well adapted to 6‑aminohexanoate degradation.

64 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

INTRODUCTION

Caprolactam is a bulk chemical mostly used for the industrial production of the polyamide nylon 6 (1). This synthetic polymer has found widespread application in various industrial and household products, such as packaging materials, fibers and fabrics, utensils, and mechanical parts. In the nylon 6 manufacturing process, caprolactam undergoes a ring opening polymerization reaction at 240-270°C in the presence of water. After the polymerization process, several undesired side products remain, including the unreacted 3 lactam and 6-aminohexanoate monomers, oligomers, and cyclic dimers (2). Caprolactam and its side products should be removed before waste or wastewater is discharged into the environment, since release into natural water streams will threaten environmental quality and public health. To understand the environmental fate of nylon-related compounds and their biodegradation, several studies have been carried out aimed at isolating microorganisms that metabolize caprolactam and 6-aminohexanoate (cyclic) oligomers (3-6). Some of these strains contain plasmids that harbour genes involved in caprolactam utilization, including genes encoding 6‑aminohexanoate dimer hydrolase and 6-aminohexanoato cyclic dimer hydrolase, which are responsible for hydrolysis of amide bonds (5-7). Whereas a complete degradation pathway is also suggested in the MetaCyc database (see URL http://MetaCyc.org) (8), most enzymes of the caprolactam catabolic route remained unidentified until two rather different aminotransferases that may catalyze 6-aminohexanoate deamination were recently discovered (9,10). Our lab described the caprolactam-utilizing bacterium Pseudomonas jessenii strain GO3, which produces an ATP-dependent lactamase that converts caprolactam to 6-aminohexanoate. This intermediate is converted by an aminotransferase that transfers the amino group to pyruvate and produces 6-oxohexanoic acid, which can be metabolized by β-oxidation via formation of adipic acid (10) (Fig. 1). Aminotransferases (ATs) are pyridoxal 5’-phosphate (PLP)-dependent enzymes that catalyze the transfer of an amino group from a donor (e.g. an amino acid or amine) to an acceptor, which in vivo is most often pyruvate or 2‑oxoglutarate (13,14). After binding of the substrate, its amino group is transferred to the PLP cofactor via formation of an imine (external aldimine) and proton shift, leading to a pyridoxamine (E∙PMP) intermediate. Following release of the deaminated product as a ketone or aldehyde, the enzyme binds the ketoacid acceptor and the amino group of PMP is transferred to this acceptor, again via imine formation and proton shift. The aminated product is released by cleavage of the Schiff base linkage under regeneration of enzyme-bound PLP. Based on crystal structures, PLP-dependent enzymes have been divided into different fold types, which to a certain extend correlates to reaction type or substrate scope (15-17).

65 CHAPTER 3

3

Fig. 1. Nylon 6, nylon 6-oligomer and caprolactam biodegradation. The catabolic pathways of 6‑amino­hexanoate (cyclic) dimers and oligomers (11,12) and the route of caprolactam degradation in P. jessenii (10) converge to 6-aminohexanoate, which is deaminated in P. jessenii by the aminotransferase described here.

Aminotransferases often belong to fold type I or fold type IV PLP enzymes (14-18). Examples of well-studied fold type I aminotransferases are L-aspartate ATs (19), branched L-amino acid ATs, β-amino acid ATs (20,21) and the ω-aminotransferases (ωATs) from Vibrio fluvialis, Chromobacterium violaceum, Paracoccus denitrificans, and Ochrobactrum anthropi (22-26). Fold type IV enzymes include D-amino acid ATs and (R)-amine selective ωATs (13-16,27,28). Aminotransferases have also been classified in subgroups or classes, mainly based on substrate structural features, leading to a classification that partially agrees with grouping in fold types (15,17). The subgroup AT-I aminotransferase are active

66 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM with α-amino acids and thus include the PLP fold type I aspartate ATs and branched L-amino acid ATs. The original AT-II subgroup (15), later also called class III ATs, includes ω-aminotransferases, i.e. enzymes active on non-α-amino acids (17). The sequence suggests that the P. jessenii strain GO3 aminotransferase (PjAT) of the caprolactam catabolic pathway is most similar to these class III ATs (10), of which structures and sequences have been compared in detail (17,25). Aminotransferases offer a diversity of realized and potential biotechnological applications. They usually have a high catalytic activity and do not require an external 3 redox cofactor recycling system if an organic amine is used as the donor (22,29-32). Process conditions for amination reactions catalyzed by enzymes are milder than in case of chemocatalytic incorporation of amine groups, which can make the use of aminotransferases attractive from an environmental point of view (33). Of particular interest is the production of chiral amines by asymmetric transformation of non- chiral keto-precursors. In such reactions, aminotransferases often show high regio-, enantio-, and chemoselectivity. Other attractive reactions are the terminal amination of aldehydes to produce amines, either in cascade conversions with free enzymes starting with ammonia and alcohol or by employing reactions with whole cells (34,35). Recent work indicates that aminotransferases can be important for constructing artificial biosynthetic pathways, even leading to the biosynthesis of non-natural amines such as 6-aminohexanoate (6-AHA), the precursor of caprolactam (36). To discover an aminotransferase involved in caprolactam metabolism and examine its potential use in various enzymatic transformations of biotechnological interest, we investigated the caprolactam degradation pathway of P. jessenii GO3, using a proteomic and genomic approach (10). The aminotransferase (PjAT) present in this strain acts in a catabolic pathway that involves compounds that are only known from chemical synthesis. The enzyme is examined here addressing the question if the enzyme is evolved to deaminate 6-aminohexanoic acid, a synthetic amino acid. The substrate range is determined and compared to that of related enzymes. We solved several crystal structures to explain the activity towards the biologically unknown substrate 6-AHA. We also examined the activity in the amination of 6-oxohexanoic acid and interpret the selectivity using 3D structures.

MATERIALS AND METHODS

Substrates and chemicals Nicotinamide adenine dinucleotide (NAD) and alanine dehydrogenase from Bacillus cereus (BcAlaDH) were purchased from Sigma-Aldrich. Pyridoxal phosphate (PLP) was purchased from Fisher Scientific. Potassium phosphate dibasic trihydrate and potassium phosphate monobasic were obtained from Merck. The substrates 6-aminohexanoato,

67 CHAPTER 3

5-aminopentanoic acid, 1-aminopentane, 4-aminobutanoic acid, L-lysine, glycine, (S)- (-)-α-methylbenzylamine, benzylamine, 2-phenylethylamine, 4-phenylbutylamine, 3-phenylpropylamine were purchased from Sigma-Aldrich. We synthesized 6-oxohexanoic acid as described by Bouet et al. (56).

Enzyme expression and purification The isolation and characterization of P. jessennii strain GO3 was recently described by 3 Otzen et al. (10). Its 6-aminohexanoate aminotransferase was produced in E. coli strain Top10 using the PjAT gene cloned in frame downstream of the hexahistidine tag sequence in expression vector pET20b(+). The coding sequence was obtained by PCR amplification of genomic DNA extracted from strain GO3. Derivatives of the expression vector pET28b(+) containing an in-frame fusion of the C. violaceum aminotransferase (CvAT, NP_901695) or the V. fluvialis aminotransferase (VfAT, AEA39183) were described by Palacio et al. (34). The ω-aminotransferases PjAT, CvAT and VfAT were expressed in E. coli strain C41 and purified to homogeneity using His-tag metal affinity chromatography followed by a desalting step, as described earlier (34).

Activity assays The activities of PjAT, CvAT and VfAT coupled to pyruvate amination were measured using an indirect assay by following alanine-dependent reduction of NAD+ by alanine 3 -1 ‑1 dehydrogenase at 340 nm (εNADH = 6.22×10 M ∙cm ) (57). Excess alanine dehydrogenase from B. cereus (BcAlaDH) was added to the reaction mixtures to ensure that the rate- limiting step is the transamination reaction. The pyruvate concentration was optimized to ensure high BcAlaDH activities and a minimal lag phase. The reaction mixtures contained variable concentrations of substrate, 2 mM NAD+, 0.05 mM PLP, 5 U/ml BcAlaDH, 0.015 mg/ml aminotransferase and 0.2 mM pyruvate in 100 mM potassium phosphate, pH 8. Assays were performed in flat-bottomed 96-well microtiter plates. The absorbance at 340 nm was monitored during 30 min at 30°C using a microtiter plate reader (Synergy Mx Microplate Reader, BioTek Instrument, Winooski, USA). The plates were pre-warmed and reactions were started by addition of 150 µl of 0.4 mM pyruvate solution to 150 μl reaction mixture. All assays were done in triplicate. The initial rates of the reduction of NAD+ observed with different substrate concentrations were used to determine the kinetic constants. Specific activities are expressed in units per mg of protein (µmole·min-1·mg-1). Amination of 6-oxohexanoic acid was also measured using the coupled assay, i.e. by following the pyruvate-dependent oxidation of NADH by alanine dehydrogenase. The reaction mixtures contained 100 mM potassium phosphate buffer (pH 8), 2 mM substrate, 0.1 mM NADH, 0.05 mM PLP, 8 U/ml BcAlaDH, 5 mM ammonium bicarbonate, 5 mM L-alanine and varying concentrations of substrate in a total volume of 300 μl. Reactions were initiated by addition of L-alanine and carried out as described above.

68 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

Crystallization and X-ray data collection The protein was concentrated to 10.5 mg·ml-1 in 25 mM HEPES buffer pH 7.5 using a Vivapsin Turbo 4 30K filter unit (Sartorius). Initial vapour diffusion crystallization experiments were performed using a Mosquito crystallization robot (Molecular Dimensions Ltd, Newmarket, England). Various commercially available crystallization screens were used, e.g. JCSG+ and PACT (Qiagen Systems, Maryland, USA) and Cryo (Emerald Biosystems, Bainbridge Island, USA). PjAT crystals were obtained at room temperature from succinate and ammonium phosphate (both pH ~7.5) solutions. Optimization of the crystallization 3 conditions yielded well-diffracting colourless crystals that grew within a few days when 1 µl protein solution (7.5 mg·ml-1) was mixed with 1 µl reservoir solution containing 0.7- 1.0 M ammonium phosphate or succinate, pH 7.3. Yellow PLP-containing protein crystals could be grown by first incubating PjAT with 0.1 mM fresh PLP for a few hours and using succinate as precipitant. Before data collection, crystals were briefly soaked in a cryoprotectant solution consisting of 30% glycerol and 1.2 M succinate, pH 7.5, in 30 % glycerol and 1.2 M ammonium phosphate, pH 7.5, or in 30% glycerol, 1.2 M succinate and 0.1 mM PLP. The ligand complexes were obtained by soaking a PLP-containing crystal in succinate solution containing 0.4 M 6-AHA or (S)-(-)-α-methylbenzylamine ((S)-MBA) for 30 s and then briefly soaked in cryoprotectant including 6-AHA or S( )-MBA. X-ray diffraction data were collected with an in-house MarDTB Goniostat system using Cu-Kα radiation from a Bruker MicrostarH rotating-anode generator equipped with HeliosMX mirrors at 100 K. Intensity data were processed using XDS (58) and the CCP4 package (59). The space group was P43, with unit cell dimensions of a = b = 98.4 Å and c = 119.3 Å. With two PjAT 3 monomers of 50 kDa in the asymmetric unit, the VM is 2.9 Å /Da (60) with a calculated solvent content of 57%. Using the FFAS03 server (61) and SCWRL (62), a homology model for PjAT was generated. Molecular replacement was performed with PHASER (63). Phenix Phase and Build (64) was used for automatic building and COOT (65) was used for manual rebuilding and map inspection. The model was refined with REFMAC5 (66) with local NCS restraints and with TLS rigid body refinement as the last step, resulting in a final model comprising 2 protein molecules forming a homodimer. No significant conformational changes are observed between native and ligand bound enzymes. The Cα atoms of all five models superimpose with root mean square deviations of 0.1-0.2 Å. The quality of the models was analyzed with MolProbity (67). Figures were prepared with PyMOL (68) and ESPript (69).

Accession numbers Atomic coordinates and experimental structure factor amplitudes are accessible under entry code PDB ID codes 6G4B for ωAT-succinate, 6G4C for ωTA-AmPhos, 6G4D for ωAT- PLP, 6G4E for ωAT-PLP-6ACA/PLP and for ωAT-PMP/PLP.

69 CHAPTER 3

RESULTS

Catalytic properties of P. jessenii 6-aminohexanoate aminotransferase To overproduce the recently discovered P. jessenii aminotransferase involved in the caprolactam degradation pathway (10), we used a pET-based expression vector and E. coli strain Top10. After overnight growth under inducing conditions, a high-level expression of soluble enzyme was reached. Preparation of cell lysate by sonication, centrifugation and 3 enzyme isolation by His-tag Ni-affinity chromatography yielded 34 mg of purified protein per l L of culture. This material was used for activity profiling and cystallography. The enzyme showed activity towards 6‑aminohexanoate (6-AHA) and 6‑oxohexanoic acid, the aminated and deaminated intermediates of the caprolactam and 6-aminohexanoate oligomer degradation pathways (Fig. 1). With 2 mM 6‑aminohexanoate and pyruvate as amino donor, an activity of 2 U/mg was found for the purified enzyme. Compounds such as amino acids, aliphatic amines and aromatic amine compounds are of interest for the production of various pharmaceuticals, paintings, and crop protectants (37,38). Therefore, specific activities ofPj AT were measured using 33 different amine substrates, including aromatic compounds, linear aliphatic compounds, and amino acids (Table 1). This activity screening was performed with spectrophotometric coupled- enzyme assays in which aminotransferase-mediated formation of L‑alanine from pyruvate and 6-aminohexanoate was coupled to alanine dehydrogenase-mediated production of NADH. Data were compared to values measured with the aminotransferases from V. fluvialis (VfAT, 42% sequence identity) and C. violaceum (CvAT, 40% sequence identity). The results (Table 1) showed that the PjAT enzyme, as well as CvAT and VfAT, had the highest specific activities with aromatic compounds carrying the amine functionality on short aliphatic side groups: (S)-α-methylbenzylamine ((S)-MBA) and benzylamine. For the latter two enzymes this is in agreement with Kaulmann et al. (24) and Shin and Kim and coworkers (39,40) who also observed that activities of CvAT and VfAT with benzylamines were higher than with aliphatic amines. Nevertheless, several aliphatic amines and the ω-amino acids 4-aminobutanoic acid, 5-aminopentanoic acid and the obvious “natural” substrate 6-AHA also gave good activities, especially with PjAT and CvAT. Glycine and most other α-amino acids tested were not converted. We found that also CvAT had high activity with 6-AHA, higher than found earlier (24). Primary phenylalkylamines with longer aliphatic groups were also converted well by all three enzymes. Some of the tested compounds were a poor substrate for all three ATs examined. Different β‑amino acids were tested, including β-alanine, but none was converted by any of the enzymes (Table 1). This clearly distinguish these aminotransferases from the homologous PLP fold-type I β-amino acid aminotransferases discovered in bacterial cultures enriched with β-Phe as growth substrate (20,21,41). Poor substrates also include compounds with bulky substituent as 3-fluorobenzylamine (Table 1). Likewise, no significant conversion by CvAT and VfAT of proteinogenic amino acids other than L-Ser and L‑Ala was found, in agreement with Kaulman et al. (24) and Shin et al. (42).

70 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

Table 1. Activities of PjAT, CvAT, and VfAT. a

Sp. act. (%) Name Structure PjAT CvAT VfAT

b b 100 (S)-α-Methylbenzylamine 100 (0.8) 100 (1.6) (1.0)b

6-Aminohexanoic acid (6-AHA) 100 180 35 3

5-Aminopentanoic acid 95 93 4

4-Aminobutanoic acid 129 174 70

1-Aminopentane 63 209 91

Benzylamine 208 406 208

2-Phenylethylamine 28 201 106

3-Phenylpropylamine 25 77 60

4-Phenylbutylamine 99 145 28

3-Fluorobenzylamine 75.5 82.3 53.6

4-Fluorobenzylamine 67.2 94.8 78.7

L-Serine 3.1 10.7 3.8

L-Leucine <1 4.7 18.6 a Reaction conditions: 15 mM of substrate, 0.2 mM pyruvate, 0.05 mM PLP, 2 mM NAD, 5 U/ml alanine dehydrogenase, and 0.015 mg/ml CvAT, VfAT or PjAT, 30˚C, in 100 mM potassium phosphate, pH 8. Substrates for which no or very low activity was detected included 2-(2-butoxyethoxy)ethanamine, 2‑aminooctanoic acid, 1-butoxy-2-propanamine, (S)-3-amino- 3-phenylpropanoic acid ethyl ester, (S)‑3-amino-3-(p-hydroxyphenyl)propionic acid, serine, L-tyrosine, L-phenylalanine, ornithine, L-valine, L-aspartate, L-glutamate, L-triptophane, L-alanine, β-phenylalanine, and β-tyrosine. b Activities are expressed as % of the activity found with (S)-α-methylbenzylamine. Values in parenthesis represent specific activities of the three aminotransferases with (S)-α-methylbenzylamine.

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To further examine the apparent activity differences, kinetic studies were performed with the aminated substrates that gave the best activities as well as with 6‑oxohexanoate, the direct deamination product of 6-AHA in the caprolactam degradation pathway (Table 2). The results revealed that of the three enzymes PjAT has the highest affinities for 6-AHA

and 6-OHA, with apparent KM values that were at least 7-fold lower for the amine substrate and 33-fold lower in case of the aldehyde when compared to values for CvAT and VfAT.

The kcat values, on the other hand, were highest for CvAT, but the physiologically most

3 relevant kcat/Km value was best for PjAT, in accordance with its function in caprolactam

degradation. Interestingly, PjAT had a lower apparent KM with 6-OHA than with the amine donor 6-AHA, indicating that the enzyme might be used for aldehyde amination, a reaction of importance for caprolactam production by metabolically engineered E. coli (36). At high substrate concentrations, however, substrate inhibition was observed with all three enzymes when using the aldehyde as amine acceptor. The results with other substrates confirmed that aryl-substituted alkylamines were well accepted by the three ω‑aminotransferases (Table 2). With all amino compounds

the highest kcat values were observed with CvAT, which was also found by Kaulmann et al. (24) when comparing CvAT and VfAT. Regarding affinities, it appeared that PjAT, which displayed the highest affinity for 6‑AHA, showed the poorest affinity in case of

the aromatic substrates. This gave a preference for 6‑AHA, expressed as ratio of kcat/Km values that was 2- and 25-fold better for PjAT compared to CvAT and VfAT, respectively. The high substrate affinity of PjAT was not only found with 6-AHA; also the shorter

ω-amino acids 5-aminopentanoic acid and 4-aminobutanoic acid gave Km values that were at least 6-fold better in case of PjAT. The carboxylate group of the ω-amino acids seems to favor PjAT, since the higher affinity of this enzyme for ω-amino acids was not observed with other amines, such as 1‑aminopentane and 2‑phenylethylamine. Substrate inhibition was also observed with most of the aromatic compounds tested, with the exception of 2‑phenylethylamine. This type of inhibition is in line with previous reports demonstrating that aminotransferases are inhibited by high concentrations of an aromatic substrate (39). It is likely due to binding of the amine substrate to the pyridoxamine intermediate rather that binding of the oxo-substrate that accepts the amine group. Summarizing, the kinetic properties indicate that PjAT is a more suitable catalyst for 6-AHA deamination than CvAT or VfAT in case of low substrate concentrations. This raises the question if the substrate’s carboxylate group located 5 carbons away from the reacting amine is involved in binding to the enzyme and in any evolutionary adaptation of PjAT to 6‑amino­hexanoate conversion.

72 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

Table 2. Steady state kinetic parameters of the aminotransferases for linear aliphatic and aromatic substrates.a

k /K Entry Substrate Enzyme K (mM) k (s-1) K (mM) cat M M cat i (mM-1.s-1)

Caprolactam metabolism intermediates 1 6-Aminohexanoate PjAT 1.54 ± 0.01 0.3 ± 0.1 0.2 2 CvAT 10.6 ± 0.4 0.95 ± 0.02 0.09 3 VfAT 71 ± 2 0.58 ± 0.01 0.008 3 4 6-Oxohexanoateb PjAT 0.06 ± 0.01 5.4 ± 0.1 12.6 ± 0.6 89 5 CvAT 2.8 ± 0.9 11 ± 2 3.3 ± 0.9 3.8 6 VfAT 2 ± 0.2 1.8 ± 0.1 11 ± 1 0.9 Linear aminated substrates 7 5-Aminopentanoic acid PjAT 0.9 ± 0.1 0.21 ± 0.01 0.2 8 CvAT 9.8 ± 0.4 0.35 ± 0.01 0.04 9 VfAT 8.2 ± 1.3 0.02 ± 0.01 0.003 10 4-Aminobutanoic acid PjAT 2.1 ± 0.1 0.26 ± 0.01 0.1 11 CvAT 2.3 ± 0.1 0.55 ± 0.01 0.2 12 VfAT 8.9 ± 0.4 0.3 ± 0.1 0.03 13 1-Aminopentane PjAT 8.5 ± 0.5 0.18 ± 0.01 0.02 14 CvAT 5.7 ± 0.5 1.1 ± 0.1 117 ± 27 0.2 15 VfAT 7.2 ± 0.7 0.6 ± 0.1 64 ± 13 0.08 Aromatic aminated substrates 16 Benzylamine PjAT 1.8 ± 0.2 0.75 ± 0.04 42 ± 7 0.4 17 CvAT 1.0 ± 0.1 1.6 ± 0.1 18 ± 2 1.6 18 VfAT 0.61 ± 0.04 0.74 ± 0.02 >200 1.2 19 (S)-α-Methylbenzylamine PjAT 2.1 ± 0.2 1.1 ± 0.1 22 ± 2 0.5 20 CvAT 1.3 ± 0.1 2.3 ± 0.1 59 ± 7 1.7 21 VfAT 1.1 ± 0.1 1.6 ± 0.1 151 ± 38 1.5 22 2-Phenylethylamine PjAT 81 ± 6 0.75 ± 0.04 0.009 23 CvAT 5 ± 0.1 0.72 ± 0.01 0.2 24 VfAT 3.6 ± 0.1 0.3 ± 0.1 0.08 25 3-Phenylpropylamine PjAT 2.4 ± 0.2 0.13 ± 0.01 44 ± 6 0.05 26 CvAT 1.7 ± 0.1 0.38 ± 0.01 46 ± 4 0.2 27 VfAT 0.77 ± 0.04 0.21 ± 0.01 0.3 27 4-Phenylbutylamine PjAT 1.5 ± 0.1 0.3 ± 0.1 >200 0.2 28 CvAT 0.56 ± 0.04 0.43 ± 0.01 >100 0.8 29 VfAT 0.71 ± 0.05 0.1 ± 0.01 0.1 a Reactions with amine donors were carried out in triplicate with varying substrate concentrations (0.1-90 mM), 0.2 mM pyruvate, 0.05 mM PLP, 5 U/ml alanine dehydrogenase, and 0.015 mg/ml CvAT, VfAT or PjAT at 30˚C in 100 mM potassium phosphate, pH 8. b Substrate amination reactions were carried out in triplicate with 0.08-32 mM 6-oxohexanoate, 0.05 mM PLP, 0.1 mM NADH, 5 mM L-alanine, 5 mM ammonium bicarbonate, 8 U/ml BcAlaDH, and 100 mM potassium phosphate buffer, pH 8, at 30˚C.

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Crystal structures The structure of PjAT was determined by protein crystallography using molecular replacement and refinement against 1.80 Å resolution diffraction data to an R-factor of 0.141 (Rfree = 0.166) with good stereochemistry (Table S1, Fig. 2). The protein is composed of two subunits forming a tight homodimer with an interface score calculated by PISA of 0.92 (http://www.ebi.ac.uk/msd-srv/prot_int/cgi-bin/piserver). The dimeric PjAT molecule has dimensions of 100 x 60 x 55 Å. The PjAT structure is very similar to the 3 structures of other PLP fold type I enzymes belonging to the ω-aminotransferases, with DALI Z-scores over 20, rmsd values ~ 0.8-1.2 Å and sequence identities of 40- 63%. These include the ω-aminotransferase from Ochrobactrum anthropi (OaTA, PDB code 5GHF, 63% identity (26)), the putative aminotransferase from Mesorhizobium loti maff303099 (3GJU, JCSG), the putative aminotransferase from Silicibacter sp. TM1040 (3FCR, JCSG), the aminotransferase from Silicibacter pomeroyi (3HMU), the ω-amino­ transferase from Paracoccus denitrificans (PdTA, 4GRX (25)), the two ω‑aminotransferases included in the above activity profiling Cv( AT, 4A6T and 4BA5 (43,44) and VfAT, 4E3Q (45) and 3NUI (unpublished)) (Fig. 3). Interestingly, only 32% identity is observed with the Pseudomonas aeruginosa ω-aminotransferase (4B9B (44)) and the Pseudomonas putida ω-aminotransferase (3A8U, unpublished). All these PLP fold type I aminotransferases group into clade 6c of the class II/III ATs, most of which are dimeric ωTAs with subunits consisting of two domains (25). The smaller domain of PjAT comprises residues 1 to 66 and 346 to 456. The large domain comprises residues 67 to 345 and contains most of the conserved residues, including residues that form the cofactor binding site. PjAT shows only low similarity (27% identity) to the aminotransferase that was proposed by Takehara et al. (9) to be involved in 6-aminohexanoate degradation by Arthrobacter sp. KI72. The PLP-binding pockets of PjAT are located at the dimeric interfaces and contain residues from both subunits. In the succinate and ammonium phosphate-grown crystals, a succinate or a phosphate ion, respectively, occupy the position of the phosphate moiety of the PLP in the homologous structures. The phosphates are located 15.5 Å from each other. The phosphate ion is hydrogen bonded to the backbone amides of Gly118 and Ser119, the backbone amide and sidechain of Thr324’, and five water molecules (Fig. 4A) and has an equal position as a sulfate ion in the Silicibacter structure (PDB 3HMU). The succinate molecule has the same interactions, including hydrogen bonds to the side chains of Ser286 and Lys287, to a water molecule and to a glycerol molecule (Fig. 4B). This glycerol molecule has hydrogen bonds to the carbonyl atoms of Asn116, Pro295 and to the carbonyl and side chain oxygens of Ser286. The glycerol occupies a small pocket shaped by Asn116, Ser292, Pro295 and Gly325’. In CvAT and Silicibacter AT this pocket is occupied by a side chain of a Tyr, while it also exists in VfAT.

74 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

3

Fig. 2. Crystal structure of Ps. jessenii aminotransferase. One subunit is colored in red/blue/ grey and the other in green. The external aldimines of PLP bound to 6-aminohexanoate in both subunits are shown as yellow spheres. Residues from both subunits contribute to each active site.

The PLP-binding pockets are well conserved between PLP fold type I class II or class III ATs (46). For the PjAT-PLP structure, 2Fo-Fc and Fo-Fc maps showed density extending continuously from the side chain of Lys287, which was modelled as the internal aldimine adduct of PLP (Fig. 5A). The phosphate moiety is bound identically as in the ammonium phosphate grown crystals. The pyridine ring is sandwiched between the perpendicular ring of Tyr151 and the isopropyl group of Val260. The nitrogen of the ring has interaction with the side chain of Asp258. Additional density was observed close to the PLP. This was modelled as a glycerol and has interaction with the ε-amino group of the catalytic Lys287, and side chains of Trp58, Tyr151, Ala230 and Arg417. Its position is different from the glycerol in the succinate experiment, being at the other side of Thr324’ at ~8 Å distance. The latter pocket is filled with water molecules in the PjAT-PLP structure.

75 CHAPTER 3

3

Fig. 3. Structure–based sequence alignment of eight PLP fold type I class III aminotransferases. Displayed are the sequences of PjAT from P. jessenii, OaAT from Ochrobactrum anthropi (5GHF, (26)), a putative AT from Mesorhizobium loti maff303099 (MlAT, 3GJU, JCSG), ω-AT from Paracoccus denitrificans (PdAT, 4GRX, (25)), VfAT from V. fluvialis (4E3Q, (45)), AT from Silicibacter pomeroyi (SpAT, 3HMU, NYSGXRC), a putative AT from Silicibacter sp. TM1040 (SiAT, 3FCR, JCSG), and CvAT from C. violaceum (4A6R, (47)). The structural alignment was made with EndScript (48). The secondary structure elements above the sequence alignment are obtained from the crystal structure of PjAT. Identical residues have a red background color and similar residues have a red color. Residues with a purple color are the catalytic lysine and with a green color line the active site. The figure was created with ESPript (48).

76 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

3

Fig. 4. Active site structure of PjAT. A) Binding of a phosphate ion (in orange) in ammonium phosphate-grown crystals. B) Binding of a succinate molecule (in orange) in the phosphate binding site. The glycerol molecule (in pink) occupies a small pocket. The residues forming the active site are displayed as sticks in cpk colors, Lys287 in green, Thr324’ from the other subunit in dark green. Waters are depicted as red spheres. Hydrogen bonds are shown as dotted lines with indicated distances in Å. Ser292 shows a double conformation.

Fig. 5. Structures of the active site of PjAT with PLP in different forms. A) Internal aldimine with PLP (yellow) bound to the ε-nitrogen of Lys287 (light green) as a Schiff base. B) Structure of the 6-AHA–PLP (yellow-magenta) external aldimine adduct, with Arg417 forming a bidentate salt bridge to the carboxylate of 6-AHA. Residue Met419 presents a double conformation. C) PLP in the pyridoxamine (PMP) form after reaction with (S)-MBA. Residues forming the active site are displayed as sticks in cpk colors, Lys287 in green, Phe86’ and Ser87’ from the other subunit in dark green and the glycerol molecule in cyan. Hydrogen bonds are shown as black lines and interactions between Lys287 and the amine nitrogen with gray lines (shown by black arrows) and with indicated distances in Å.

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Electron density maps of the PjAT-PLP crystal soaked with 6-AHA showed discontinuous residual density in subunit A between the ε-amino group of Lys287 and PLP. Instead, additional density extending from the PLP carbonyl carbon was observed. This was modelled as the 6-AHA–PLP external aldimine adduct (Fig. 5B). In subunit B the unreacted internal aldimine was observed. The structure of the 6-AHA derived external aldimine revealed that the tunnel-like active site is shaped by several mostly hydrophobic residues from the A and B subunits. Tyr20, Met54, Leu57, Trp58, Tyr151, Leu164, Ile261, Ala230, 3 Arg417, Met419, Phe86’, Ser87’ and Ala318’ provide a rather nonpolar active site. Upon binding of 6-AHA, Met419 obtains a double conformation with a new conformation pointing toward the substrate (Fig. 5B). This extra position is possible by a switch of the side chain of Arg417, which is very mobile and adopts a different conformation in all five determined structures. This Arg is highly conserved residue in ATs and binds the α-carboxylic group of the substrate, e.g. the α-keto acceptor. The flexibility of Arg417 can also be inferred from its elevated B-factors and is observed in other ATs as well (25,44,47). In the 6-AHA aldimine adduct of PjAT, Arg417 forms a bidentate salt bridge with the carboxylate of 6-AHA through the Nε and Nη of the Arg417 side chain (3.8 and 3.7 Å distance), and there is an additional hydrogen bond of one of the carboxylate oxygens with the indole nitrogen of Trp58 (3.7 Å). Other contacts between substrate and enzyme are mainly hydrophobic, through the sidechains of Tyr20, Leu57, Phe86’ and Tyr151 (Fig. 5B). In electron density maps of the crystal soaking experiment with (S)-MBA, PMP was observed, but no density for (S)-MBA emerged in subunit A, showing that the first half- reaction has been completed (Fig. 5C). In subunit B the internal aldimine was observed similar to the complex found in the 6-AHA binding study.

Fig. 6. Overlay of the active sites of PLP-bound forms of PjAT, OaAT, CvAT and VfAT in stereo view. PjAT in gray, with internal aldimine complex in yellow, OaAT PMP bound form (PDB code 5GHF) in green, CvAT PLP bound form (4AH3) in cyan (with R416 in double conformation) and VfAT in the PMP bound form (4E3Q) in magenta. Only residues that differ and the flexible arginine are shown.

78 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM

The structures determined of PjAT resemble best the complex structures of OaAT (5GHF), of CvAT with PLP bound (PDB 4A6T) and with gabaculine-PLP (m-carboxyphenyl pyridoxamine phosphate) (4BA5) (26,43,44). The results provide no indication of a major conformational change upon substrate binding since the structures of PjAT with PLP, PMP, phosphate, succinate, and the external aldimine formed with 6-AHA were very similar, as also observed in the P. aeruginosa transaminase (44). However, conformational changes upon binding of a phosphate or phosphate mimic of several loops involved in structuring the active site may be possible in ATs, like displayed in CvAT (43,47). A 3 conformational change associated with substrate binding likely is not necessary in PjAT since Ser87, opposite to Arg417 in the active site, which is also a Ser in OaAT but a Phe in the other homologous enzymes (Fig. 4 and Fig. 6), leaves enough space for the repositioning of Arg417 and for substrate binding.

DISCUSSION

The recently identified P. jessenii ω-transaminase, involved in the degradation of caprolactam, was studied after expressing the enzyme in E. coli by measuring substrate selectivities and examining various crystal structures. The sequence and the structure indicate that the enzyme is a class II/III aminotransferase of fold type I superfamily of PLP enzymes. To examine if and why the enzyme shows exceptional activity with 6-AHA and 6-OHA, which are intermediates of the caprolactam degradation pathway, activities were measured with a range of substrates, and compared to those found with well- characterized ω-aminotransferases from C. violaceum and V. fluvialis. The results showed that at low concentrations 6-AHA and 6-OHA are better substrates for the new PjAT as compared to the reference ω-ATs, suggesting that the enzyme is indeed evolved for efficient deamination of the 6-AHA intermediate formed by enzymatic ring opening of caprolactam. The specificity constant (kcat/KM) found with 6-AHA was 2-20 fold better for

P. jessenni enzyme, mainly due to the much higher KM in case of VfAT and CvAT. The same is found for the aldehyde 6-OHA: the kcat/KM is at least 25-fold better in case of PjAT than with the other ATs and the kcat/KM with 6-OHA is also at least 40-fold better than that with all the other tested amine substrates. In vivo levels of intermediates formed during caprolactam metabolism are unknown and may vary, but at high concentrations the aldehyde may be inhibitory for all three enzymes, as indicated by substrate inhibition. In aminotransferase, substrate inhibition may be due to binding of the acceptor aldehyde to the PLP form of the enzyme in competion with the amine donor. Similarly, substrate inhibition by the amine donor may be due to binding to the PMP form of the enzyme (39,40). These circumstances make it difficult to assess the relevance of the differences in kinetic constants for growth kinetics, but the structural studies provided further indications for a dedicated role for the PjAT enzyme in 6-AHA metabolism. This role is

79 CHAPTER 3

in agreement with the upregulation of PjAT found in proteomics experiments by Otzen et al. (10) when comparing cells cells growing on caprolactam as compared to controls growing on glucose and ammonia. Comparison of the crystal structures of PjAT, CvAT and VfAT and the recently solved structure of O. anthropi ω-aminotransferase (OaAT) showed that both the overall structures and the active sites are well conserved. Differences can be observed in the Gly166-Asn167 (PjAT) loop which approaches the active site in PjAT and OaAT whereas 3 in the corresponding regions of CvAT (Tyr168-Me169) and VfAT (Tyr165-Asn166) the backbone structure is further outward (Fig. 6). The distance of the Tyr-OH to the flexible arginine is about 7 Å in VfAT and CvAT, while the shortest distance from Asn167 to the 6-AHA substrate in PjAT is 6.5 Å. These distances are too long for any interaction. Another difference is the presence of Tyr20 in PjAT and OaAT, which is hydrogen bonded to the Asn in the Gly166-Asn167 loop. There is a Phe at this position in the other two ATs, making the subsite in PjAT smaller and a bit more polar. Further comparison of the active sites suggest a cause of the better recognition of 6-AHA by PjAT. In VfAT, CvAT and other ω‑amino­transferases a Phe is conserved at position 87, whereas a Ser is present in PjAT and the more similar OaAT. The smaller Ser facilitaties an outward motion of Arg417 that leads to a hydrogen bonding interaction with the terminal carboxylate of 6-AHA, rather than a collision. In line with this finding, previous studies using VfAT revealed that its substrate scope can be altered by mutagenesis of the active site. Cho et al. (48) demonstrated that the substitution of the conserved Trp57 and 147 with a Gly residue enabled VfAT to accept longer aliphatic chain substrates, and Arg415 is replaced in several protein engineering studies (45,51-55). The creation of space that allows outward movement of Arg417 by the Phe to Ser substitution at position 87 in PjAT, which in turn makes space for the 6-ACA carboxylate, may be one of the adaptations of the enzyme to a role in caprolactam metabolism. Substrate scope analyses and kinetic studies have shown a preference of the three aminotransferases examined here towards aromatic substrates. This is in line with previous studies using CvAT and VfAT (24,41). Interestingly, PjAT revealed lower catalytic efficiency towards the linear substrate 1-aminopentane in comparison to 4-aminobutanoic acid. The carboxylate group in the latter substrate will also be recogized by the flexible Arg417 (54), allowing better substrate binding. In contrast, VfAT and CvAT showed the best activity with 1-aminopentane in comparison with the other linear amines tested. As mentioned, in PjAT residue Ser87 replaces a phenylalanine in CvAT and VfAT, therefore Arg417 is in a more polar environment and the combined effect may cause binding of the apolar 1-aminopentane to be unfavorable in PjAT. In conclusion, we showed that PjAT has a non-polar active site that is shaped mainly by aromatic side chains, such as Tyr and Phe. The high sequence similarity and the conserved secondary structure confirm the identity of the enzyme as an ω-transaminase. The high

catalytic efficiency and the low KM of PjAT with 6-AHA and 6-OHA in combination with

80 BIOCHEMICAL PROPERTIES OF A PSEUDOMONAS AMINOTRANSFERASE INVOLVED IN CAPROLACTAM METABOLISM the residue configuration in the active site explain the role of PjAT in the caprolactam/ nylon 6 degradation pathway.

AUTHOR CONTRIBUTIONS

All authors designed experiments and contributed to the interpretation of the data. C.M.P. cloned and isolated the enzyme. C.M.P. and H.R. performed kinetic and crystallography 3 experiments, respectively. C.M.P., H.R., M.O. and D.B.J. wrote the manuscript.

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Catalysts 254, doi:10.3390/catal8070254 3 32. Kelly SA, Pohle S, Wharry S, Mix S, Allen CCR, Moody TS, Gilmore BF. 2018. Application of ω-transaminases in the pharmaceutical industry. Chem Rev 118: 349-367. 33. Dunn PJ. 2012. The importance of green chemistry in process research and development. Chem Soc Rev 41:1452–1461. 34. Palacio CM, Crismaru CG, Bartsch S, Navickas V, Ditrich K, Breuer M, Abu R, Woodley J, Baldenius K, Wu B, Janssen DB. 2016. Enzymatic network for production of ether amines from alcohols. Biotechnol Bioeng 113:1853–1861 35. Klatte S, Wendisch VF. 2015. Role of L-alanine for redox self-sufficient amination of alcohols. Microb Cell Fact 14:9. 36. Turk SCHJ, Kloosterman WP, Ninaber DK, Kolen KPAM, Knutova J, Suir E, Schürmann M, Raemakers-Franken PC, Müller M, De Wildeman SMA, Raamsdonk LM, Van Der Pol R, Wu L, Temudo MF, Van Der Hoeven RAM, Akeroyd M, Van Der Stoel RE, Noorman HJ, Bovenberg RAL, Trefzer AC. 2016. 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Cloning and characterization of a novel β-transaminase from Mesorhizobium sp. strain LUK: A new biocatalyst for the synthesis of enantiomerically pure β-amino acids. Appl Environ Microbiol 73:1772–1782. 42. Shin JS, Kim BG. 2001. Comparison of the ω-transaminases from different microorganisms and application to production of chiral amines. Biosci Biotechnol Biochem 65:1782–1788. 43. Humble MS, Cassimjee KE, Abedi V, Federsel H-J, Berglund P. 2012. Key amino acid residues for reversed or improved enantiospecificity of an ω-transaminase. ChemCatChem 4:1167–1172. 44. Sayer C, Isupov MN, Westlake A, Littlechild JA. 2013. Structural studies of Pseudomonas and Chromobacterium ω-aminotransferases provide insights into their differing substrate specificity. Acta Crystallogr Sect D Biol Crystallogr 69:564–576. 45. Midelfort KS, Kumar R, Han S, Karmilowicz MJ, McConnell K, Gehlhaar DK, Mistry A, Chang JS, Anderson M, Villalobos A, Minshull J, Govindarajan S, Wong JW. 2013. Redesigning and characterizing the substrate specificity and activity of Vibrio fluvialis aminotransferase for the synthesis of imagabalin. Protein Eng Des Sel 26:25–33. 46. Denesyuk AI, Denessiouk KA, Korpela T, Johnson MS, Akademi Ê. 2002. Functional attributes of the phosphate group binding cup of pyridoxal phosphate-dependent enzymes. J Mol Biol 316:155-72 47. Humble MS, Cassimjee KE, Hãkansson M, Kimbung YR, Walse B, Abedi V, Federsel HJ, Berglund P, Logan DT. 2012. Crystal structures of the Chromobacterium violaceum ω-transaminase reveal major structural rearrangements upon binding of coenzyme PLP. FEBS J 279:779–792. 48. Cho B, Park H-Y, Seo J-H, Kim J, Kang T-J, Lee B-S, Kim B-G. 2008. Redesigning the substrate specificity of ω-aminotransferase for the kinetic resolution of aliphatic chiral amines. Biotechnol Bioeng 99:275–284. 49. Robert X, Gouet P. 2014. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res 42:320–324. 50. Łyskowski A, Gruber C, Steinkellner G, Schürmann M, Schwab H, Gruber K, Steiner K. 2014. Crystal structure of an (R)-selective ω-transaminase from Aspergillus terreus. PLoS One 9:e87350. 51. Genz M, Melse O, Schmidt S (2016) Engineering the amine transaminase from Vibrio fluvialis towards branched-chain substrates. ChemCatChem 8:1–5. 52. Nobili A, Steffen-Munsberg F, Kohls H, Trentin I, Schulzke, C, Höhne M, Bornscheuer UT. 2015. Engineering the active site of the amine transaminase from Vibrio fluvialis for the asymmetric synthesis of aryl-alkyl amines and amino alcohols. ChemCatChem 7:757–760.

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53. Skalden L, Peters C, Dickerhoff J, Nobili A, Joosten HJ, Weisz K, Höhne M, Bornscheuer UT. 2015. Two subtle amino acid changes in a transaminase substantially enhance or invert enantiopreference in cascade syntheses. Chembiochem 16:1041-5. 54. Steffen-Munsberg F, Vickers C, Thontowi A, Schätzle S, Meinhardt T, Svedendahl Humble M, Land H, Berglund P, Bornscheuer UT, Höhne M. 2013. Revealing the structural basis of promiscuous amine transaminase activity. ChemCatChem 5:154–157. 55. Cassimjee KE, Humble MS, Land H, Abedib V, Berglund P. 2012. Chromobacterium violaceum ω-transaminase variant Trp60Cys shows increased specificity for S( )-1-phenylethylamine and 4’-substituted acetophenones, and follows Swain–Lupton parameterisation. Org Biomol Chem 10:5466–5470. 56. Bouet A, Oudeyer S, Dupas G, Marsais F, Levacher V. 2008. New advances in stereoselective Meyers’ lactamization . Application to the diastereoselective synthesis of β-substituted oxazoloazepinones. Tetrahedron: Asymmetry 19:2396– 3 2401. 57. Barber JEB, Damry AM, Calderini GF, Walton CJW, Chica RA. 2014. Continuous colorimetric screening assay for detection of D-amino acid aminotransferase mutants displaying altered substrate specificity. Anal Biochem 463:23–30. 58. Kabsch W. 2010. Integration, scaling, space-group assignment and post-refinement. Acta Crystallogr Sect D Biol Crystallogr 133–144. 59. Winn MD, Charles C, Cowtan KD, Dodson EJ, Leslie AGW, McCoy A, Stuart J, Garib N, Powell HR, Randy J. 2011. Overview of the CCP 4 suite and current developments. Acta Crystallogr Sect D Biol Crystallogr 4449:235–242. 60. Matthews BW. 1968. Solvent content of protein. J Mol Biol 33:491–497. 61. Jaroszewski L, Rychlewski L, Li Z, Li W, Godzik A, Program B, Road NTP, Jolla L. 2005. FFAS03 : a server for profile –profile sequence alignments 33:284–288. 62. Canutescu AA, Shelenkov AA, Jr RLD. 2003. A graph-theory algorithm for rapid protein side-chain prediction. Protein Sci 12:2001–2014. 63. Mccoy AJ, Grosse-Kunstleve RW, Adams PD, Winn MD, Storoni LC, Read RJ. 2007. Phaser crystallographic software. J Appl Crystallograhy 40:658–674. 64. Adams PD, Afonine P V, Bunkóczi G, Chen VB, Davis IW, Echols N, Headd JJ, Hung LW, Kapral GJ, Grosse- Kunstleve RW, McCoy AJ, Moriarty NW, Oeffner R, Read RJ, Richardson DC, Richardson JS, Terwilliger TC, Zwart PH. 2010. PHENIX: A comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr Sect D Biol Crystallogr 66:213–221. 65. Emsley P, Lohkamp B, Scott WG, Cowtan K. 2010. Features and development of Coot. Acta Crystallogr Sect D Biol Crystallogr 66:486–501. 66. Murshudov GN, Skubák P, Lebedev AA, Pannu NS, Steiner RA, Nicholls RA, Winn MD, Long F, Vagin AA. 2011. REFMAC 5 for the refinement of macromolecular crystal structures. Acta Crystallogr Sect D Biol Crystallogr 67:355–367. 67. Chen VB, Arendall III WB, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, Murray LW, Richardson JS, Richardson DC. 2010. MolProbity : all-atom structure validation for macromolecular crystallography. Acta Crystallogr Sect D Biol Crystallogr 66:12–21. 68. Delano WL. 2002. Unraveling hot spots in binding interfaces : progress and challenges. Curr Opin Struct Biol 12:14–20. 69. Robert X, Gouet P. 2014. Deciphering key features in protein structures with the new ENDscript server. Nucl Acids Res 42:W320-W324.

84 Enhancing thermal stability of 4Pseudomonas jessenii transaminase by computational library design

Cyntia M. Palacio, Hein J. Wijma, Marleen Otzen, Dick B. Janssen

Manuscript in preparation

87 ABSTRACT

Transaminases catalyze the reversible conversion of amines to keto compounds or aldehydes. Their diversity in combination with high chemo-, regio- and stereoselectivity of individual enzymes allow applications in the synthesis of various terminal and chiral amines. We have recently discovered a transaminases from a caprolactam-degrading strain of Pseudomonas jessenii that is active with 6-aminohexanoic acid, suggesting that the enzyme could be attractive for in vivo or in vitro synthesis of primary amines including nylon precursors. However, the protein appeared to be rather unstable and showed disappointing heat lability. In order to pave the way for improving the stability, we applied the computational library design strategy FRESCO (Framework for Rapid Enzyme Stabilization by Computational libraries). Energy calculations on all single mutants at 397 out of 450 positions followed by molecular dynamics simulations and on-screen inspection predicted 96 mutations outside the dimer interface that could enhance stability, of which 64 mutants at 38 positions were experimentally characterized. To examine if the experimental verification can be further restricted to mutations that have a high probability of being effective, high-temperature molecular dynamics simulations were performed. Positions in the protein that showed a higher degree of unfolding in these MD simulations were assumed to represent labile regions subject to early unfolding and were assigned a high priority. Experimental testing identified five variants that showed enhanced thermal stability, and all these carried mutations in highly promising regions predicted by MD. The results suggest that high-temperature MD is a useful tool for identifying target regions for enzyme thermostability engineering.

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INTRODUCTION

In theory, enzymes are ideal catalysts for application in synthetic chemistry. Their diversity is enormous and enzymes usually exhibit high chemo-, regio- and stereoselectivity and impressive catalytic power, allowing mild reaction conditions. Nevertheless, issues such as low thermal stability, modest lifetime, and fragility during preparation, storage and use may limit application of enzymes in industrial processes. Especially thermostability is highly important. Often, it is desirable to perform a conversion process at elevated temperature because this increases reaction rates and substrate solubility and at the same time decreases viscosity and risk of microbial contamination. Thus, enzymes with high thermal stability and long shelf life are in great demand (1–3). Native enzymes 4 isolated from mesophilic organisms often are not suitable for industrial application and need to be improved to remain sufficiently stable and active at elevated reaction temperatures. Other robustness properties that are desirable include compatibility with the presence of organic co-solvents and tolerance to high mixing rates and associated shear and surface forces (2, 4, 5). Furthermore, high stability might benefit industrial application because less biocatalyst is used, in part because recycling is more effective (6–9). Over the last decades, many protein engineering strategies have been developed for improving protein thermal stability, including directed evolution, rational design, consensus-based methods, and computation-based methodologies (6–9). Directed evolution is a powerful strategy that is often used to improve protein stability and can yield enzymes that are more active in organic solvents as well as enzyme variants with improved or modified substrate specificity (9–11). Several commercial enzymes, including α-amylases, lipases and subtilisins, have been evolved using this strategy (12). Directed evolution starts with generating sequence diversity, either in a random manner or inspired by insight in structure-function relationships of the protein under study. Random methods include, for example, DNA shuffling (13), which may be combined with error-prone PCR (14). Although the combination of these methods provides a powerful engineering method, the protocols are normally time-consuming because of the need to perform repeated rounds of mutagenesis and screening (5, 15–17). Furthermore, these methods become impractical in case a high-throughput expression and screening method is not feasible, as is the case with fungal or mammalian expression systems. A second strategy to create thermostable enzymes is rational design. This strategy involves careful structural inspection of 3D structures to identify positions where mutations may improve interactions that on the basis of the biophysical principles of protein folding are expected to increase the stability of the folded state or to destabilize the unfolded state. Stabilizing mutations may act through disulfide bond formation, fill hydrophobic cavities or enlarge hydrophobic clusters, compensate unpaired hydrogen bond donors or acceptors or improve electrostatic interactions. When introduced at

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the right spot, such mutations may increase thermodynamic stability or decrease the rate of unfolding by stabilizing labile regions (18–22). The abundance of information on protein folding and 3D structures have established rational design as a reliable approach for finding improved enzyme variants (23–25). However, single mutations often have a modest effect, and successful rational design of stable enzymes often requires the introduction of multiple mutations with independent or additive thermostabilization effects. It may be problematic to discover by rational design the required mutations, which have small effects individually (26–30). The search can become very time consuming. Supported by the development of improved energy functions for calculating 4 the effect of mutations and triggered by the successful design of highly stable small proteins, interest is rapidly increasing in the use of computational methods for enhancing enzyme stability (3, 31, 32). Computational design indeed can provide a rapid pathway to improved enzymes with better thermal stability for specific process conditions (33– 35). In our laboratory, we have explored a computational strategy for improving thermal stability named FRESCO (Framework for Rapid Enzyme Stabilization by Computational libraries) (36). This procedure aims to predict and identify a large number of stabilizing mutations through subsequent in silico screening steps, which reduce the number of variants to be tested experimentally. The initial step consists of molecular mechanics energy calculations on all possible point mutations. Mutants that are predicted to be more stable are subjected to molecular dynamics simulations (37) and visual inspection (21, 38) and those that pass these tests are examined experimentally. Thereafter, confirmed stabilizing mutations are checked for compatibility by model building and simulations are combined to obtain highly stable variants (3). This strategy was successful for increasing the thermal stability of the limonene epoxide hydrolase from Rhodococcus erythropolis DCL14 by +35˚C (3). The same computational strategy was also used to improve the stability of a halohydrin and a haloalkane dehalogenase for use in the presence of organic cosolvents. The improved variants reached a +27˚C increase in stability without decrease of activity (31, 39). Similarly, a stable variant of peptide amidase was created this way for use in neat organic solvent, allowing improved application of the enzyme in peptide C-terminal coupling reactions (40). The most attractive feature of the FRESCO protocol is the reduction of library size to a group of less than 190 mutants, which are easily tested in one or two 96-well microtiter plates using rapid unfolding assays. Since the success rate is 10-15%, this yields typically 20-30 stabilizing mutations. Some are at the same position or may be incompatible, but the remaining mutations can be combined to obtain a highly stable variant. Nevertheless, strategies to further reduce library size without decreasing the number of positive variants would be highly attractive. For example, mutagenesis could be focused on early unfolding regions, also called weak spots, in the protein structure (20).

90 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN

Table 1. Success rates amongst predicted stabilizing point mutations in FRESCO libraries.

number of mutationsA fraction enzyme reference tested stabilizing successful (%) dehalogenase LinB 109 10 9 (31) halohydrin dehalogenase HheC 218 29 13 (39) HMF oxidase 140 17 12 (41) limonene epoxide hydrolase 64 11 17 (3) peptide amidase 120 12 10 (40) xylanase 105 10 10 (42) A This only includes point mutations introduced in the starting variant of the enzyme. 4 Omega transaminases are PLP-dependent fold type I subgroup AT-II enzymes, which have been studied for the conversion of aldehydes and ketones to ω-amino acids, β-amino acids, chiral amines and terminal amines (43). The amine donor is a primary amine or ω-amino acid that transfers its amino group via an enzyme-PMP intermediate to the amino acceptor. These enzymes are considered to have high potential for industrial purposes (44). They show broad substrate specificity and apart from a cheap amine donor (alanine, isopropylamine) transaminases do not require expensive cosubstrates or redox-active cofactors (45). Due to these advantages and the environmentally friendly properties of the catalyst, transaminases are widely investigated for use in kinetic resolution of racemic amines and for the asymmetric synthesis of enantiopure amines from ketones (46, 47). One of the most relevant examples is their application in the manufacturing process of Sitagliptin, a top-selling anti-diabetic drug (48). In the original process, the non-enzymatic conversion of a β-ketoamide to Sitagliptin required the use of transition metal catalysts and high pressure. The metal catalyst was later replaced by a highly evolved transaminases, resulting in a reduction of waste production and energy consumption, as well as an increased overall yield and volumetric productivity (49). In general, transaminases are attractive for conversions which demand high stereo-, regio-, and enantioselectivity in combination with high reaction rates. In this chapter we explore the use of the FRESCO workflow to improve the thermal stability of a recently discovered and characterized ω-transaminase involved in the caprolactam degradation pathway (50). This enzyme was isolated from the caprolactam degrading bacterium Pseudomonas jessenii strain ODJ3. Caprolactam is widely used for the production of Nylon 6 (51), a polymer used for manufacturing of numerous products, such as toys, fabrics, clothing, utensils, mechanical parts, etc. Protein mass spectrometry demonstrated that this transaminase is induced in caprolactam-grown cells. The purified transaminase catalyzes the reversible transamination of the aldehyde 6-oxohexanoic acid into 6-aminohexanoic acid. Both these compounds are intermediates in an artificial biosynthetic pathway towards caprolactam and in the natural pathway of caprolactam biodegradation (50, 52). The Pseudomonas jessenii transaminase showed high activity

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towards a wide variety of aromatic and aliphatic linear amines. However, the low stability of the transaminase at high temperatures limits its potential applications. For the above reasons, we set out to target the PjTA enzyme as a model system to apply the FRESCO protocols for enhancing the stability of a PLP dependent aminotransferase. Since the enzyme is rather large (455 amino acids), we examined the use of high-temperature MD simulations to examine if this approach can be used to reduce library size and increase library quality. Whereas reports on improving stability of transaminase emerged while this work was ongoing (53, 54), these studies did not focus on surface mutations or computational selection of target regions. After selection of mutants, we performed experimental screening and identified five variants with 4 increased thermal stability, including two mutants with increased catalytic activity. These were in regions that by MD simulations were predicted to be priority targets for enhancing stability.

MATERIALS AND METHODS

Substrates and chemicals Nicotinamide adenine dinucleotide (NAD+), 6-aminohexanoic acid and alanine dehydrogenase from Bacillus cereus were purchased from Sigma-Aldrich. Pyridoxal phosphate (PLP) was purchased from Fisher Scientific. Pyruvic acid was acquired from Acros Organics. Potassium phosphate dibasic trihydrate and potassium phosphate monobasic were obtained from Merck Millipore. The substrate (S)-α-methylbenzylamine was obtained from Acros Organics. The fluorescent stain SYPRO Orange was purchased from Life Technologies.

Mutagenesis Mutants of PjTA were created by QuikChange mutagenesis in 96-well plate format. The vector was pET20b(+)-His-PjTA, containing an in-frame fusion of the PjTA gene as described ((55), see also Chapter 2 of this thesis). The reactions were performed in parallel. Primers were designed with the QuikChange Primer Design Program of Agilent Technologies. After transformation to strain E. coli TOP10, also in a 96-well microtiter plates, transformants from individual wells were plated onto agar in 24-well microtiter plates. Plasmids from colonies were analyzed by agarose gel electrophoresis (0.8%) and clones showing plasmid with the expected size were transferred to 96-well plates, grown at 37ºC and stored in the presence of 15% glycerol at -80ºC. The mutations were verified by DNA sequencing (Eurofins Genomics).

92 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN

Enzyme expression and purification The enzymes were produced as described by Palacio et al. (56). Briefly, cells were cultivated in 250 mL flasks overnight at 30°C on TB medium with induction by IPTG, collected by centrifugation, and lysed by sonication. Purification was carried out in Pall AcroWell 96-well filter plates (Sigma Aldrich) loaded with TALON metal affinity chromatography resin (Clontech). The desalting step was done with a multi-well gravity column PD MultiTrap G-25 (GE Healthcare). The purification ofPj TA from larger cultures was performed as described by Palacio et al. (56). The enzymes were stored at 4°C in 100 mM potassium phosphate, pH 8.0.

Thermal shift assay 4

Melting temperatures (Tm) were determined by the thermofluor method, which is based on an enhancement of fluorescence upon binding of a hydrophobic fluorescent compound to protein that becomes unfolded when the temperature is increased (57). Five µl of 100-fold diluted SYPRO orange and 20 µl of a 0.1 to 1.5 mg/ml enzyme solution were added to an IQ 96-wells PCR plate (Bio-Rad). Phosphate buffer without protein was used as a control. The plates were sealed with Microseal B adhesive sealer (Bio-Rad) and heated in a MyiQ real-time PCR machine (Bio-Rad) from 25°C to 90°C at 1°C/min. The wavelengths for excitation and emission were 490 nm and 575 nm, respectively (58). The temperature at the moment of maximum rate of fluorescence change (dRFU/dT) was taken as the apparent melting temperature (TM,app) (31).

Activity assay Enzyme activities were measured by coupling the aminotransferase to B. cereus alanine dehydrogenase as described by Palacio et al. (55). The appearance of NADH at 340 nm 3 -1 ‑1 (εNADH = 6.22×10 M ∙cm ) was monitored using a microtiter plate reader (Synergy Mx, BioTek Instruments). Assays were performed in 96-well plates containing reaction mixtures lacking the amino acceptor pyruvate. A solution of pyruvate was added to each well to initiate the reaction. The absorbance at 340 nm was monitored for 30 min at 30˚C. The initial rates of appearance of NADH by the alanine dehydrogenase were used to determine the kinetic constants of the aminotransferase. Specific activities are expressed in units/mg (µmol∙min-1∙mg-1).

Identification of priority regions by MD To predict regions in the PjTA structure that might be sensitive to unfolding and thereby serve as targets for stability engineering, the PjTA-PLP structure was subjected to high- temperature molecular dynamics simulations. The simulations were done at 500 K to allow detection of structural changes that happen too slowly at ambient temperature. Three X-ray structures of P. jessenii TA which were solved in-house were used: PjTA-ap, the apoenzyme with phosphate bound (1.87 Å resolution with an Rfree of 0.184); PjTA

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-as, the apoenzyme with succinate bound (resolution 1.80 Å, Rfree 0.203); and PjTA -plp, the PLP-bound enzyme (2.15 Å resolution, Rfree of 0.261). First, molecules originating from the crystallization buffer were removed and protonation states of ionizable groups were assigned (59) assuming pH = 8.0. Simulations started with an energy-minimized structure, and the temperature was increased from 5 K to the final simulation temperature of 500 K in the first 30 ps, followed by 32 ns of MD simulation at 500 K. A periodic boundary simulation cell was used with distances of at least 7.5 Å between enzyme and the cell walls. The integration time step was 1.25 fs with non-bonded interactions updated every 2 simulation steps. Simulations were performed with the Amber11 force field under Yasara (60). The simulations were 4 performed in triplicate, using different initial atom velocities according to a Boltzmann distribution (61, 62). Snapshots were saved every 25 ps. For every snapshot the RMSD (root mean square deviation) was determined and recorded for each amino acid. A local increase in RMSD observed in the 500 K simulations was interpreted as indicative of unfolding. Some of these structural changes might be due to the omission of crystal contacts. To avoid these being interpreted as a sign of unfolding as well, an averaged structure from a similar set of simulations at 298 K was used as a reference instead of the crystal structure. This reference was obtained from 10 simulations of each 2.5 ns of which the equilibrated last 0.5 ns was averaged. The use of repetitive simulation runs with independent initialization improves coverage of conformational space (62–64) whereas in case of high temperature MD simulations we used timescales long enough to detect early unfolding events. When a partially unfolded protein is superpositioned on its folded structure using standard methods, the apparent RMSD is increased throughout the protein structure since the alignment algorithm minimizes the overall RMSD. Since this can mask local unfolding, we used the motif superpositioning method of Vriend and Sander (65). This algorithm only superimposes the folded parts of the protein and gave higher RMSDs for truly unfolded residues and a lower RMSD for stable regions. A method to convert high temperature RMSD values to priorities for mutagenesis was developed in house (to be published elsewhere). Briefly, the RMSD per residue calculated as explained above was averaged and priorities were assigned to positions as a function of this RMSD and the RMSD of residues with which it interacts in the 3D structure. The latter was included because residues critical for stabilizing interactions may not appear as early unfolding themselves, but may allow unfolding of regions with which they interact in a suboptimal manner.

Computational design of stabilizing mutations To design potentially stabilizing mutations in the PjTA protein, we followed the FRESCO protocol (framework for enzyme stabilisation by computational library design) (3, 66, 67). First, we calculated effects on free energy of folding for point mutations at all

94 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN positions in the protein, substituting with all proteinogenic amino acids except cysteine. The difference in free energy of unfolding of each point mutant (ΔΔGfold) was calculated using Rosetta (68) with the Row 3 protocol [options: –ddg::local_opt_only true – ddg::opt_radius 8.0 –ddg::weight_file soft_rep_design -ddg::iterations 50 -ddg::min_ cst false -ddg::mean true -ddg::min false -ddg::sc_min_only false -ddg::ramp_repulsive false]. The same calculations were performed with FoldX (69), using its standard settings. All FoldX calculations were repeated five times to obtain better averaging. Both for the FoldX and the Rosetta protocol, the results over the three dimeric aminotransferase structures were averaged. To eliminate mutations that are unlikely to be stabilizing we used visual inspection and MD simulations, which is a standard part of the FRESCO procedure (3, 31, 40, 67) 4 For each mutant, a 3D structure was predicted by FoldX using the crystal structure of the wild-type PjTA -plp as the template. The resulting models were used for 100 ps MD simulations. For each mutant, five simulations at 298 K were performed with a different set of initial atom velocities. Yasara was used with the same settings as above, except that the Yamber3 force-field was used (70). The visual inspections were recently described in detail (36) and result in the dismissal of mutations causing solvent exposure of hydrophobic side chains, introduction of unsatisfied H-bond donors and acceptors, and other obvious structural problems. We also examined the effect of the use of more strict energetic criteria for mutant selection, similar to protocol recently published under the acronym FireProt (71). Again, FoldX and Rosetta are used to calculate the effect of mutations on ΔΔGfold, but only mutations were accepted for which the calculated ΔΔGfold is better both by at least -4.184 kJ mol-1 for FoldX and by -8.368 kJ mol-1 for Rosetta. The stricter criteria could prevent false-positive predictions causing the accidental introduction of destabilizing mutations. The settings for the Rosetta Row 16 protocol were: -ddg::weight_file soft_ rep_design -ddg::iterations 20 -ddg::local_opt_only false -ddg::min_cst true -ddg::mean false -ddg::min true -ddg::sc_min_only false -ddg::ramp_repulsive true. The Row 16 protocol uses energy minimization of the entire protein while the Row 3 protocol performs energy minimization only on amino acid sidechains that are within 8 Å of the mutated residue. The prediction accuracy of the computationally much more expensive Row16 protocol is slightly better: for a large benchmark set of mutations with known ΔΔGfold the correlation coefficient R2 was 0.68 for the Row 3 protocol and 0.69 for the Row 16 protocol (68). The less strict criteria commonly used in the FRESCO workflow (in this study ΔΔGfold = -2.5 kJ/mol per subunit both for FoldX and Rosetta, unlike with the strict criteria the mutation needs to pass only FoldX or Rosetta to be accepted) will initially select a large number of mutations, from which pathological mutations are removed by orthogonal tests, i.e. molecular dynamics simulations and visual inspection. The few mutations that passed the stricter energy criterion were also experimentally characterized if they did not pass these orthogonal tests.

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RESULTS

Stability of P. jessenii aminotransferase Preliminary experiments reported by Otzen et al. (50) indicated that a P. jessenii transaminase (PjTA) that is active on 6-aminocaproic acid is unstable upon freezing and storage. Formation of a precipitate was observed when the enzyme was thawed after storage at -20˚C in 50 mM potassium phosphate, pH 8, containing 10% glycerol. After removing this material by centrifugation, an activity test was performed with the supernatant and no activity was observed. When the enzyme was stored in the same buffer at 4˚C, activity decreased 36% over a period of 15 days. In view of these 4 stability problems, we decided to study the possibility to stabilize the enzyme by protein engineering, at the same time testing if the use of high-temperature molecular dynamics would be helpful to identify priority mutations that contribute to enhanced stability.

Selection of target regions The FRESCO workflow for stability engineering makes use of computational protocols to identify substitutions that have a high probability of contributing to enhanced stability. Although the in silico design and screening strategy is effective in terms of final outcome, the number of experimentally confirmed positives (more stable variants) in the designed libraries is still modest (Table 1). In case of large proteins FRESCO suggests a larger number of stabilizing mutations than what one would like to examine in the laboratory. Earlier applications of the FRESCO protocol mainly concerned enzymes with lower molecular weight than PjTA, which is a 455 amino acid dimeric protein with 50 kDa subunits. To reduce the numbers of variants that must be tested in the lab and increase the success frequency, the FRESCO strategy would benefit from an additional computational step that can discern topological regions in a protein where mutations are effective from regions where mutations cannot make a contribution to enhanced stability. Such a method should preferably be orthogonal to the already applied methods of energy calculations, MD simulations, and visual inspection. The irreversible denaturation of proteins at high temperature may start at early unfolding regions (20). Exposing hydrophobic patches may trigger aggregation and thereby cause cooperative irreversible inactivation. Mutations in such labile regions may enhance overall stability. This is the basis of the so-called B-fit approach, which aims to stabilize flexible regions identified by high crystallographic B-factors (72, 73). An alternative approach would be to pinpoint early unfolding regions where mutations may enhance stability by using molecular dynamics simulations (74). However, the timescales of MD simulations are too short in most cases to detect such functionally relevant structural events. A way to enhance the unfolding rate in simulations is to increase the temperature (75). We therefore performed MD simulations both at 298 and at 500 K

96 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN and compared RMSD changes. Starting with the recently solved crystal structure with PLP bound (PjTA-plp) 32 ns trajectories were generated in triplicate by MD simulations at 500 K. For the room temperature simulations, 10 trajectories of each 2.5 ns were averaged to obtain an MD equilibrated structure, which served as a reference for the 500K simulations. This averaged structure was used as a reference instead of the X-ray structure because the latter would make the comparisons sensitive to effects of loss of crystal contacts or inaccuracies in the force-field. The results of the high temperature MD simulations and RMSD calculations were used to assign each position with a priority rank, ranging from 1 to 449, where the highest rank corresponds to the highest regional RMSD, calculated as described in the Materials and Methods. The usefulness of the unfolding predictions was subsequently examined in the 4 laboratory with PjTA residues that are not located at the interface. In total 100 positions with high priority (rank 1-100) and 40 positions with low priority (rank 410-449) were selected for experimental analysis (Table 2; Fig. 1).

Computational design of point mutations Initial energy calculations were carried out for all possible substitutions at all 397 positions that were further than 10 Å from the PLP cofactor. Changes in free energy of unfolding (ΔΔGFold) were calculated using FoldX and Rosetta with the three different PjTA structures and the results were averaged, yielding 323 potentially stabilizing substitutions (ΔΔGFold per dimer better than -2.5 kJ/mol for FoldX or Rosetta) in the high-priority regions and 128 mutations in the low priority region (Table 2). The predicted structures of these 451 mutants were used for MD simulations to identify some mutations that should be dismissed because of expected destabilizing effects as indicated by structural problems or enhanced flexibility (Table 2). Due to inaccuracies in the energy functions and the conformational sampling methods, both FoldX and Rosetta tend to select a mixture of stabilizing mutations and mutations decrease stability due to the biophysical problems that they introduce. Therefore, mutations were inspected on screen, which dismissed a further set of mutations (Table 2). Interface mutations were excluded because the priority assignment algorithm was known not to work for such mutations (see above).

97 PjTA structures and the results were averaged, yielding 323 potentially stabilizing substitutions (''GFold per dimer better than -2.5 kJ/mol for FoldX or Rosetta) in the high-priority regions and 128 mutations in the low priority region (Table 2). The predicted structures of these 451 mutants were used for MD simulations to identify some mutations that should be dismissed because of expected destabilizing effects as indicated by structural problems or enhanced flexibility (Table 2). Due to inaccuracies in the energy functions and the conformational sampling methods, both FoldX and Rosetta tend to select a mixture of stabilizing mutations and mutations decrease stability due to the biophysical problems that they introduce. Therefore, mutations were inspected on screen, which dismissed a further set of mutations (Table 2). Interface mutations were excluded because the priority assignment algorithm was known not to

work forCHAPTER such 4 mutations (see above).

4

Fig. 1Fig.. Identification 1. Identification of ofsurface surface-located-located target targ regionset regions for thermostabilisation for thermostabilisation of P. jessenii of P. transaminase by high temperature MD simulations. The priority (thicker lines indicate higher jesseniipriority) transaminase and the location by highof the temperature selected mutations MD (numbered simulations. spheres) The are priority indicated. (thicker Orange lines spheres indicate positions which were given high priority by the 500K RMSD + neighbour indicatecorrection higher algorithm. priority) Positionsand the with location black spheres of the were selected given a mutationslow priority. The(numbered PLP cofactor spheres) is are indicated.indicated withOrange yellow spherescarbon atoms. indicate The two positions subunits are which in cyan were green given and marine high blue. priority by the 500K RMSD + neighbour correction algorithm. Positions with black spheres were given a low Thepriority. combined The selection PLP cofactor steps in isthe indicatedFRESCO protocol with yellowreduced carbon the set ofatoms. promising The two mutations in high- and low priority regions to a total of 88 (Table 2). At the same subunitspositions, are in thecyan use green of a set and of marinestricter energy blue. criteria (but without the inspection steps) resulted in selection of only 18 mutations (Table 2). This included 8 mutations that were not selected by the FRESCO protocol (Table 3). As a result, a total of 96 mutations were The combined selection steps in the FRESCO protocol reduced the set of selected for experimental characterization. promising mutations in high- and low priority regions to a total of 88 (Table 2). At the Mutagenesis and expression same positions, the use of a set of stricter energy criteria (but without the inspection Of the 96 selected mutations remaining by in silico design and MD screening, 68 were obtained by QuikChange PCR as confirmed by DNA sequencing. For examining expression and thermostability, the mutants were grown in 50 mL cultures in 250 mL flasks after which cells were lysed and mutant enzymes were isolated by His-tag metal affinity chromatography in microtiter plates. Using this procedure, we isolated from each 50 ml culture 10-45 mg of purified PjAT variant. Concentrations were determined by Bradford assay. In total 64 PjAT variants were obtained in soluble form, indicating that detrimental mutations which completely abolished expression were rare. The purified enzyme samples were used for thermofluor stability assays.

98 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN

Thermostability assays The stability of the isolated PjTA variants was examined by thermofluor assays, which measure real-time thermal unfolding in the presence of a fluorescent dye. The assays were done in microtiter plates to allow comparison of large numbers of mutants, using 1-20 μg/well samples of protein per assay. The changes in apparent melting temperature

(ΔTM,app) in comparison to the wild-type TM,app revealed the stabilizing effect of the designed mutations. The wild-type enzyme displayed modest stability with a TM,app of 60.25 ºC. All 64 mutants that gave expression of soluble protein gave a good signal in these thermofluor assays (Table 3). Of the 13 mutants (12 FRESCO mutants plus 1 mutant predicted by the stricter FireProt energy criteria) substituted in low priority regions, none displayed an enhanced 4 stability (ΔTM,app ≥1.0˚C) in thermofluor assays compared to the wild-type PjTA. On the other hand, when examining mutations in the high priority regions, it appeared that out of 51 mutations (39 from FRESCO only, 6 from strict energy criteria, and 6 from both) attempted mutations, 5 mutations gave a modest but significant increase in thermostability. These 5 all came from the more relaxed FRESCO energy criteria and orthogonal inspection by MD and on-screen visualization (Table 3). Of the other

46 mutants in high priority regions, 34 showed a change in ΔTm,app of less than 1.0°C, which is too low for reliable conclusions, whereas 12 of those 46 mutants gave a slightly lower stability than the wild type. The discovery of 5 stabilizing mutations only in the high-priority group does not unequivocally proof that high-temperature MD identified regions where computationally designed mutations can contribute to an increase in stability because of the smaller number of tested mutations localized in low priority regions. Also the fraction of stabilizing mutations (5/45=11%) amongst the high priority mutations does not exceed the success rate in earlier FRESCO studies where no strategy was applied to target early unfolding regions (Table 1). Thus, the current system and data do not provide support for the hypothesis that high temperature MD simulations helped to decrease the screening effort required to find good mutations.

99 CHAPTER 4

Table 2. Computational design of stabilizing mutations using different energy criteria and ranking methods.

FRESCO criteria Stricter criteria priority priority priority priority Step total total 1 - 100 410-449 1 - 100 410-449 theoretical possibilities 2520 1800 720 2660 1900 760 FoldX criteria (kJ/mol) A < -2.5 < -2.5 < -2.5 <-4.2 <-4.2 <-4.2 No. of FoldX mutants 167 124 43 81 58 23 Rosetta row protocol 3 3 3 16 16 16 criteria (kJ/mol) A, B < -2.5 < -2.5 < -2.5 < -8.4 < -8.4 < -8.4 No. of Rosetta mutants 375 267 108 24 17 7 4 total number of energy-based mutationsC 451 323 128 24 17 7 position at the dimer interface (eliminated) 38 0 38 6 0 6 solvent exposed hydrophobic groups 130 96 34 - - - unsatisfied H-bond donors/acceptors 46 42 4 - - - other problems D 86 62 24 - - - increased side chain flexibility 6 5 1 - - - increased local backbone flexibility 21 19 2 - - - increased flexibility of entire protein 2 0 2 - - - no solid conclusion by inspectionE 6 30 6 - - - total number of mutations remaining 88 69 19 18 17 1 protein expression obtained 57 45 12 12 11 1

increased Tm,app 5 5 0 0 0 0

decreased Tm,app 11 9 2 4 4 0

no effect on m,appT 42 32 10 8 7 1 success (%)F 8 11 0 0 0 - A Energy criteria are per monomer. B Calculations with the Rosetta Row 16 protocol were only carried out for mutants that passed the FoldX criterion because the calculations were very CPU expensive. C passed either Rosetta or FoldX criteria or both. D Occasionally it occurred that all mutations at a certain position were predicted to be stabilizing, suggesting a systematic error in the energy calculation for the wild-type structure. E In the standard FRESCO procedure such mutants are included but they were omitted here to restrict library size. F equals the number of stabilizing mutations divided by the number of mutations examined experimentally.

No stabilizing mutations were discovered within the smaller set of 12 tested mutant proteins that were suggested when using the stricter energy selection criteria (Table 2). These 12 mutations were almost exclusively located at high priority positions, and 6 of them were selected while that the visual inspection or MD simulations of the FRESCO protocol suggested their elimination. Of these disputed mutations, 4 were even significantly destabilizing. Of these 4, 3 had been eliminated from the FRESCO library because they introduced a solvent exposed hydrophobic group on the protein surface (D45F, D45Y, and E345M).

100 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN

Table 3. Mutations influencing stability of PjTA.

Fold A Predicted ΔΔG (kJ/mol) FRESCO FireProt Observed Priority Mutation Rosetta Rosetta FoldX selected selected ΔTM,app Row 3 Row 16 23 S6K 0.7 -5.3 ND + - 0.5 58 P9A 17.9 -8.7 ND + - 1.5C 58 P9K 6.7 -14.8 ND + - 1.5C 58 P9R 6.1 -9.9 ND + - 0.25 39 A23L -18.4 1.8 -33.7 + + 0.25 11 E28K -4.5 -16.4 ND + - 0 43 D45I -12.2 -11.3 -18 + + 0.5 43 D45V -6.5 -5 ND + - 0 43 D45F -12.8 -17.5 -22.2 -B + -1 43 D45K -8.8 -2.1 12.3 + - -1.25 43 D45Y -14.3 -23 -24 -B + -1.25 43 D45W -9 -31.8 -25.5 -B + -0.25 40 Q46K -0.5 -6 ND + - 0.25 4 40 Q46N 0.3 -8.5 ND + - -0.5 69 G49A -1.1 -7.9 ND + - -2.25 69 G49P -13.3 12.9 -22.1 + + -0.25 61 E103A 6.2 -8.2 ND + - -0.25 61 E103K 0.3 -13 ND + - 0 86 P139K 11.2 -6.4 ND + - 1 72 G166S -1.6 -13.2 ND + - -0.25 425 D252K -1.9 -7.2 ND + - 0 45 Y187M -7.1 30.5 ND + - -1.5 45 Y187F -7.3 2.8 ND + - -1.25 13 L191A 1.5 2.1 ND + - -0.25 49 E196P -7.1 14.1 ND + - -0.25 64 H198A 3.2 -9.1 ND + - 0.25 64 H198R -1.7 -7.6 ND + - 0 64 H198Q -1.7 -10 ND + - 0.25 15 A192P -7.5 -11.1 ND + - 0.25 410 K210L -10.1 -10.1 -10.1 + - -0.5 89 R238H -6.3 14.9 ND + - 0.25 419 E242A 0.1 -7.6 ND + - 0.5 419 E242K -1.3 -9.3 ND + - -0.75 419 E242P -8.2 14.4 ND + - -0.5 425 D252K -1.9 -7.2 ND + - 0 85 Q269H 0.6 -11.2 ND + - 0.75 85 Q269N 0.7 -8.3 ND + - 0.25 411 A303P -8.6 8.2 -5.8 + - 0.25 412 P304A 15 -9.6 ND + - -1.25 88 S360K -5.3 -12.1 ND + - -0.75 88 S360A -2.1 -9.4 ND + - -0.75 67 E345M -11.5 -14.4 -17.5 -B + -1.75 67 E345A 0.7 -9.6 ND + - -2.5 67 E345K -9 -19.2 -12.9 + - -3 67 E345N -3.2 -11 ND + - -3 423 Q353K -0.2 -7.3 ND + - 0.75 99 R359L -15.8 -21.6 -28.8 + + 0.25 99 R359I -11.6 -9.6 -25.9 + + -0.25 47 D367K -0.9 -9.4 ND + - 0.5 47 D367N 1.3 -11.3 ND + - 0.75 1 S391K 3.6 -7 ND + - -0.25 4 A393R -7.9 9.2 ND + - 1.0 18 L398Y -6.4 3.7 ND + - -1.5 18 L398P -7 -7.6 ND + - -0.25 38 R403A -0.1 -5.5 ND + - 0.5 62 G407N -7.3 -15.3 ND + - -0.25 62 G407Y -9.1 -16.6 -26.3 -B + 0 78 M419L 4.6 -8.3 ND + - 1.25C 437 E433P -3 -8.9 ND + - 0.25 437 E433Q 4.5 -6.4 ND + - 0 420 G437Y -18.7 -22.2 -32.1 -B + 0.5 420 G437N -1.7 -11.8 ND + - -1 83 T450L -22.6 -9.4 -29.2 + + -1.25 73 T451F -6.3 -7.9 ND + - -0.25 A Reported energies are per dimer. B Eliminated in the FRESCO protocol because of introduction of a solvent-exposed hydrophobic group on the protein surface. C significantly increased thermostability.

101 CHAPTER 4

Characterization of stabilized PjTA variants The five variants that showed a significantly improved apparent melting temperature

(ΔTM,app > 1°C, Fig. 2) carried mutations that were mainly located at low B-factor regions (Fig. 3). These stabilizing mutations were distributed over four different positions: P9, P139, A393 and M419 (Fig. 3). Of these, only A393 is located at a high B-factor region. The presence of most of the mutations in relatively rigid areas indicates that high B-factor regions are not the only areas where mutations can stabilize a protein.

WT 4 1500 A393R M419L P9A P9K 1000 P139K

500

dRelative fluorescence/dT 0

-500 20 40 60 80 100 Temperature (°C) Fig. 2. Thermostabilities of wild-type PjTA and the five best variants determined by the thermofluor method.

To analyze whether the increased thermostability affected the catalytic performance of the mutants, specific activities of the five most stable variants and the wild-type PjTA were tested with (S)-α-methylbenzylamine (MBA) and 6-aminohexanoic acid (6- ACA) (Table 4). MBA is often used for the detection of transaminase activity (76) and 6-ACA is of interest because of its role as an intermediate in the caprolactam/nylon 6 degradation pathway (31, 50). Variants A393R and P9A showed higher activity while P9K showed wild-type activity. Different effects on activity are observed more often as result of thermostabilization protocols (3). On the other hand, variants M419L and P139K displayed slightly decreased activities. Thus, the single-site mutations with improved thermal stability seem to have only a moderate impact on the specific activity.

102 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN

1.5 ˚C 1.25 ˚C 4 1 ˚C ! Fig. 3. Positions of stabilizing mutations in the 3D structure of PjTA. The colored! spheres show the Fig. 3. Positions of stabilizing mutations in the 3D structure of PjTA. The colored stabilizing mutations and the effect on TM,app. Protein flexibility determined by crystallographic B-factors isspheres represented show by the the thickness stabilizing of the backbone. mutations and the effect on TM,app. Protein flexibility determined by crystallographic B-factors is represented by the thickness of the Table 4. Specificbackbone. activities of the PjTA mutants with enhanced thermal stability. Specific activity (μmol min-1 mg-1) Variant (S)-α-Methylbenzylamine 6-Aminohexanoic acid WT Table 4. Specific0.54±0.01 activities of the PjTA mutants0.17±0.01 with enhanced thermal stability. M419L 0.48±0.01 0.14±0.01 WC WC P139K 0.40±0.01 ".%$0;0$!($)0Q0):!=h*+2!*0,0.13±0.01 !*- ?! d('0(,)! P9A 0.64±0.01="?WiWJ%)@:21%,3:2(*0,%! 0.16±0.01 NW<*0,+@%K(,+0$!($0/! P9K fP! 0.55±0.01 D9OLjD9DC! 0.16±0.01 D9CMjD9DC! A393R 0.71±0.01 0.20±0.01 Activities wereJLCEA measured! with a coupled assay, using pyruvateD9LIjD9DC as amine! acceptor and alanine dehydrogenase to coupleD9CLjD9DC its ! conversion to\CFEb alanine to! NADH formation. D9LDjD9DC! D9CFjD9DC! \E

With six published<$)0Q0)0%&!Y%'%!*%(&#'%/!Y0)@!(!$+#.2%/! examples, the FRESCO protocol has(&&(:Z!#&0,-!.:'#Q()%!(&!(*0,%!($$%.)+'!(,/!(2(,0,%! emerged as an efficient strategy for enhancing/%@:/'+-%,(&%!)+!$+#.2%!0)&!$+,Q%'&0+,!)+!(2(,0,%!)+!X<[G!;+'*()0+,9 thermostability (3, 31, 40–42, 67). Computational design and in silico screening of mutant libraries preceeds laboratory expression and stability screening, thereby strongly reducing the amount of work that needs to be done to find stable variants. However, even with careful energy calculations, inspection and MD simulation, the typicalDiscussion success rate of point mutations still does not exceed 10-20%, suggesting that further improvements are desirable. In the work reported here, we examine the With six published examples, the FRESCO protocol has emerged as an efficient use of high-temperature MD simulations as a means to identify relatively flexible surface regions thatstrategy may befor involved enhancing in early thermostability unfolding and (3, triggering 31, 40– 42,aggregation 67). Computational leading design and in silico screening of mutant libraries preceeds laboratory expression and stability screening, thereby strongly reducing the amount of work that needs to be done to find 103 stable variants. However, even with careful energy calculations, inspection and MD simulation, the typical success rate of point mutations still does not exceed 10-20%, suggesting that further improvements are desirable. In the work reported here, we examine the use of high-temperature MD simulations as a means to identify relatively CHAPTER 4

to irreversibe inactivation. Mutations located in or contacting early unfolding regions are expected to have a higher probability of increasing stability, especially in case of large proteins where unfolding is irreversible and controlled by kinetics rather than thermodynamic factors. To examine this approach we designed and constructed a library of 64 variants with single mutations (none of which were located at the subunit interface) at positions that encompass different classes of flexibility. The flexibility classes were identified in high-temperature molecular dynamics simulations and used to assign priority scores to the mutations, high priority areas being regions with highest increase in RMSD in MD simulations. Regions were defined not only as amino acids showing large Cα RMSD 4 but also nearby residues. The mutants were produced and expressed in soluble form. Of the set of 64 variants, 51 were located at 29 positions in high priority areas and 13 substitutions at 9 positions were in non-favoured areas. The effects on stability, as determined by the thermofluor assays, were modest, even for the high priority regions,

with five mutants showing an increase of more than 1˚C of M,appT (success rate 11%, 5/46, 46 corresponding to the 51 mutations in high priority areas with 5 negative controls included to test the stricter energy criteria excluded, see Table 3). The vast majority of the mutations had neutral effects and some were detrimental for stability. The percentage of success found here with FRESCO-designed surface mutations in PjTA is lower than what was reported by Wijma et al. 2014 (3) for another dimeric protein (39). There, a percentage of success of 17% was found amongst point mutations in the first stage of experimental screening with the limonene epoxide hydrolase. Arabnejad et. al. 2016 (67) reported 29 stabilized mutants of halohydrin dehalogenase after the screening of 218 mutants (13%), which shows a similar percentage of success to what is obtained here with PjAT. All five mutants with significant positive effect were located in the predicted early unfolding regions, whereas no such stabilizing mutations were found in the non-flexible regions. We also observed that the use of the stricter energy criteria as implemented elsewhere (71) (requiring -8.2 kJ/mol for Rosetta and simultanously -4.2 kJ/mol for FoldX predictions instead of requiring -2.5 kJ/mol for at least one of both software predictions) did not improve the selection of mutants. No stabilizing variants were found in the resulting smaller set of 12 mutations and 4 out of these 12 mutations were even destabilizing. The destabilization can be due to the introduction in 3 (out of the 4) variants of a hydrophobic group on the protein surface. We have frequently observed that such mutations are proposed by energy calculations (negative ΔGFold) and elsewhere it has been found for a small and well soluble model protein (ThreeFoil) that such mutations indeed had a beneficial effect on FoldΔG but decreased solubility (77). For larger proteins such as enzymes, the lower solubility may decrease thermal stability by accelerating irreversible aggregation, which outweighs the benefits of the improved ΔGFold. Also with limonene epoxide hydrolase it was observed that mutations

104 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN that were predicted to be strongly stabilizing were destabilizing due to introduction of hydrophobic aromatic groups on the protein surface (3). Based on these observations, mutations that introduce hydrophic groups are usually dismissed in the FRESCO protocol before laboratory testing. It appears that introduction of hydrophobic groups on the protein surface is a systematic problem of the prediction algorithms that cannot be solved just by setting the energy criteria for accepting mutations to more restrictive values. Four of the five mutants with enhanced stability showed a modest reduction of catalytic activity (Table 4). An inverse relationship between stability and function has been observed in other enzymes, including citrate synthase (78), a Staphylococcal nuclease (79), thioredoxin (80) and lysozyme (3). Structural inspection provided clues 4 about the cause of loss of (some) activity. For example, M419L is located close to the tunnel-like active site of the enzyme and may influence substrate entry, causing some reduction of enzyme activity. The P9K and P9A surface mutations displayed the highest positive ΔTM,app values (1.5˚C). Position 9 is in the vicinity of a predicted flexible region (Fig. 3). Previously, areas near flexible regions were found to be critical for enzyme stability (81). Additionally, proline is a potent helix disruptor which can adopt just a few conformations. Thus, the substitution by alanine or lysine seems to help the formation of stabilizing secondary structure. The PjAT variant P139K also showed a decrease in the specific activity and an improvement of the thermostability. The replacement of a proline by a lysine may cause an increase in loop flexibility and added a positive charge. Results from studies on ubiquitin, human acylphosphatase, and Cdc42GTPase have shown that the stability of enzymes can be increased via the optimization of the surface charge–charge interactions (82).

105 CHAPTER 4

A B

4

Fig. 4. Location of stabilizing mutations. A, position of M419L, which caused a minor decrease in activity. The PLP cofactor bound in the active site is shown in pink while the location of M419 is shown by the magenta patch on the surface. B, position of P9 in a surface loop. The carbonyl O is hydrogen bonded to Lys142.

The fifth mutation is A393R, located in one of the regions with the highest crystallographic B-factor. It provides a moderate increase in thermostability and a 30% higer activity than wild-type PjTA with both of the tested substrates. Although position 393 is distant from the active site, the replacement of alanine by arginine seems to indirectly influence the catalytic activity. Leferink et al. (83) showed that mutations distant from the active site of a copper-containing nitrite reductase resulted in altered catalytic activity due to minor structural perturbations. Variant P9A, also carrying a substitution distant from the active site, showed a modest increase in activity towards (S)-α-methylbenzylamine. As described above, mutations located far from the active site can influence the activity of the enzymes through minor structural changes. The work reported here demonstrates that this computational-based point mutation strategy has the potential to improve PjTA thermostability and that the use of high-temperature MD simulations is a promising orthogonal method for improving library quality. Nevertheless, in terms of absolute values, both the number of positive mutations and their contribution to thermostability was very modest as compared to results with other proteins. For example, Arabnejad et al. (39) working with a tetrameric

enzyme reported ∆Tmapp between 1 and 13.5˚C. Recent results in our laboratory (84) and reported in the literature by Börner et al. (54, 85) indicate that mutations at the subunit interfaces and mutations influencing cofactor binding may have a large and positive effect on stability of related PLP fold type I transaminases. Dissociation of dimeric or

106 ENHANCING THERMAL STABILITY OF PSEUDOMONAS JESSENII TRANSAMINASE BY COMPUTATIONAL LIBRARY DESIGN tetrameric transaminases leads to inactivation, denaturation, and release of the cofactor pyridoxal phosphate (86, 87), which results in aminotransferases being active just in the multimeric state (88). Further attempts to engineer the stability of PjAT should thus be focused on improving interactions at the dimer interface or with the cofactor. Mutations in these regions may deliver stabilized proteins in which new weak spots appear, maybe on the protein surface, in which case introduction of the surface mutations examined here may have a larger positive effect. In conclusion, the current work suggests that introduction of stabilizing mutations in priority regions identified by high temperature MD may become a useful addition to the FRESCO strategy. Its impact on the engineering of robust enzymes is probably much larger in case of monomeric proteins of low stability as compared to stabilization 4 of multimeric enzymes where irreversible denaturation may be governed less by local unfolding than by global dissociation events.

AUTHOR CONTRIBUTIONS

All authors designed experiments and contributed to the interpretation of the data. H.J.W. performed computational design and simulations. C.M.P. constructed mutans and expressed and characterized the mutant enzymes. C.M.P., H.W., and D.B.J. wrote the manuscript.

107 CHAPTER 4

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111 5Enzymatic network for production of ether amines from alcohols

Cyntia M. Palacio, Ciprian G. Crismaru, Sebastian Bartsch, Vaidotas Navickas, Klaus Ditrich, Michael Breuer, Rohana Abu, John Woodley, Kai Baldenius, Bian Wu, Dick B. Janssen

This work was published in Biotechnol Bioeng (2016) 113:1853-1861

113 ABSTRACT

We constructed an enzymatic network composed of three different enzymes for the synthesis of valuable ether amines. The enzymatic reactions are interconnected to catalyze the oxidation and subsequent transamination of the substrate and to provide cofactor recycling. This allows production of the desired ether amines from the corresponding ether alcohols with inorganic ammonium as the only additional substrate. To examine conversion, individual and overall reaction equilibria were established. Using these data, it was found that the experimentally observed conversions of up to 60% observed for reactions containing 10 mM alcohol and up to 280 mM ammonia corresponded well to predicted conversions. The results indicate that efficient amination can be driven by high concentrations of ammonia and may require improving enzyme robustness for scale-up.

114 ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS

INTRODUCTION

Ether amines and polyether amines are valuable synthetic compounds with applications in diverse areas such as surface chemistry, colloid chemistry, and bioconjugate chemistry (1–3). Polyether amines may be used as curing agents, silica deposition agents, in paintings, or as intermediates in the synthesis of polyamides or polyureas (4–6). Ether amines can be produced chemically by a reaction of haloalkyl ethers with ammonia or diamines at high pH and high temperature (7), or by the cyanoethylation of ether alcohols with acrylonitrile followed by hydrogenation of the corresponding cyanoethers (8). A more cost-effective process would be the direct conversion of an ether alcohol, using ammonia as the amine donor. Chemical manufacturing processes have been developed for such conversions employing metal catalysts (9) or by making use of other well-known chemical reactions (10). However, the lack of enantio- and 5 regioselective control often hampers these processes by formation of undesired side- products. Furthermore, the catalysts are toxic and the reactions typically require harsh conditions involving high energy use and environmental costs (11). Hence, a biocatalytic process would be an attractive alternative if it affords high efficiency and selectivity with a low energy consumption and little use of raw materials. Since there is no enzyme known to catalyze the conversion of an alcohol to the corresponding amine in a single step, multi-enzyme routes have been considered to access amines (12–16). One attractive solution emulates a short metabolic pathway via an enzymatic network process that oxidizes an alcohol to an aldehyde or ketone catalyzed by an alcohol dehydrogenase (ADH), and subsequent transamination of the carbonyl compound to an amine by an aminotransferase (AT). If L-alanine is used as amino donor and NAD as electron-accepting cofactor for the dehydrogenase, their recycling is required for an efficient process. This can be done with an alanine dehydrogenase (AlaDH), which oxidizes the reduced cofactor and synthesizes alanine from pyruvate (17). Theoretically, the recycling would allow the use of only low concentrations of NAD and alanine. In practice, a large excess of alanine has been used (18), which makes it possible to overcome equilibrium or product inhibition issues that might prevent efficient cycling in the network. Variations of this network have been described, e.g. the use of other enzymes for cofactor recycling (13, 19, 17, 20). For example, Tauber et al. (2013) (21) examined regeneration of the reduced nicotinamide cofactor formed during alcohol oxidation by an NADP-dependent alcohol dehydrogenase and an NADPH oxidase, while the NADH required by alanine dehydrogenase was recycled by a formate dehydrogenase. The same group investigated the use of a lactate dehydrogenase to reduce pyruvate to lactate in order to shift the conversion of the aminotransferase step to completion. Such modifications can increase yields, but conversion becomes dependent on auxiliary reactions, i.e. formate oxidation and pyruvate reduction. The two-step transformation of an alcohol to the corresponding

115 CHAPTER 5

amine has also been applied for the conversion of caprolactone to 6-aminohexanoic acid (22), in which case a methyl ester was transiently generated to prevent formation of 6-hydroxyhexanoic acid. Recently, a variation of this network was described in which an engineered amine dehydrogenase rather than an aminotransferase was used for direct incorporation of ammonia into ketones (23). These studies indicate that various measures can be undertaken to improve conversion in an amination network, and raise the questions which factors restrict conversion by a self-sufficient network when no auxiliary reactions are included for recycling of intermediates. To examine the suitability of a self-sufficient network for ether amine formation and study the factors that determine conversion, we investigated a biocatalytic process that uses ether alcohols and ammonia as the substrates to produce the ether amines. For this purpose a redox-neutral enzymatic network of three enzymes was used (18). 5 Different alcohol dehydrogenases, aminotransferases and alanine dehydrogenases were tested, and the characteristics of the system were studied by measurement of reaction equilibria, which are important parameters for the design and optimization of such biocatalytic networks (24). Only few equilibrium constants for amination and alcohol oxidation reactions have been reported in the literature (25–28). We selected a primary ether alcohol (butyldiglycol, 1a) and a secondary ether alcohol (1-butoxy-2-propanol, 2a) as model substrates, since both the alcohols and amines are miscible with water and ether amines derived from similar compounds are used in industrial products. From experimentally determined conversion curves and reaction equilibria it appeared that very high concentrations of ammonia can drive conversion towards effective synthesis

MATERIALS AND METHODS

Substrates and chemicals Butyldiglycol (1a), nicotinamide adenine dinucleotide (NAD+), reduced nicotinamide adenine dinucleotide (NADH), L-alanine, ammonium carbamate and sodium carbonate were purchased from Sigma-Aldrich. Compounds 1b-c and 2a-c were prepared by BASF (Ludwigshafen, Germany). Substrate 2a was the (S)-enantiomer, in agreement with the enantioselectivity of the ADH that was selected. Pyridoxal phosphate (PLP) was purchased from Fisher Scientific and pyruvic acid was acquired from Acros Organics.

Enzymes Enzymes tested as catalysts for the enzymatic network were alcohol dehydrogenases from Geobacillus stearothermophilus 1 (GsADH1, accession number BAA14411), Geobacillus stearothermophilus 2 (GsADH2, CAA80989), Pseudomonas putida (PpADH, ADR59556) or Rhodococcus jostii RHA1 (RjADH, ABG94302.1). Aminotransferases were from Chromobacterium violaceum (CvAT, NP_901695), Vibrio fluvialis (VfAT, AEA39183),

116 ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS and Escherichia coli putrescine aminotransferase (EpTA, NP_417544). The two alanine dehydrogenases examined were from Archeoglobus fulgidus (AfAlaDH, AIG98665.1) and from Vibrio proteolyticus (VpAlaDH, AF070716). The coding DNA segments were obtained by gene synthesis or PCR and cloned into the expression vector pET28b or pBAD to add a hexahistidine tag (Table 1). The constructs were confirmed by DNA sequencing. The enzymes were produced in E. coli C41(DE3) or E. coli TOP10 (Table 1). For this, cells were grown at 37°C in TB medium with 50 µg/ml kanamycin. Expression was induced by addition of 0.8 mM isopropyl-β-D-thiogalactopyranoside (IPTG) (pET system) or 0.02% arabinose (pBAD system) when the optical density (OD600) reached ca. 0.6. Cultivation was continued for 16 h at 28°C and 135 rpm. Cells were obtained by centrifugation and disrupted by sonication at 4°C, followed by centrifugation for 45 min at 15,000 rpm to obtain the cell-free extract. The enzymes were purified in a two-step procedure using metal affinity chromatography (HisTrap HP column; 5 ml; GE Healthcare) and a desalting 5 step (HiPrep 26/10 column, 53 ml, GE Healthcare). The enzymes were stored frozen at -20 oC in 50 mM potassium phosphate, pH 8.0.

Alcohol dehydrogenase reactions Activities of different alcohol dehydrogenases were measured by following NAD+ 3 -1 ‑1 reduction at 340 nm (ε NADH = 6.22×10 M cm ). The reaction mixtures of 1 ml contained ammonium carbamate (40 mM, pH 9), alcohol dehydrogenase (1 mg/ml), NAD+ (1 mM) and alcohol 1a or 2a (10 mM). For estimating reaction equilibria, the assay system consisted of the same buffer, a suitable amount ofGs ADH (ca. 0.1 mg/ml), NAD+ (0.4 mM) and alcohols 1a (5 mM) or 2a (0.4 mM) in a final volume of 1 ml. For the reverse reaction the same enzyme concentration and buffer system were used with NADH (0.4 mM) and aldehyde 1b (5 mM) or ketone 2b (0.4 mM). The formation or depletion of NADH was followed at 340 nm at 30°C. Equilibria were calculated from Equation 2, assuming stoichiometric relationships between the change in NADH and alcohol or aldehyde.

Aminotransferase reactions Activities of different aminotransferases were determined by following acetophenone formation at 245 nm (ε = 12 mM−1 cm−1) as described by Schätzle et al. (2010) (29). The reaction mixtures contained 1-phenylethylamine (2 mM), 1b or 2b (10 mM), sodium phosphate (50 mM, pH 7) and aminotransferases (0.2 mg/ml). Equilibria were estimated by incubating purified enzyme in ammonium (sodium) carbamate buffer (40 mM, pH 9) with CvAT (0.35 mg/ml), L-Ala (10 mM), ketone 2b (1 mM), and PLP (0.35 mM). Samples (1350 µl) were taken and quenched by adding NaOH (150 µl, 10 N) and ethyl acetate (500 µl). The mixture was stirred with a Vortex mixer for 30 s, sonicated, centrifuged for 1 min at 13,200 rpm and analyzed. The concentrations of the ketone 2b and amine 2c were determined by GC analysis, while the concentrations of pyruvate and L-Ala were calculated from the stoichiometry. Equilibria were calculated with Equation 3.

117 CHAPTER 5

Alanine dehydrogenase reactions Reaction mixtures contained enzyme (0.002 mg/ml), ammonium carbamate (40 mM, pH 9), NADH (0.2 mM), pyruvate (10 mM) and ammonium carbonate (125 mM). Activities were calculated from the rates of pyruvate-dependent NADH oxidation, measured at 340 nm. The assay system for establishing the equilibrium of the alanine recycling reaction consisted of sodium carbonate (40 mM, pH 9), NAD (0.4 mM), VpAlaDH (0.004 mg/ml) and L-alanine (2.5 mM) in a final volume of 1 ml. The conversion was followed by monitoring the formation of NADH at 340 nm, while the concentrations of the other components were calculated from the reaction stoichiometry.

Network reactions Three-enzyme conversions were routinely performed in reaction mixtures (15 ml) 5 containing ammonium carbamate buffer (40 mM, pH 9), alcohol 1a or 2a (10 mM, final concentration), NAD+ (1 mM), L-Ala (0.5 mM), PLP (0.35 mM), GsADH (0.1 mg/ml), VpAlaDH (0.004 mg/ml for 1a and 0.04 mg/ml for 1b) and CvAT (0.064 mg/ml). The mixtures were incubated in 50 ml glass bottles at 30°C, and samples were taken at different times for analysis by gas chromatography (GC). Apparent equilibrium constants (K’) were calculated with Equation 1. For these calculations and in Tables and Figures we used nominal concentrations of ammonia representing the sum of protonated and unprotonated species and assuming complete dissociation of carbamate to 2 eq. of ammonia (30). Optimization was studied by individually varying concentrations of ammonium (80 mM, 200 mM, 400 mM, 1 M or 2 M), alcohol 1a (5 mM, 10 mM, 20 mM, 50 mM and 100mM), L-Ala (0.5 mM, 1 mM, 2.5 mM and 5 mM) and NAD+ (0.125 mM, 0.25 mM, 0.5 mM and 1 mM). PLP was kept at 0.35 mM and enzyme concentrations were GsADH at 0.1 mg/ ml, VpAlaDH at 0.004 mg/ml and CvAT at 0.064 mg/ml.

RESULTS AND DISCUSSION

Enzyme production and selection To establish a three-enzyme network for alcohol to amine conversion, we first examined several enzymes for each reaction step. We cloned and expressed four alcohol dehydrogenases for the oxidation of 1a and 1b, three transaminases for the transamination of the corresponding aldehyde (1b) and ketone (2b), and two alanine dehydrogenases for the recycling of the cofactors and amino donors (Table 1). All enzymes were expressed in soluble form and were purified by His-tag affinity chromatography. Activity assays with the purified enzymes were performed as described under Materials and Methods to select suitable enzymes for the designed network. The results in Table 1 show that the thermostable ADH from G. stearothermophilus 1 (GsADH1)

118 ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS and the aminotransferase from C. violaceum (CvAT) had the highest activity towards 1a and 2a, and 1b and 2b, respectively. These were therefore selected for further use. The thermostable and highly active AlaDH from V. proteolyticus (VpAlaDH) was used for cofactor recycling because of its high activity and high overexpression in E. coli.

Network reactions Having selected suitable enzymes, we tested the possibility for a network reaction with 1a and 2a as substrates (10 mM) in the presence of all three enzymes (Fig. 1). In the initial tests, 8 equivalents of ammonia and 1 equivalent of L-Ala were added (final concentrations 80 mM and 10 mM, respectively). For both substrates, conversion of ether alcohol to ether amine reached a promising 40%, using the network reaction conditions described in Materials and Methods. 5 Table 1. Expression and catalytic activities of enzymes for use in amination network. Expression Expression Activity c (mU /mg) Reaction Enzymes Genea system (mg/L) 1a/1b/ L-Ala 2a/2b/L-Ala Rhodococcus jostii RHA1 PCR pET/C41(DE3) 6 <1 <1 Geobacillus stearothermophilus 1 PCR pET/C41(DE3) 100 74 834 ADH Geobacillus stearothermophilus 2 PCR pET/C41(DE3) 200 55 483 Pseudomonas putida Synb pET/C41(DE3) 10 12 46 Vibrio fluvialis Synb pET/C41(DE3) 160 3 62 AT Chromobacterium violaceum PCR pET/C41(DE3) 200 5 78 E. coli putrescine AT Synb pET/C41(DE3) 80 <1 <1 Archeoglobus fulgidus PCR pBAD/TOP10 20 2x104 AlaDH Vibrio proteolyticus PCR pBAD/TOP10 300 1x104 a Gene obtained by PCR amplification of genomic DNA or as synthetic gene.b Synthetic gene. c One unit of enzyme activity corresponds to a conversion of 1 µmole.min-1 under the assay conditions used. Data represent averages of measurements done in duplicate or triplicate. Average standard deviations estimated from multiple duplicate measurements were less than 10% of the reported values.

We next examined the effect of varying concentration of substrates on the conversion, aiming at a higher yield of the ether amines. For this, we performed time course experiments in which supposedly important conditions were varied, especially the concentrations of alcohol substrate, cofactor (NAD+), L-Ala and ammonium. First, different concentrations of alcohol 1a were tested in the range from 5 mM to 100 mM. The highest yields and conversions rates were observed with the lower concentrations of 1a (Fig. 2A). The highest accumulation of product 1b was obtained with 50 mM alcohol, but the conversion of substrate to amine decreased at the highest concentration of 1a almost to zero. Further reactions were carried out with alcohol concentrations in the range of 5 mM to 10 mM, because these gave the best conversion (Fig. 2A).

119 The highest yields and conversions rates were observed with the lower concentrations of 1a (Fig. 2A). The highest accumulation of product 1b was obtained with 50 mM alcohol, but the conversion of substrate to amine decreased at the highest concentration of 1a almost to zero. Further reactions were carried out with alcohol concentrations in theCHAPTER range 5 of 5 mM to 10 mM, because these gave the best conversion (Fig. 2A).

5

Fig. 1. Enzymatic network with 1a and 2a as substrates. The proposed enzymatic cycle Fig.encompasses 1. Enzymatic 3 enzymes: network an with alcohol 1a anddehydrogenase 2a as substrates. (GsADH1) The that proposed converts enzymaticthe alcohol cycle to a ketone or an aldehyde; a transaminase (CvAT) that converts the ketone or the aldehyde to the encompasses 3 enzymes: an alcohol dehydrogenase (GsADH1) that converts the alcohol amine with L-Ala as the amino donor; and an alanine dehydrogenase (VpAlaDH) that converts topyruvate a ketone to L-Alaor an with aldehyde; simultaneous a transaminase recycling of NADH (Cv AT)to NAD that+. converts the ketone or the

aldehyde to the amine with L-Ala as the amino donor; and an alanine dehydrogenase Next, the effect of increasing ammonium concentrations was measured since this (VpAlaDH) that converts pyruvate to L-Ala with simultaneous recycling of NADH to NAD+. might shift the equilibrium of the reaction. However, increasing the concentration by adding different level of ammonium (80 mM, 200 mM and 1M) did not improve the Next, the effect of increasing ammonium concentrations was measured since this percentage of conversion of 1a to 1c, and conversion was significantly reduced above might200 mMshift ammoniathe equilibrium while precipitationof the reaction. of enzymesHowever, was increasing observed. the Theconcentration best conversion by addingwas observeddifferent atlevel 80 mMof ammonium of ammonia (80 (Fig. mM, 2B). 200 mM and 1M) did not improve the We also examined the effect of varying L-Ala concentrations. The conversion to amine percentage of conversion of 1a to 1c, and conversion was significantly reduced above 1c was only slightly affected by the level of L-Ala added (Fig. 2C). Importantly, at a low 200concentration mM ammonia of L-Alawhile (0.5 precipitation mM) conversion of enzymes to amine was already observed. reached The 30%, best andconversion conversion waswas observed not better at 80 at mMhigher of ammonialevels. Furthermore, (Fig. 2B). L-Ala was indeed recycled, since the level of amine produced (3 mM) was 6-fold higher than the level of L-Ala added (0.5 mM). Subsequent experimentsWe also examinedon the amination the effect of 1aof andvarying 2a were L-Ala carried concentrations. out with 0.5 ThemM conversionL-Ala. to amineFinally, 1c was the only level slightly of NAD affected+ was varied. by the Good level conversionof L-Ala added was obtained(Fig. 2C). with Importantly, 1 mM NAD + at addeda low concentration(Fig. 2D), whereas of L conversion-Ala (0.5 mM) was reducedconversion when to amine the cofactor already concentration reached 30%, was lower. Since the final concentration of product 1c (4 mM) was higher than that of cofactor (1 mM), also AlaDH-mediated cofactor recycling was working properly. Further experiments were carried out with 1 mM NAD+.

120 ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS

A series of optimization measures were tested, in which substrate, amino donor, ammonium and cofactor concentrations were varied in different combinations. These attempts did not lead to identification of reaction conditions that improved conversion beyond 40% for 1a to 1c and conversion also did not exceed 40% for 2a to 2c. This suggests that equilibrium factors, in combination with effects of ammonia on enzyme activity, were limiting the degree of conversion.

Reaction equilibria In agreement with observations on other reactant systems (31), the thermodynamic equilibrium was postulated to limit conversion in the three-enzyme amination network. To examine this possibility, we measured the apparent equilibrium constants of the three-enzyme network and of separate reactions. Following the notation of Goldberg (2014) (32), the equilibrium for the overall conversion of alcohol to amine (K’ ) is given N 5 by Equation (1), while Equation (2) gives the apparent equilibrium constant for alcohol oxidation (K’o), Equation (3) for the aminotransferase reaction, and K’r in Equation (4) stands for the recycling step or alanine dehydrogenase reaction. The numbers are pH- dependent. All measurements were done at pH=9.0.

A B 40 40 5 mM 80 mM 10 mM 200 mM 20 mM 30 30 400 mM 50 mM 1000 mM )

100 mM ) 2000 mM 20 20 Conversion (% 10 Conversion (% 10

0 0 0246 0246 Time (days) Time (days)

C 40 D 40 5 mM 1 mM 2.5 mM 0.5 mM 1 mM 0.25 mM 30 30 0.5 mM 0.125 mM ) )

20 20 Conversion (% Conversion (% 10 10

0 0 0246 0246 Time (days) Time (days)

Fig. 2. Time course of ether amine formation under different reaction conditions. Panels: A, varying substrate alcohol 1a; B, varying ammonium; C, varying amino donor (L-alanine); D, varying cofactor (NAD+) concentration.

121 # "!!! # $! $!!

%%!! &!! %! &!!

CHAPTER 5 Fig. 2.. TimeTime coursecourse ofof etherether amineamine formationformation underunder differentdifferent reactionreaction conditions.conditions. Fig. 2. Time course of ether amine formation under different reaction conditions. Panels: A, varying substrate alcohol 1a;; B,B, varyingvarying ammonium;ammonium; C,C, varyingvarying aminoamino donordonor Panels: A, varying substrate alcohol 1a; B, varying ammonium; C, varying amino donor ++ (L(L--alanine); D, varying cofactor (NAD +)) concentration.concentration. In these equations, [Ami] stands(L-alanine); for the D, equilibrium varying cofactor concentrations (NAD )) concentration.concentration. of amin es 1c or 2c,

[Alc] stands for the alcohols 1a or 2a, [Ald] stands for aldehyde ++ 1b or ketone 2b,, [Pyr][Pyr] forfor pyruvate,pyruvate, andand [NH[NH44+]] isis thethe totaltotal nominalnominal concentrationconcentration ofof 1b or ketone 2b, [Pyr] for pyruvate, and [NH4 ] is the total nominal concentration of ammonia.ammonia. + 1b or ketone 2b, [Pyr] for pyruvate,ammonia. and [NH4 ] is the total nominal concentration of

ammonia. (1)(1) (1) (1) !"# !! !"# !! ! ! !"# !"!! !! ! !"# !"! (2) ! ! (2)(2) !"#$ !"# !! !"#$ !"# !! ! !! ! !"#! !"# !! (3) ! ! !"# !"# ! (3)(3) !"# !"# !! !"# !"# !!! !! ! !"# !"# (4) ! ! !"# !"# (4)(4) 5 ! (4) !"#! !!!"#!! The other!! abbreviations!"# have!!"# their! usual meaning. By convention, water is fixed at 1 !! ! The other abbreviations have! their! ! usual!"# meaning.!"!! !!!"#$ By !convention,! water is fixed at 1 and and does! not! appear!"# in!" the! equilibrium!!"#$! constants (32). All concentrations are lumped for does not appear in the equilibrium constants (32). All concentrations are lumped for different protonation states, which are obviously pH dependent. different protonation states, which are obviously pH dependent. The apparent equilibrium constant of the whole network should match the The apparent equilibrium constant of the whole network should match the equilibrium constants ofequilibrium the separate constants reactions of the separate (Equation reactions 5). (Equation 5).

(5) (5) ! ! ! ! While prior studies have shown𝐾𝐾! that= 𝐾𝐾 the! ∙ 𝐾𝐾equilibrium! ∙ 𝐾𝐾! of transamination reactions with While prior studies have shown that the equilibrium of transamination reactions with a a ketone or aldehyde as substrate and L-Ala as amino donor is in the direction of the amino acid (33), little ketoneis known or aldehyde about asthe substrate equilibrium and L-Ala of theas amino oxidation donor reactionis in the directionof of the ether alcohols to etheramino ketones acid or (33), ether little aldehydes. is known about Some the equilibriumequilibrium of data the oxidation of alcohol/ reaction of ether ketone redox reactionsalcohols have been to ether reported ketones in or the ether literature aldehydes. (28, Some 34), butequilibrium the equilibrium data of alcohol/ketone constants were calculatedredox at differentreactions havetemperatures, been reported buffer in the conditions, literature (28,and 34),with differentbut the equilibrium compounds. In order toconstants establish were the calculated position at differentof the various temperatures, equilibria, buffer reactionsconditions, withand with different the three enzymes werecompounds. performed In separatelyorder to establish as described the position in Materialsof the various and equilibria,Methods. reactions with

All the equilibrium constantsthe three enzymes (K’N, K’ owere, K’r and performed K’t) shown separately in the as Tabledescribed 2 were in Materials calculated and Methods. from experimental measurements, except for the value of K’ for the reaction of 1b All the equilibrium constants (K'N, K'o, tK'r and K't) shown in the Table 2 were to 1c. Due to the reactivity of 1b with product 1c under the conditions of sample calculated from experimental measurements, except for the value of K't for the reaction preparation, the analysis of 1c was not reliable. A value for K’t was estimated from the other experimentally measuredof 1b to 1c. constants. Due to the reactivity of 1b with product 1c under the conditions of sample preparation, the analysis of 1c was not reliable. A value for K't was estimated from the The apparent equilibrium constants K’o calculated with Equation 2 from conversion data (Fig. 3A) showed thatother alcohol experimentally oxidation measured is unfavorable constants. for substrates 1a and 2a (Table -3 2). Similar equilibrium constants The wereapparent reported equilibrium for 1-butanol constants (1.8K'o·10 calculated) and for with 1-octanol Equation 2 from oxidation (1.1·10-3) confirmingconversion that data NAD (Fig.+-coupled 3A) showed alcohol that alcoholoxidation oxidation is thermodynamically is unfavorable for substrates 1a and 2a (Table 2). Similar equilibrium constants were reported for 1-butanol (1.8·10-3) and for 1-octanol oxidation (1.1·10-3) confirming that NAD+-coupled alcohol oxidation is thermodynamically rather unfavorable (34). Especially for ether alcohol 1a, the 122 equilibrium is strongly in the direction of the alcohol. The aminotransferase equilibrium (Equation 3) of 2b and 2c was estimated by GC analysis (Fig. 3B). The equilibrium constants appeared to be highly unfavorable both

for ether aldehyde and ether ketone amination (Table 2). Especially the K't value for conversion of ether ketone 2b to amine 2c illustrates poor acceptance of an amino group. The observed unfavorable equilibrium of the aminotransferase reaction is in agreement with the equilibrium constant reported for the transamination of 2- ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS rather unfavorable (34). Especially for ether alcohol 1a, the equilibrium is strongly in the direction of the alcohol. The aminotransferase equilibrium (Equation 3) of 2b and 2c was estimated by GC analysis (Fig. 3B). The equilibrium constants appeared to be highly unfavorable both for ether aldehyde and ether ketone amination (Table 2). Especially the K’t value for conversion of ether ketone 2b to amine 2c illustrates poor acceptance of an amino group. The observed unfavorable equilibrium of the aminotransferase reaction is in agreement with the equilibrium constant reported for the transamination of 2-oxoglutarate and L-Ala (2.9·10-3) (25). Additionally, the equilibrium constant of the transamination of acetophenone with alanine to produce 1-phenylethylamine is reported to be 8.81·10−4 (33), which is also strongly favorable towards the substrates. Obviously, transfer of the charged (at neutral pH) amino group from the zwitterionic L-Ala to an apolar acceptor is not favored. 5

Table 2. Experimental equilibrium constants at 30°C and pH 9.0. Mean values are reported ± the standard error of the mean. K’ (M-1) K’ K’ K’ (M-1) N Substrate o t r (ADH) (AT) AlaDH Experimental Calculated -4 1a, 1b 2.6·10 6.1·10 -2 a 13.1 ± 0.45 - ± 2.9 10-6 8.23·10 +5 -4 ± 4.23 10+4 0.14 4.0·10 12.1 ± 1.28 46b 2a, 2b ± 0.004 ± 4.7 10-6 a b This value was calculated from the experimental values of K’o, K’r and K’N, from Equation (5). This value was calculated with Equation (5).

The alanine dehydrogenase equilibrium was measured by following NADH formation (Fig. 3C). The equilibrium constant appeared highly favorable for recycling of alanine as amine donor and NAD+ as electron acceptor for alcohol oxidation, and predicts an L-alanine:pyruvate ratio of 82,000 per M of ammonia present at equal concentrations of NAD+ and NADH. The equilibrium constants obtained here are in the same range as those reported for similar substrates by Goldberg et al. (1993; 2007) (28, 34). From these individual equilibria it appears that conversion of 1a to 1c and of 2a to 2c are both thermodynamically feasible (Table 2), mainly due to the alanine recycling reaction, which strongly favors alanine and NAD formation thereby driving the alcohol oxidation and aminotransferase reactions.

123 CHAPTER 5

A "! B#! ! "! #!

!

!

! %! &! ! %! &! C D ! !

5

!

! Fig. 3. Estimation of reaction equilibria. Panel A: Formation of NADH by GsADH acting on Fig.the oxidation3. Estimation of alcohol of reaction 2a Panel equilibria. B: Production Panel A: Formationof ketone of2b NADH catalyzed by Gs byADH Cv AT.acting Panelon theC: oxidationNADH formation of alcohol in 2a the Panel conversion B: Production of L-Ala of ketoneto pyruvate, 2b catalyzed catalyzed by CvbyAT. VpAlaDH.Panel C:Panel NADH D: formationProgress incurves the conversionfor alcohol of L-consumptionAla to pyruvate, and catalyzedamine by Fig. 3. Estimation of reaction equilibria. Panel A: Formation of2a NADH by GsADH acting on 2c the VpAlaDH. Panel D: Progress curves for alcohol 2a consumption and amine 2c Fig.oxidation 3. Estimation ofproduction alcohol of 2ainreaction thePanel complete B: equilibria.Production enzymatic Panelof network.ketone A: Formation 2bReaction catalyzed conditions of by NADH CvAT. are byPanel describedGs C:ADH NADH in acting formation inMaterials theproduction conversion and inMethods. the of L-Alacomplete Curves to pyruvate, enzymatic are representative catalyzed network. by examplesReaction VpAlaDH. ofconditions Panelexperiments D: Progressare describedthat werecurves in onfor the alcohol oxidation 2a consumption of alcohol and 2a aminePanel 2c B: production Production in theof ketonecomplete2b enzymatic catalyzed network. by Cv AT. performedMaterials in andduplicate. Methods. Curves are representative examples of experiments that were Reaction conditions are described in Materials and Methods. Curves are representative examples Panel C: NADHperformed formation in duplicate. in the conversion of L-Ala to pyruvate, catalyzed by of experiments that were performed in duplicate. VpAlaDH. ImplicationsPanel D: forProgress network reactions curves for alcohol 2a consumption and amine 2c Implications for network reactions productionThe in therelationship complete between enzymatic the overall network. reaction Reaction equilibrium conditions K'N and the are theoretical described in ImplicationsThe for relationship network betweenreactions the overall reaction equilibrium K'N and the theoretical Materials andmaximal Methods. conversion Curves in the are three representative-enzyme network examples was examined. of experiments Since a very thatlow were + The relationshipconcentrationmaximal between conversion of NAD the wasin overallthe used, three thereaction- enzymeaccumulation networkequilibrium of aldehydewas examined.K’N orand ketone theSince is theoreticalnegligible a very low performed in duplicate. + maximal conversionin Equationconcentration (1), in and theof NADammonia three-enzyme was-dependent used, the network conversionaccumulation was of alcoholofexamined. aldehyde to amine or Since ketone is given a is very negligibleby: low concentration of NAD+ was used, the accumulation of aldehyde or ketone is negligible in Equation (1), and ammonia-dependent conversion of alcohol to amine is given by: Implicationsin Equation (1), for and network ammonia-dependent reactions conversion of alcohol to amine is given by: (6) The relationship between the overall reaction equilibrium K'N and the theoretical (6) ! !"# (6) ! ! maximal conversion ! !! in! !"#the! three!!!"#-enzyme!!! !"#!"! ! network!!!"#!! was examined. Since a very low ! ! ! !"# !!!!"#!!! !"! !!!!"#!! where [Alc]!0 is+! the initial concentration of the ether alcohol and [ ]0 is the initial concentrationwhere [Alc]0 isof the NAD initialwas concentration used, the accumulation of the ether alcoholof aldehyde and or ketone is the is negligibleinitial where [Alc] is the initial concentration of the ether alcohol and [ ! ] is the initial concentration concentration of ammonia of0 ammon (sumia of(sum ionization of ionization states). states). Conversion Conversion in in the the! wholewhole0 networknetwork in Equation (1), and ammonia-dependent conversion of alcohol to !"amine! is given by: can be calculatedconcentration from: of ammonia (sum of ionization states). Conversion in the! whole network can be calculated from: !" can be calculated from:

(7) ! ! ! ! ! ! ! ! ! ! (7) !!!"#! !!!"! !!!!! !! !!!"#! !!!"! !!!!! ! !(6)!!!"# ! !!"! !! !!"#! ! ! ! !"# ! ! !!"#!!! ! ! !!!!"#!! Equation! ! (7)! describes!"# !! !the!"# theoretical!!! !" !maximal!!!!"# conversion!! as a function of the overall reaction equilibrium K'N and the initial substrate concentrations, and was used to where124 [Alc]0 is the initial concentration of the ether alcohol and [ ]0 is the initial calculate the maximum conversion at different concentrations of ammonia (Fig. 4A). To ! concentrationvisualize the conditions of ammon at whichia (sum amination of ionization becomes feasible, states). we Conversion also plotted the in !">90% the! whole network

canconversion be calculated window from:as a function of K'N and the initial ammonia loading (Fig. 4B). The

plot shows that K'N should be at least 10-100 to obtain a product yield exceeding 90%.

The dependence of the yield on K'N and ammonia concentration is further plotted in Fig.

4C, again illustrating the requirement of a high K'N (> 10) and high ammonium concentrations (> 0.5 M) for effective amination. These results show that the conversion of the three-enzyme amination networks can be limited by an unfavorable equilibria of the final amination steps yielding amines 1c and 2c and of the formation of the intermediates aldehyde 1b and ketone 2b. The use of a high ammonium concentration can drive the equilibrium to product formation.

Reaction Optimazation Using Equation 7 as a guide, we attempted to further improve conversion of alcohol to amine. For reactions 1a to 1c and 2a to 2c, at least 0.7 M of ammonia is predicted to be required for a good conversion (>95% yield, Fig. 4A). Therefore, conversion was tested with a range of ammonia concentrations varying from 80 mM to 1 M. However, addition of ammonia to concentrations exceeding 200 mM caused precipitation of the enzymes, as indicated by visual turbidity and SDS-PAGE analysis of the precipitate. The latter indicated that all three enzymes formed precipitating aggregates (data not shown). Therefore, reactions were run with repeated addition of smaller amounts of ammonia (concentration 80 mM) and of enzyme (GsADH (0.1 mg/ml), VpAlaDH (0.004 mg/ml) and CvAT (0.064 mg/ml)), and the production of ether amine was followed over time. This strategy resulted in improved yields. The highest conversion was found with stepwise addition of a total 280 mM ammonium, which afforded a conversion of 60% for 1a to 1c and for 2a to 2c (Fig. 5). To the best of our knowledge, ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS

Equation (7) describes the theoretical maximal conversion as a function of the overall reaction equilibrium K’N and the initial substrate concentrations, and was used to calculate the maximum conversion at different concentrations of ammonia (Fig. 4A). To visualize the conditions at which amination becomes feasible, we also plotted the

>90% conversion window as a function of K’N and the initial ammonia loading (Fig. 4B).

The plot shows that K’N should be at least 10-100 to obtain a product yield exceeding

90%. The dependence of the yield on K’N and ammonia concentration is further plotted in Fig. 4C, again illustrating the requirement of a high K’N (> 10) and high ammonium concentrations (> 0.5 M) for effective amination. These results show that the conversion of the three-enzyme amination networks can be limited by an unfavorable equilibria of the final amination steps yielding amines 1c and 2c and of the formation of the intermediates aldehyde 1b and ketone 2b. The use of a high ammonium concentration can drive the equilibrium to product formation. 5 Reaction Optimization Using Equation 7 as a guide, we attempted to further improve conversion of alcohol to amine. For reactions 1a to 1c and 2a to 2c, at least 0.7 M of ammonia is predicted to be required for a good conversion (>95% yield, Fig. 4A). Therefore, conversion was tested with a range of ammonia concentrations varying from 80 mM to 1 M. However, addition of ammonia to concentrations exceeding 200 mM caused precipitation of the enzymes, as indicated by visual turbidity and SDS-PAGE analysis of the precipitate. The latter indicated that all three enzymes formed precipitating aggregates (data not shown). Therefore, reactions were run with repeated addition of smaller amounts of ammonia (concentration 80 mM) and of enzyme (GsADH (0.1 mg/ml), VpAlaDH (0.004 mg/ml) and CvAT (0.064 mg/ ml)), and the production of ether amine was followed over time. This strategy resulted in improved yields. The highest conversion was found with stepwise addition of a total 280 mM ammonium, which afforded a conversion of 60% for 1a to 1c and for 2a to 2c (Fig. 5). To the best of our knowledge, these are the highest conversions reached in such a three- enzyme network for secondary amine production using purified enzymes as catalysts (21).

125 CHAPTER 5 these are the highest conversions reached in such a three-enzyme network for secondary amine production using purified enzymes as catalysts (21). A B

5

C

Fig. 4. Maximal conversion in amination networks based on equilibria. Panel A: predicted maximal Fig.conversion 4. Maximal of 10 mMconversion ether alcohol in amination to the corresponding networks ether based amine on with equilibria. different Panel concentrations A: of ammonia. The solid line represents K’ = 13.1 for reaction 1a to 1c. The dashed line represents predicted maximal conversion of 10 mM Nether alcohol to the corresponding ether amine K’N = 12.1 for reaction 2a to 2c. Panel B: feasibility of operation window of the amination network

withas adifferent function ofconcentrations K’N and ammonia of concentration. ammonia. The Lines: solid dotted line line, represents [alcohol] K'0 N= 0.1= 13.1M; short for dashed

line, [alcohol]0 = 0.5 M; long dash, [alcohol]0 = 1 M. Panel C: Surface representing the theoretical reaction 1a to 1c. The dashed line represents K'N = 12.1 for reaction 2a to 2c. Panel B: maximal conversion (%) dependent on the ammonia concentration and the K’N of the network. feasibility of operation window of the amination network as a function of K'N and

ammonia concentration. Lines: dotted line, [alcohol]0 = 0.1 M; short dashed line, The time course experiment with stepwise addition of ammonium and enzyme [alcohol] = 0.5 M; long dash, [alcohol] = 1 M. Panel C: Surface representing the showed0 that the accumulation of amine0 correlated reasonably well with predictions for theoreticalmaximum maximal conversion conversion based (%)on reactiondependent equilibria on the ammonia (Fig. 5), suggesting concentration that and conversions the K'indeedN of the became network. equilibrium-limited. The final product concentrations of amines 1c and 2c were 6 mM, exceeding the level of added nicotinamide cofactor (1 mM NAD+) and

126 The time course experiment with stepwise addition of ammonium and enzyme showed that the accumulation of amine correlated reasonably well with predictions for maximum conversion based on reaction equilibria (Fig. 5), suggesting that conversions indeed became equilibrium-limited. The final product concentrations of amines 1c and 2c were 6 mM, exceeding the level of added nicotinamide cofactor (1 mM NAD+) and L-Ala (1 mM for 1a), and again indicating effective recycling in the alanine dehydrogenase reaction. This is in agreementENZYMATIC NETWORK with the FOR PRODUCTIONequilibrium OF ETHERcalculations, AMINES FROM which ALCOHOLS showed that cofactor recycling is an essential component of the network since it drives the overall conversion towards amine synthesis. L-Ala (1 mM for 1a), and again indicating effective recycling in the alanine dehydrogenase reaction.Whereas This iscofactor in agreement recycling with networks the equilibrium were reported calculations, earlier (35 which–37) , showedamination that networkscofactor recyclingare usually is anoperated essential in thecomponent presence ofof thean excessnetwork of since L-Ala, it driveswhich themay overall be addedconversion up to towards a 25-fold amine excess synthesis. (18, 19). Alternatively, amination is driven by an Whereas cofactor recycling networks were reported earlier (35–37), amination additional redox reactions, such as the conversion of NADH to NAD+ by an NADH networks are usually operated in the presence of an excess of L-Ala, which may be oxidaseadded up(38) to, aor 25-fold the conversion excess (18, of 19). pyruvate Alternatively, to lactate amination (33). For is drivenexample, by anKlatte additional and Wendredoxisch reactions, (2014) such(19) usedas the whole conversion cells expressing of NADH theto NADthree+ enzymesby an NADH of the oxidase network (38), withor the addition conversion of cofactors,of pyruvate amino to lactate donor, (33). ammonia For example, source, Klatte and and substrates. Wendisch They (2014) (19) used whole cells expressing the three enzymes of the network with addition of described a conversion of 100% with 1,10-diaminodecane (10 mM) with addition of cofactors, amino donor, ammonia source, and substrates. They described a conversion 250of 100% mM (25with equivalents) 1,10-diaminodecane of L-alanine (10. Equimolar mM) with concentrations addition of 250 of alaninemM (25 and equivalents) alcohol substrateof L-alanine. were Equimolar effective concentrations when transamination of alanine was and stimulated alcohol substrateby oxidase were-mediated effective 5 conversionwhen transamination of the produced was pyruvatestimulated (17) by. oxidase-mediated conversion of the produced pyruvate (17).

!

! !

!

"! 1 0 # 1 0 ! ) 8 ) 8 M M m m ( (

n n 6 6 o o i i t t a a r r t t n n 4 4 e e c c n n o o C C 2 2

0 0 0 2 4 6 8 1 0 0 2 4 6 8 1 0 T im e (d a y s ) T im e (d a y s )

Fig. 5. Time course of alcohol to amine conversion by a three-enzyme network. Panel A: observed conversion of alcohol 1a (squares) to amine 1c (closed circles) as compared to predicted maximum conversion (inverted triangles, calculated using Equation 7). The concentration of aldehyde 1b remained below the detection limit (<0.03 mM). Panel B: observed conversion of alcohol 2a (squares) to ketone 2b (triangles) and amine 2c (closed circles) and theoretical maximum conversion (inverted triangles). The reactions were carried out at 30°C in ammonium carbamate buffer (40 mM, pH 9), substrate alcohol (1a) or (2a) (10 mM), NAD+ (1 mM), PLP (0.35 mM), L-Ala (0.5 mM), GsADH (0.1 mg/ml), VpAlaDH (0.004 mg/ml) and CvAT (for 1a: 0.064 mg/ml, for 2a: 0.35 mg/ml). Pulses of ammonium and re-addition of enzyme took place after sampling at 4 days (40 mM ammonium), 6 days (80 mM), 7 days (40 mM) and 8 days (80 mM) for 1a and 2a. Samples were analyzed in duplicate. Data show a representative example of an experiment carried out in duplicate.

127 CHAPTER 5

CONCLUSION

In conclusion, the biocatalytic conversion of ether alcohols to the corresponding amines with ammonia as the sole additional substrate would be an attractive process. In the current study, we describe an amination cycle using an alcohol dehydrogenase, an aminotransferase, and an alanine dehydrogenase that recycles both the nicotinamide cofactor (NAD+) for the alcohol dehydrogenase and the amine donor alanine (L-Ala) for the aminotransferase. Equilibrium measurements showed that conversion of alcohol to aldehyde or ketone is disfavored, as is the amination of aldehyde and ketone. The overall conversion of alcohol to amine is based on the alanine dehydrogenase-mediated formation of L-Ala and NAD+. Using measured and computed equilibrium constants, theoretical maximum conversions and feasible operation windows were calculated. 5 High ammonia concentrations can drive the overall reaction, giving conversions of up to 60%, in agreement with equilibria. The results further suggest that enzyme robustness, especially resistance and maintenance of activity at high concentrations of ammonia and high pH, is a key factor when pursuing practical application of the suggested amination network.

AUTHOR CONTRIBUTIONS

CMP designed, performed and evaluated the biocatalytic transformations, CGC and SB helped with cloning, VN, CD, MB and KB suggested the cascade and provided chemicals and analytical protocols, RA and JMW advised on the thermodynamic analysis, SB, BW and DBJ supervised the work, CMP wrote the paper, which was edited by BW and DBJ.

128 ENZYMATIC NETWORK FOR PRODUCTION OF ETHER AMINES FROM ALCOHOLS

REFERENCES

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28. Goldberg R, Tewari Y, Bhat T. 2007. Thermodynamics of enzyme-catalyzed reactions: Part 7. J Phys Chem Ref Data 36:1347–1397. 29. Schätzle S, Höhne M, Robins K, Bornscheuer U. 2010. Conductometric method for the rapid characterization of the substrate specificity of amine-transaminases. Anal Chem 82:2082–2086. 30. Wang T, Bishop S, Himoe A. 1972. Detection of carbamate as a product of the carbamate kinase-catalyzed reaction by stopped flow spectrophotometry. J Biol Chem 247:4437–4441. 31. Höhne M, Kühl S, Robins K, Bornscheuer UT. 2008. Efficient asymmetric synthesis of chiral amines by combining transaminase and pyruvate decarboxylase. ChemBioChem 9:363–365. 32. Goldberg R. 2014. Standards in biothermodynamics. Perspect Sci 1:7–14. 33. Koszelewski D, Tauber K, Faber K, Kroutil W. 2010. ω-Transaminases for the synthesis of non-racemic α-chiral primary amines. Trends Biotechnol 28:324–332. 34. Goldberg R, Tewari Y, Bell D, Fazio K. 1993. Thermodynamics of enzyme-catalyzed reactions: Part 1. Oxidoreductases. J Phys Chem Ref Data 22:515–582. 35. Kragl U, Vasic-Racki D, Wandrey C. 1996. Continuous production of L-tert-leucine in series of two enzyme membrane reactors. Bioprocess Eng 14:291–297. 36. Yun H, Yang Y, Cho B, Hwang B, Kim B. 2003. Simultaneous synthesis of enantiomerically pure (R)-1-phenylethanol and (R)-alpha-methylbenzylamine from racemic alpha-methylbenzylamine using omega-transaminase/alcohol dehydrogenase/glucose dehydrogenase coupling reaction. Biotechnol Lett 25:809–814. 37. Findrik Z, Vasic-Racki D. 2009. Overview on reactions with multi-enzyme systems. Chem Biochem Eng Q 23:545–553. 5 38. Findrik Z, Šimunović I, Vasić-Rački D. 2008. Coenzyme regeneration catalyzed by NADH oxidase from Lactobacillus brevis in the reaction of L-amino acid oxidation. Biochem Eng J 39:319–327.

130 6Summary and perspectives

133 134 SUMMARY

Aminotransferases, or transaminases, are enzymes that catalyze the reversible transfer of an amino group from an amine donor to a ketone or aldehyde acceptor. These enzymes play an important role in the natural metabolism of amino acids and amines, but also have many realized and potential uses in applied biocatalysis. The asymmetric conversion of a ketone to a chiral amine is of particular interest, as the products appear as components of many bioactive compounds. One clearly successful example is the production of sitagliptin through a combined chemocatalytic and biocatalytic pathway, including a transaminase-mediated step that introduces an amine functionality and creates a chiral center (1). The substitution of chemical amination reactions by enzymatic transamination in multistep synthetic pathways is also attractive since it may give a more pure product, lower the amount of waste that is formed, reduce energy consumption, and simplify the whole production processes (2). Although some known natural transaminases are outstanding biocatalysts, several challenges remain open to make transaminases more widely applicable for efficient industrial processes. The enzyme stability required for high reaction temperatures and harsh conditions such as intensive stirring may be insufficient. In other cases, a broader substrate scope may be needed, and strategies to overcome equilibrium problems are required to transform transaminases investigated in the laboratory to widely used industrial biocatalysts. The work described in this thesis is aimed at exploring the properties of known and new transaminases and establishing the possibilities and limitations of their use in biocatalysis. Issues that are examined are enzyme stability, effect of coupled reactions on reaction equilibrium, and structural and catalytic properties of a novel class III transaminase. In Chapters 2 and 3 we describe the discovery of a novel ω-transaminase termed PjTA in a strain of the Gram-negative bacterium Pseudomonas jessenii. This strain was isolated on basis of its capability to use caprolactam as a growth substrate. The PjTA enzyme belongs to the fold-type I group of PLP enzymes, in particular to the class III transaminases. The enzyme catalyzes the deamination of 6-aminohexanoic acid to produce 6-oxohexanoic acid, and was identified by proteomics profiling of genes induced by growth on caprolactam, employing the partial genome sequence to establish the putative identification and function of such proteins. Using genome sequence information, gene clusters involved in caprolactam degradation in P. jessenii were identified. BLAST searches showed the presence of genes with high similarity to these P. jessenii caprolactam degradation genes in a strain of Pseudomonas mosselii that was isolated as a caprolactam degrader from nylon industry waste water (3). This suggests that the same caprolactam catabolic pathway is present in both strains. Additionally, searches against the non-redundant protein database revealed the presence of sequences with high similarity to PjTA in other Pseudomonas strains, indicating indicating that the ability to hydrolyze lactams or cyclic peptides may not be unusual in Pseudomonas.

135 CHAPTER 6

During this study on bacterial caprolactam degradation by Ps. jessenii, we found that an ATP-dependent lactamase is involved in the conversion of caprolactam to 6-aminohexanoic acid (Chapter 2). This product can then be deaminated by the PjTA transaminase. The sequence analysis indicated that the ATP-dependent caprolactamase belongs to the ATP-dependent carboxylases/lactamase superfamily (4), and that it is further is similar to proteins annotated as 5-oxoprolinase or as hydantoinase. Other genes presumed to act in the caprolactam catabolic pathway were also discovered, with functions downstream of 6-aminohexanoic acid deamination. Proteomic studies, sequence comparison and (in the case of the lactamase and the transaminase) functional expression were used to identify the enzymes. The properties of the PjTA transaminase are further explored in Chapter 3, using enzyme that was recombinantly expressed in E. coli. Structural studies and sequence alignment indicate that the novel ω-transaminase indeed belonged to subgroup AT-II, class III aminotransferases of the fold type I superfamily of PLP enzymes. Furthermore, comparison of the crystal structures of PjTA to the well-studied ω-transaminases of 6 Chromobacterium. violeaceum (CvTA) and Vibrio fluvialis( VfTA) and the recently elucidated structure of Ochrobactrum anthropi (OaTA) showed that the overall structures and active sites are very well conserved. Activity studies with the caprolactam degradation pathway intermediates 6-aminohexanoic acid (6-ACA) and 6-oxohexanoate (6-OHA) showed that PjTA is a better biocatalyst for these compounds when compared to the homologous ω-transaminases

of CvTA and VfTA. Kinetic studies showed that specificity constants (kcat/KM) with 6-ACA and 6-OHA were 2-20 fold and 25 better for the PjTA enzyme, respectively. This is an indication that the PjTA enzyme may have evolved further for efficient deamination of the 6-aminohexanoic acid intermediate. Comparing the structures of the three enzymes does not indicate large or global differences that immediate make clear why PjTA shows better activity for 6-ACA. An interesting and potentially important difference is visible in the tunnel like active site. Here the 6-ACA carboxylate group of the external aldimine intermediate makes a salt bridge with a conserved arginine residue, Arg417. This arginine is known to undergo conformational changes in homologous enzymes, which allow it to interact either hydrophobically with alkyl or aromatic groups of amine donors or via electrostatic interactions with the carboxylate of an acceptor such as pyruvate. The interaction between the arginine and the 6-aminohexanoate carboxylate requires a more outward position of the arginine iminium than it can easily adopt in CvTA and VfTA because a bulky Phe needs to move away in the latter two enzymes. In PjTA the Phe is replaced by a Ser, facilitating the repositioning of the carboxylate binding arginine. Kinetic assays revealed that at high concentrations 6-OHA may be inhibitory for the PjTA transaminase. Such substrate inhibition is suspected to occur due to binding of the aldehyde acceptor to the PLP form of the enzyme in competition with the amino donor. Inhibition by amino donor is also conceivable, but in this case by binding of the

136 SUMMARY AND PERSPECTIVES substrate to the already aminated (PMP-containing) form of the enzyme. Whereas it may be problematic for cell-free applications of a transaminase in biocatalysis, we expect that when incorporated in an in vivo pathway, the enzyme would work at low substrate concentrations, where expression levels, stability, and selectivity will be the main factors that determine performance. The substrate scope study included in Chapter 3 also shows that PjTA has a preference towards aromatic substrates, as was reported earlier for CvTA and VfTA (5). When linear substrates were tested, PjTA revealed higher catalytic efficiencies towards 4-aminobutanoic acid than towards the linear substrate 1-aminopentane. The cause of the improved activity might be the recognition of the α-carboxylate of 4-aminobutanoic acid by the aforementioned flexible Arg417 in the binding site of the PjTA (6). Differently, CvTA and VfTA displayed the best activity with 1-aminopentane. This is probably related to the different molecular environment around Arg417 in these transaminases. Future protein engineering studies aimed at controlling PjTA activity may include replacing residues surrounding this arginine. Another protein engineering target is the stability of the enzyme. We observed rapid loss of activity under various conditions, such as 6 storage at -20˚C in 50 mM potassium phosphate, pH 8, containing 10% glycerol and during storage in the same buffer at 4˚C. Improving the stability of the PjTA enzyme was investigated in the work described in Chapter 4. We especially wanted to explore the use of computational design and in silico screening to search for a thermostability-enhanced version of PjTA without extensive laboratory screening. To this end, the FRESCO protocol was used, which should reduce the amount of laboratory resources and time needed to find thermostable variants. Additionally, high-temperature molecular dynamics (MD) simulations were examined as a tool to identify relatively flexible surface regions in PjTA. Such regions might be involved in early unfolding and thereby trigger exposure of hydrophobic patches that lead to aggregation and irreversible enzyme inactivation. Since MD was expected to discover only surface flexibility, buried residues and interface residues were omitted from the analysis. Following this approach, a library of 96 single surface mutants was designed and constructed by oligonucleotide-assisted mutagenesis. Mutations comprised different classes of flexibility. Favored, high-priority mutations were those located at positions that were on bases of the MD results expected with highest probability to be stabilizing. Non- favored mutations were those not located in regions predicted to have high flexibility by high temperature MD. From the 96 variants that were selected for construction and expression, 64 were produced and obtained in soluble form. This included 51 mutants distributed over 29 positions in favored areas, and 13 mutations at 9 positions in non- favored areas. Stabilities were measured with a thermal shift fluorescence assay, and the results showed that stability was moderately improved in only a few variants. Most mutations were neutral or detrimental and only five mutants showed a thermostability

137 CHAPTER 6

increase of more than 1˚C in TM,app. The five improved mutants were all located in the regions displaying relatively high flexibility. The success rate of 11% (5/46, 46 of the 51 mutations were in high priority areas designated by the FRESCO protocol, 5 were from alternative (stricter) energy criteria) is lower than what was reported previously for FRESCO by Wijma et al. 2014 (7). Four of the five stabilized mutants showed modest reduction of the catalytic activity, which is an inverse relationship that has been more often observed between stability and function (8, 9). By inspecting the structure, possible explanations for this reduced activity were found. For example, the stabilizing mutation at position M419L is located close to the tunnel-like active site of the enzyme and this may influence substrate entry or binding, causing some reduction of enzyme activity. One mutation, A393R, displayed a 30% increase in catalytic activity, for which we have no good explanation. The complexity of the catalytic cycle, with two half reactions each encompassing several chemicals steps, makes it difficult to correlate effects on rates with the nature of a mutation. Twelve non-stabilizing mutations were discovered in high priority locations and four 6 of them appeared significantly destabilizing, which might be due to the introduction of hydrophobic groups on the protein surface. This type of substitutions is more often predicted by FRESCO, mostly due to Rosetta energy calculations, and can be easily omitted from the laboratory testing step. The results showed that the computational single-mutation strategy together with high temperature MD simulations have the potential to identify regions where stabilizing mutations should be introduced, although the results with PjTA are not spectacular. Recent results in our laboratory (10) and observations with a tetrameric halohydrin dehalogenase (11) indicate that mutations that stabilize the subunit interface may also be computationally designed by the FRESCO strategy. Work with an aminotransferase obtained from a metagenomic library (12) indicated that mutations improving cofactor binding may have a large positive effect on stability. The benefits of using high temperature molecular dynamics simulations to identify priority regions for introducing stabilizing mutations may be more pronounced in case of monomeric enzymes. Finally, in Chapter 5 we describe a three-enzyme biocatalytic network for the conversion of the ether alcohols butyldiglycol (a primary ether alcohol) and 1-butoxy-2-propanol (a secondary ether alcohol) to the corresponding amines. This enzymatic network for alcohol to amine conversion was built by combining an alcohol dehydrogenase from Geobacillus stearothermophilus, the transaminase from C. violaceum also used in Chapter 3 (CvTA), and an alanine dehydrogenase from Vibrio proteolyticus. The three enzymes were overexpressed in E. coli and used in purified form. Three interconnected reactions, i.e. alcohol oxidation, L-alanine-driven carbonyl transamination, and reductive pyruvate amination with ammonia, were carried out in a one-pot system, allowing production of the desired amine and simultaneous recycling of the alcohol dehydrogenase cofactor NAD+ and the amine donor L-alanine. Thus, the

138 SUMMARY AND PERSPECTIVES net reaction is alcohol plus ammonia gives organic amine plus water, which indeed is a highly attractive overall conversion because there is no use of reducing cofactors or an organic amine donor. Various concentrations of alcohol, ammonium, and alanine were tested to improve the yield of amine, which reached 40%. The optimization tests showed that none of the substrates could be added at high initial concentrations due to their inhibitory effect (alanine and the alcohol substrate) or a negative effect on the stability of the enzymes (ammonium). The thermodynamic equilibrium of the three-enzyme amination network was another main factor determining the maximum degree of conversion, in accordance with previous studies (13). Therefore, equilibrium constants, according to Goldberg (14) notation, were calculated from experimental data. The results showed that for the first reaction, from alcohol to ketone or aldehyde, the equilibrium is in the unwanted direction of the alcohol. Similarly, the equilibrium constant of the transamination reaction is unfavorable for production of the amine, with the equilibrium strongly lying on the side of the substrates ketone/aldehyde and L-alanine. On the other hand, the alanine dehydrogenase-catalyzed recycling reaction, which recycles the amino donor 6 alanine and the electron acceptor NAD+, displays a favorable equilibrium constant. Thus, the latter reaction appears to drive the enzymatic network to the amine production, and it will do so better if the ammonium concentration is higher. Subsequently, we theoretically examined the overall reaction equilibrium as a function of substrate concentrations. Results showed that in order to achieve a good conversion (>90%), a high concentration (≥ 0.7M) of the amino donor ammonium should be used. Therefore, a range of ammonia concentrations (80 mM to 1M) was tested. As a result, conversion was increased from 40% to 60% when a total concentration of 280 mM of ammonium was used. For this, a step-wise addition of ammonia was required, as the enzymes precipitated or aggregated when a high concentration of ammonium was added in one step. The results again suggested that enhancing enzyme stability, now in the presence of high ammonia and salt, should be an important future goal.

PERSPECTIVES

Transaminases hold powerful characteristics for use as as catalysts, including a broad substrate scope and high product enantioselectivity in asymmetric conversions. Nevertheless, limitations due to unfavorable equilibrium, low thermal- and process stability, and narrow substrate scope should be solved to enable wider application in sustainable production of amines. Besides discovery of new natural transaminase variants, which will allow a broader range of conversions, some specific engineering aims or strategies emerge from the work reported here. In Chapter 4, we attempted to increase the thermostability of the PjTA transaminase

139 CHAPTER 6

through the FRESCO computational strategy, especially with the aim to examine if MD simulations can steer the choice of target regions. However, targeting mutations to the protein surface, where MD suggested priority regions, yielded only moderate improvements. For obtaining robust transaminase variants, it is advisable to shift attention from mutating surface residues to improving subunit interface interactions. Mutating residues on the subunit interface of the dimeric aminotransferases might strengthen the interactions between the monomers, increasing the thermostability of the enzyme if denaturation commences by dimer dissociation. Hayashi et al. (15) showed that a dimeric D-amino acid transaminase reached higher thermostability and catalytic efficiency when a tryptophan located at the interface of the subunits was substituted by a phenylalanine. Preliminary experiments in our lab indicate that computational design of mutations at the PjTA subunit interface indeed is very effective (10). As mentioned above, an option suggested by the work of Börner et al. (16) is to improve cofactor binding, which probably can also be achieved by computational methods. In Chapter 5 we confirmed that both stability and equilibrium of an amination 6 reaction are issues to overcome when designing a transaminase catalyzed process based on a multi-enzyme network. Although not tested in this thesis, one of the most studied strategies to improve the stability of enzymes under process conditions is immobilization. This strategy is widely used because immobilization can lead to markedly improved operational performance of biocatalysts. For instance, Koszelewski et al. (17) showed that the apparent optimum temperature of transaminase TA-117 increased from 30˚C to 40- 50˚C when the enzyme was immobilized in sol-gel/celite. Immobilization also allowed the re-use of the biocatalyst through different cycles, even when used at elevated temperatures. Neto et al. (18) demonstrated that an ω-transaminase immobilized on solid carriers allowed the reuse of the enzyme for 8 cycles of 24 h, retaining more than 50% of the original activity. This strategy might be beneficial to increase the stability of the enzymes and allow the re-usability of complete multi-enzymatic reactions. Another way to increase the stability of transaminases is the usage of whole cells, which also was not examined in this thesis. Whole cell biocatalysis is a promising strategy because stability of the enzymes is improved and addition of cofactors is unnecessary, making network reactions as used in Chapter 5 more economical. Klatte et al. (19, 20) showed a redox self-sufficient amination of alcohols through a network reaction similar to that studied here in Chapter 5, using plasmid-born overproduction in E. coli of the three enzymes: transaminase, alcohol dehydrogenase, and alanine dehydrogenase. One major challenge to overcome when designing reactions with ω-transaminases is the unfavorable thermodynamic equilibrium of the reaction (21), as described in Chapter 5. A widely used strategy is to shift the equilibrium by the addition of an excess of one of the substrates. Truppo et al. (22) showed that using a large excess of the amino donor isopropylamine with acetophenone as amino acceptor resulted in 95% conversion. Although this strategy might seem simple to implement, an important consideration

140 SUMMARY AND PERSPECTIVES is that enzyme activity may be lowered when a large access of substrate is added due to substrate inhibition or enzyme unfolding. The latter may affect all enzymes used in a multi-enzymatic system, and even salting-out effects may occur when using high substrate concentrations. The choice of amine donor will also influence the position of the thermodynamic equilibrium. Finally, the removal of a product or co-product is another uncomplicated method to shift the equilibrium of transaminase mediated reactions. This can be accomplished through, for example, the continuous physical separation of the product from the reaction mixture, such as through volatilization of acetone when isopropylamine is used as amino donor (23), or the design of cascade reactions (24), such as the recycling of the amino acceptor pyruvate back to alanine (see Chapter 5), its conversion to lactate by a dehydrogenase, or its enzymatic decarboxylation.

6

141 CHAPTER 6

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142 7Samenvatting en perspectief

145 146 SAMENVATTING EN PERSPECTIEF

SAMENVATTING

Aminotransferases, oftewel transaminases, zijn enzymen die de reversibele overdracht van aminogroepen van een amine donor naar een keton- of aldehyde acceptor katalyseren. Deze enzymen vervullen een belangrijke rol in het natuurlijke metabolisme van aminozuren en amines, maar ze hebben ook vele reeds bekende en potentiële toepassingen in het veld van biokatalyse. De asymmetrische conversie van een keton naar een chiraal amine is van bijzonder belang, omdat de chirale amines vaak voorkomen als bouwsteen in bioactieve stoffen. Een bijzonder voorbeeld is bloedglucose regulerende geneesmiddel sitagliptine, dat gesynthetiseerd wordt door middel van een combinatie van chemokatalytische en biokatalytische reactiestappen, waaronder een transaminase gemedieerde stap die een amine functionaliteit introduceert en daarbij een chiraal centrum creëert (1). Het vervangen van chemische amineringsreacties door enzymatische transaminering in meerstaps synthetische routes is interessant omdat het vaak de productopbrengst verbetert, de hoeveelheid afval vermindert, het energieverbruik reduceert en het hele productieproces vereenvoudigt (2). Ondanks dat sommige natuurlijke transaminases bijzonder goed werken, is het een uitdaging transaminases breder toepasbaar te maken voor industriële processen. De enzymstabiliteit die nodig is voor hoge reactietemperaturen en zware 7 omstandigheden, zoals intensief roeren, kan onvoldoende zijn. In andere gevallen is een breder substraatbereik nodig, en proces-strategieën die evenwichts-problemen verhelpen kunnen nodig zijn om transaminases die in het laboratorium ontwikkeld zijn in de industrie toe te passen. Deze thesis beschrijft het verkennen van eigenschappen van bekende en nieuwe transaminases en het vaststellen van de mogelijkheden en beperkingen van hun gebruik in de biokatalyse. Kwesties die onderzocht worden zijn: enzymstabiliteit, het effect van gekoppelde enzymreacties op het netto reactie- evenwicht, en de structurele en katalytische eigenschappen van een nieuw klasse III transaminase. In hoofdstuk 2 en 3 beschrijven we de ontdekking van een nieuw ω-transaminase genaamd PjTA in een stam van de gram-negatieve bacterie Pseudomonas jessenii. Deze stam is geïsoleerd op basis van zijn mogelijkheid om caprolactam als groeisubstraat te gebruiken. Het PjTA enzym behoort tot de groep van type I PLP enzymen, in het bijzonder tot de klasse III transaminases. Het enzym katalyseert de deaminering van 6-aminohexaanzuur tot 6-oxohexaanzuur, en is geïdentificeerd door proteoom- profilering van genen die geïnduceerd worden tijdens groei van de bacterie met caprolactam als groeisubstraat, waarbij de genoom-sequentie van de bacterie is gebruikt om het complete gen van het nieuwe transaminase te identificeren. De genoom-sequentie is tevens gebruikt voor het opsporen van genclusters waarin andere genen zijn gelegen die betrokken zijn bij de afbraak van caprolactam in P. jessenii. Vervolgens toonde het doorzoeken van databases met genoomsequenties aan

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dat een Pseudomonas mosselii stam die ook caprolactam kan afbreken beschikt over genen die sterk verwant zijn aan de caprolactam-afbraak genclusters die wij vonden in P. jessenii (3). Dit wijst erop dat dezelfde afbraakroute voor caprolactam aanwezig is in beide stammen. Tevens bleek uit het doorzoeken van databases met eiwitsequenties dat enzymen die sterk lijken op PjTA aanwezig zijn in diverse andere Pseudomonas stammen’ Het vermogen lactamen of cyclische peptiden te metaboliseren lijkt niet ongewoon te zijn bij Pseudomonas bacteriën. Gedurende de studie van bacteriële caprolactam afbraak door P. jessenii hebben we ontdekt dat een ATP-afhankelijk lactamase betrokken is bij de eerste reactiestap: omzetting van caprolactam naar 6-aminohexaanzuur (hoofdstuk 2). Dit product kan vervolgens worden gedeamineerd door de genoemde transaminase. De sequentie- analyse liet zien dat het ATP-afhankelijke caprolactamase behoort tot de ATP- afhankelijke carboxylases/lactamase superfamilie (4), en dat dit enzym verder lijkt op eiwitten die zijn geannoteerd als 5-oxoprolinase of hydantoinase. Andere genen die worden verondersteld een rol te spelen bij de afbraakroute voor caprolactam werden ook ontdekt, met functies bij stappen die volgen op de deaminering van 6-aminohexaanzuur. Proteoom-studies, sequentie vergelijking en (in het geval van de lactamase en transaminase) en functionele expressie werden gebruikt om de enzymen 7 te identificeren. De eigenschappen van het PjTA transaminase zijn verder onderzocht in hoofdstuk 3, door gebruik te maken van enzymen die recombinant tot expressie worden gebracht in E. coli. Structuur-studies en sequentie-vergelijking wijzen erop dat het nieuwe ω-transaminase inderdaad behoort tot de subgroep AT-II, klasse III aminotransferases van de “fold-type I” superfamilie van PLP enzymen. Verder liet vergelijking van de kristalstructuren van PjTA met de goed bestudeerde ω-transaminases van Chromobacterium violeaceum (CvTA) en Vibrio fluvialis (VfTA) en de recent gevonden structuur uit Ochrobactrum anthropi (OaTA) zien dat de algehele structuur en actieve gebieden goed geconserveerd zijn. Studies naar de activiteit van PjTA met als substraten de tussenproducten van caprolactam-afbraak 6-aminohexaanzuur (6-ACA) en 6-oxohexaanzuur (6-OHA), lieten zien dat PjTA een betere biokatalysator is voor deze stoffen in vergelijking tot de homologe ω-transaminases CvTA en VfTA. Kinetische studies toonden aan dat de

specificiteitsconstante (kcat/KM) voor 6-ACA en 6-OHA respectievelijk 2-20 keer en 25 keer beter waren voor het PjTA enzym. Dit wijst erop dat het PjTA enzym verder heeft kunnen evolueren voor efficiënte deaminering van het 6-aminohexaanzuur tussenproduct. Vergelijking van de structuren van de drie enzymen laat geen grote of globale verschillen zien die duidelijk maken waarom PjTA een betere activiteit heeft voor 6-ACA. Echter, een potentieel belangrijk verschil is zichtbaar in de tunnelachtige actieve plek dicht bij het reactieve centrum van het enzym. Hier maakt de 6-ACA carboxylaat groep van het externe aldimine tussenproduct een zoutbrug met een geconserveerd arginine

148 SAMENVATTING EN PERSPECTIEF residu, Arg417. Het is bekend dat arginine conformationele veranderingen ondergaat in homologe enzymen, waardoor zowel een hydrofobe interactie kan aangaan met alkyl- of aromatische groepen van amine donoren alsook een elektrostatische interactie met een carboxyl groep van een acceptor zoals pyruvaat. In het geval van PjTA komt daar nog een andere interactie bij: de arginine 417 vormt een zoutbrug met de carboxyl groep van 6-ACA, hetgeen een meer naar buiten gerichte positie van de arginine iminium vereist dan mogelijk is in CvTA en VfTA, omdat bij de twee laatstgenoemde enzymen een grote Phe in de weg zit. In PjTA is deze Phe vervangen door de veel kleinere Ser, hetgeen de herpositionering van de arginine en daarmee een interactie met de carboxyl groep van 6-ACA mogelijk maakt. Kinetische experimenten lieten zien dat een hoge concentratie van 6-OHA een remmend effect zou kunnen hebben op de PjTA transaminase. Men vermoedt dat een dergelijke substraat-remming bij transaminases wordt veroorzaakt door de binding van de aldehyde acceptor aan de PLP vorm van het enzym, concurrerend met de amine donor. Remming door de amine donor is ook mogelijk, in dat geval door binding van het substraat aan de reeds geamineerde (PMP bevattende) vorm van het enzym. Ondanks dat het problematisch zou kunnen zijn voor toepassingen van transaminases in bij biokatalytische processen, verwachten we dat het enzym wanneer het is geïncorporeerd in een in vivo reactiepad bij lage concentraties werkt. Dan zijn 7 expressie-niveaus, stabiliteit en selectiviteit de belangrijkste factoren die de prestaties bepalen. De studies aan het substraatbereik in hoofdstuk 3 laten ook zien dat PjTA een voorkeur heeft voor aromatische substraten, zoals eerder gevonden voor CvTA en VfTA (5). Toen lineaire substraten werden getest, liet PjTA een hogere katalytische efficiëntie zien met 4-aminobutaanzuur dan met het lineaire substraat 1-aminopentaan. De oorzaak van deze verbeterde activiteit zou kunnen zijn dat de flexibele Arg417 bij het aktieve centrum van PjTA de carboxyl groep van 4-aminobutaanzuur herkent (6). Daarentegen vertoonden CvTA en VfTA de beste activiteit met 1-aminopentaan. Dit is mogelijk gerelateerd aan verschillen in de moleculaire omgeving rond Arg417 in deze transaminases. Toekomstige studies die gericht zijn op het veranderen van de PjTA selectiviteit zouden kunnen kijken naar het vervangen van residuen rondom deze arginine. Een andere eiwit “engineering target” is de stabiliteit van het enzym. We hebben waargenomen dat het enzym vrij snel aktiviteit verliest onder verschillende condities, zoals opslag bij -20˚C of bij 4˚C in 50 mM kaliumfosfaat, pH 8, met 10% glycerol. Het verbeteren van de stabiliteit van het PjTA enzym is onderzocht in hoofdstuk 4. We wilden gebruik maken van de zgn. FRESCO strategie, d.w.z. computergestuurd ontwerp en in silico screening om op zoek te gaan naar een versie van PjTA met verbeterde themostabiliteit zonder arbeidsintensieve screening in een laboratorium. Daarbij werden moleculaire dynamica (MD) simulaties onderzocht als instrument om de relatief flexibele oppervlakte gebieden in PjTA te vinden. Deze gebieden zouden

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betrokken kunnen zijn bij vroege ontvouwing van het enzym, waardoor hydrofobe gebieden bloot komen te liggen, hetgeen leidt tot aggregatie en onomkeerbare inactivatie van het enzym. Omdat MD alleen naar oppervlakte flexibiliteit kijkt, werden diepgelegen residuen en interface residuen die betrokken zijn bij interacties tussen de subeenheden van het enzym niet meegenomen in deze analyse. Door middel van deze aanpak is een verzameling van 96 verschillende PjTA mutanten ontworpen, elk met een enkele oppervlak-mutatie. Posities in delen van het eiwit waar op grond van MD-resultaten mutaties waarschijnlijk een stabiliserend effect kunnen hebben, zijn gekwalificeerd als hoge prioriteit posities; posities in gebieden die geen hoge flexibiliteit vertonen bij hoge temperatuur MD simulaties werden lage prioriteit posities genoemd. Van de 96 ontworpen mutanten werden er 64 geproduceerd en verkregen als gemuteerd PjTA enzym in oplosbare vorm. Hieronder waren 51 mutanten met aanpassingen op 29 hoge prioriteit posities, en 13 mutanten met aanpassingen op lage prioriteit posities. De stabiliteit van de mutanten is bepaald door met behulp van fluorescentie-metingen de ontvouwing van de enzymen te volgen bij oplopende temperatuur. De resultaten lieten zien dat de stabiliteit matig was verbeterd bij slechts een klein aantal varianten. De meeste mutaties waren neutraal of nadelig, maar vijf

mutanten lieten een verbetering van thermostabiliteit zien van meer dan 1˚C in TM,app. 7 Deze vijf mutanten hadden allen een mutatie in gebieden met relatief hoge flexibiliteit bij de MD-simulaties en de betreffende posities waren dus terecht gekozen als posities met hoge prioriteit. De positieve opbrengst van 11% (5/46, 46 van de 51 mutaties waren op posities met hoge prioriteit volgens het FRESCO-protocol, 5 waren van alternatieve striktere energiecriteria) is lager dan eerder gerapporteerd door Wijma et al. 2014 (7). Vier van de vijf gestabiliseerde mutanten lieten een gereduceerde katalytische activiteit zien; deze inverse relatie is eerder waargenomen tussen stabiliteit en functie (8, 9). Door te kijken naar de structuur werden mogelijke verklaringen gevonden voor de gereduceerde activiteit. De stabiliserende M419L mutatie bijvoorbeeld bevindt zich dichtbij het tunnelvormige actieve centrum van het enzym en dit kan invloed hebben op substraat-toegang en -binding, resulterend in reductie van enzymactiviteit. Eén mutant, A393R, liet een stijging van 30% zijn in katalytische activiteit zien, waarvoor geen duidelijke verklaring is. De complexiteit van de katalytische cyclus, met twee halfreacties, elk met meerdere chemische stappen, maakt het moeilijk om effecten op de reactiesnelheid te correleren met de aard van de mutatie. Twaalf niet-stabiliserende mutaties werden ontdekt in locaties met hoge prioriteit en vier van deze leken aanzienlijk destabiliserend, hetgeen kan worden verklaard door het introduceren van hydrofobe groepen aan het eiwitoppervlak. Dit soort substituties worden vaker voorspeld door FRESCO, voornamelijk door de onderliggende Rosetta energie-berekeningen, en kunnen eenvoudig worden weglaten bij het testen in het laboratorium. De resultaten lieten zien dat een mutatie-strategie waarbij veranderingen worden

150 SAMENVATTING EN PERSPECTIEF aangebracht op posities die met hoge-temperatuur MD simulaties worden geïdentificeerd als gunstig of kansrijk, duidelijk potentieel heeft om gebieden te identificeren waar stabiliserende mutaties moeten worden toegepast. Echter, de resultaten met PjTA zijn niet spectaculair. Recente resultaten uit ons laboratorium (10) en observaties met een tetrameer halohydrin dehalogenase (11) wijzen erop dat mutaties die de interacties tussen de subeenheden van het enzym stabiliseren ook met de computer kunnen worden ontworpen. Een studie met een aminotransferase uit een metagenoom- bibliotheek (12) toonde aan dat ook mutaties die cofactor-binding verbeteren een groot positief effect kunnen hebben op de stabiliteit. De voordelen van het gebruik van hoge temperatuur moleculaire dynamica simulaties om prioriteitsgebieden te vinden voor stabiliserende mutaties zouden veel duidelijker kunnen zijn bij monomere enzymen. Ten slotte beschrijven we in hoofdstuk 5 een biokatalytisch netwerk met drie enzymen voor de conversie van de ether alcoholen butyldiglycol (een primair ether alcohol) en 1-butoxy-2-propanol (een secundair ether alcohol) naar de corresponderende amines. Dit enzym-netwerk voor conversie van alcoholen naar amines is samengesteld uit een alcohol dehydrogenase van Geobacillus stearothermophilus, het transaminase van C. violaceum dat ook gebruikt is in hoofdstuk 3 (CvTA), en een alanine dehydrogenase afkomstig van Vibrio proteolyticus. De drie enzymen werden in E. coli tot overexpressie gebracht en gezuiverd. Drie met elkaar verbonden reacties, namelijk alcohol oxidatie, 7 L-alanine-gedreven carbonyl aminering en reductieve pyruvaat animering met ammonia, zijn uitgevoerd in een één-pot-systeem, waardoor productie van de gewenste amine en tegelijkertijd recycling van de alcohol dehydrogenase cofactor NAD+ en de amine donor L-alanine plaatsvindt. De netto reactie is dus: alcohol en ammonia geven organische amine en water, wat in zijn geheel een zeer aantrekkelijke conversie is, omdat er geen gebruikt wordt gemaakt van reducerende cofactoren of een organische amine donor. Verschillende concentraties van alcohol, ammonium en alanine werden getest om de opbrengst van amine te verbeteren tot 40%. De optimalisatie liet zien dat geen van de substraten kon worden toegevoegd in hoge initiële concentraties vanwege een remmend effect (alanine en het alcohol substraat) of een negatief effect op de stabiliteit van de enzymen (ammonium). Het thermodynamisch evenwicht van het aminering netwerk met drie enzymen was een andere belangrijke factor die de maximale mate van conversie bepaalde, in overeenstemming met eerdere studies (13). Derhalve werden evenwichtscontanten berekend met de experimentele data volgens de Goldberg notatie (14). De resultaten lieten zien dat voor de eerste reactie, van alcohol naar keton of aldehyde, het evenwicht in de ongewenste richting van de alcohol is. Ook de evenwichtsconstante van de transaminering-reactie is ongunstig voor de productie van amine, met het evenwicht sterk aan de zijde van de substraten keton (of aldehyde) en L-alanine. Aan de andere kant laat de alanine dehydrogenase-gekatalyseerde recycling reactie, die de amine donor alanine en de elektron acceptor NAD+ regenereert, een gunstige evenwichtsconstante

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zien. Deze laatste reactie stuwt dus het enzymatische netwerk tot de productie van amine, en zal dat beter doen bij hogere concentraties ammonium. Vervolgens hebben we theoretisch naar het algehele reactie-evenwicht gekeken als functie van substraatconcentraties. De resultaten lieten zien dat een hoge concentratie (≥ 0.7 M) van de amine donor ammonium benodigd is om een goede conversie (>90%) te bereiken. Daarom werd een reeks verschillende ammonia concentraties (80 mM tot 1 M) getest in het laboratorium. Wanneer een totale concentratie van 280 mM ammonium werd gebruikt, verbeterde de conversie van 40% naar 60%. Hiervoor was een stapsgewijze toevoeging van ammonium nodig, omdat de enzymen precipiteerden of aggregeerden wanneer een hoge concentratie ammonium in één keer werd toegevoegd. De resultaten wezen er opnieuw op dat verbeteren van de enzymactiviteit en stabiliteit, nu in de aanwezigheid van hoge concentraties ammonium en zout, een belangrijk toekomstig doel is.

PERSPECTIEF

Transaminases hebben goede eigenschappen voor gebruik als katalysator, zoals 7 acceptatie van een breed scala aan substraten en een hoge product enantioselectiviteit bij asymmetrische conversies. Niettemin moeten beperkingen door een ongunstig evenwicht, lage thermische en proces-stabiliteit en lage activiteit met sommige substraten worden opgelost om een bredere toepassing in duurzame productie van amines mogelijk te maken. Naast ontdekking van nieuwe natuurlijke transaminase varianten, die een breder bereik aan conversies mogelijk maakt, komen enkele specifieke doelstellingen en strategieën voort uit het hier beschreven werk. In hoofdstuk 4 hebben we geprobeerd de thermostabiliteit van de PjTA transaminase te verhogen met behulp van de computergestuurde FRESCO-strategie, vooral met het doel om te onderzoeken of MD simulaties kunnen helpen bij het bepalen van posities in het eiwit waar mutaties succesvol zijn. De gerichte mutaties aan het eiwitoppervlak, waar MD prioriteit gebieden aangaf, gaven echter matige verbeteringen. Om robuuste varianten van het transaminase te verkrijgen is het aan te raden de aandacht te verschuiven van het muteren van oppervlakte residuen naar het aanbrengen van mutaties die de interacties tussen de subeenheden van het enzym verbeteren. Dergelijke mutaties aan het raakvlak kunnen de interacties tussen de monomeren versterken, waardoor de thermostabiliteit van het enzym zal toenemen wanneer dissociatie van de subeenheden een rol speelt bij de inactivatie. Hayeshi et al. (15) hebben laten zien dat een dimeer D-aminozuur transaminase hogere stabiliteit en katalytische efficiëntie had wanneer een tryptofaan aan het raakvlak tussen twee subeenheden werd vervangen door een fenylalanine. Recente experimenten in ons laboratorium duiden erop dat computergestuurd ontwerp van mutaties op het raakvlak

152 SAMENVATTING EN PERSPECTIEF van de subeenheden van PjTA inderdaad erg effectief is (10). Zoals hierboven genoemd, suggereert het werk van Börner et al. (16) dat ook mutaties die de binding van de PLP cofactor verbeteren de stabiliteit kunnen verhogen. Ook dergelijke mutaties kunnen waarschijnlijk worden voorspeld met behulp van computerberekeningen. In hoofdstuk 5 hebben we vastgesteld dat zowel stabiliteit van de enzymen als het evenwicht van een amineringsreactie punten van aandacht zijn bij het ontwerpen van een transaminase-gekatalyseerd proces gebaseerd op een netwerk van meerdere enzymen. Alhoewel niet getest in deze thesis, is immobilisatie een van de meest bestudeerde strategieën om stabiliteit van enzymen te verbeteren onder procescondities. Deze strategie wordt breed toegepast omdat immobilisatie kan leiden tot aanzienlijke verbetering van operationele prestaties van biokatalyse. Koszelewski et al. (17) lieten bijvoorbeeld zien dat de optimale temperatuur van het transaminase TA- 117 toenam van 30˚C naar 40-50˚C wanneer het enzym geïmmobiliseerd is als colloïdale sol-gel. Immobilisatie biedt ook de mogelijkheid tot hergebruik van de biokatalysator in verschillende cycli, zelfs bij hogere temperaturen. Neto et al. (18) lieten zien dat een op vast substraat geïmmobiliseerde ω-transaminase tot 8 cycli van 24 uur kan worden hergebruikt, terwijl het 50% van de originele activiteit behoudt. Deze aanpak zou kunnen helpen om de stabiliteit van de enzymen te verbeteren en om complete multi- enzymatische netwerken te hergebruiken. 7 Een andere manier om de stabiliteit van transaminases te verbeteren is door gebruik te maken van complete cellen, iets wat in deze thesis ook niet is onderzocht. Het gebruik van hele cellen in de biokatalyse is een veelbelovende strategie, omdat stabiliteit van de enzymen wordt verbeterd en toevoegen van cofactoren onnodig is, met als gevolg dat netwerk reacties zoals omschreven in hoofdstuk 5 economisch aantrekkelijker worden. Klatte et al. (19, 20) hebben een aminering van alcoholen met behulp een netwerkreactie die lijkt op wat is omschreven in hoofdstuk 5 laten zien. Zij gebruikten E. coli cellen die drie enzymen overproduceerden: transaminase, alcohol dehydrogenase en alanine dehydrogenase. Een grote uitdaging bij het ontwerpen van een reactie met ω-transaminases is het ongunstige thermodynamisch evenwicht van de reactie (21), zoals omschreven in hoofdstuk 5. Een veel gebruikte strategie is om het evenwicht te verschuiven door een overmaat van een van de substraten te gebruiken. Truppo et al. (22) hebben laten zien dat een grote overmaat van de amine donor isopropylamine met acetofenon als amine acceptor resulteerde in een conversie van 95%. Hoewel het eenvoudig lijkt deze strategie te implementeren, is een belangrijk aspect dat de activiteit van het enzym verlaagd kan worden door substraat-inhibitie of zelfs ontvouwing van het enzym wanneer een grote hoeveelheid substraat wordt toegevoegd. Dit laatste effect kan alle enzymen in het multi-enzymatische netwerk beïnvloeden, en ook uitzout-effecten kunnen optreden bij hoge substraatconcentraties. De keuze van de amine donor zal ook invloed hebben op de positie van het thermodynamisch evenwicht.

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Ten slotte is de verwijdering van een product of co-product een andere methode om het evenwicht van transaminase-gemedieerde reacties te verschuiven. Dit kan worden bereikt door bijvoorbeeld het continue fysisch scheiden van de producten van het reactiemengsel, zoals door verdamping van aceton wanneer isopropylamine wordt gebruikt als amine donor (23); of door het ontwerpen van cascade reacties (24), zoals het hergebruik van de amine acceptor pyruvaat terug naar alanine (zie hoofdstuk 5), de conversie van pyruvaat naar lactaat door een dehydrogenase of de enzymatische decarboxylering van pyruvaat.

7

154 SAMENVATTING EN PERSPECTIEF

REFERENTIES

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155 Acknowledgements

157 158 ACKNOWLEDGEMENTS

I would like to thank Eurotango and those people that I never met, but offered me the priceless opportunity to do my PhD in Europe. I would like to express my gratitude to my supervisor. Dear Dick, thank you for accepting me into your research group, for supporting my PhD, for all the advice, and for investing many hours in reading and improving my manuscripts.

Thank you also, to two talented post-docs who helped me along those critical years of the PhD; Marcelo Masman and Marleen Otzen. Marleen and Marcelo, thank you for being so supportive, for giving critical advice, and supporting not only my research, but for supporting me in the many difficult moments of the PhD.

Thank you to all the amazing people that I met in the laboratory, and with who I shared lots of fun, parties, science and gossip: Hugo, Mathew, Willem, Thaito-chan, Ana Toplack, Hanna Dudek, Antonija, Jeroen, Maximiliam, Mohammahed, Danna, Hemant, Marzena, Alex Ferrari, Nikola, Sambicka, Elvira, Elisa, Cora, and Suzanne. A special thanks, from a deep place in my heart, to Patricia, Aline and Guille who helped me through the first years of living on this side of the world. It was fun to share adventures, parties, and the milestones of our lives together.

To all the people who shared the “happy office” with me: Roga, Ana, Arif, and Thai. I enjoyed working with you, thank you for your advice and for sharing your knowledge. Roga and Thai, you have a special place on my heart, thank you for your kindness and help. I sincerely wish you all the best and I hope to see you again soon.

Misun and Friso you have my sincere gratitude for helping me prepare the defense, for investing many hours on preparing the thesis, and for motivating me to have the party afterwards. You were witnesses to two of the most important moments of my life, and for me your support is irreplaceable.

Misun, you deserve a paragraph of your own. Miss Lee you are, with no doubt, one of the best friends that I will ever have in my life. I never thought that a girl coming from the exact other side of the world would end up being one of my best friends. Thank you for sharing your knowledge with me, for listening, for tolerating me, and for letting me join your important moments. I hope we can keep this friendship for many years.

159 A mis amigas en Argentina, Maga y Andre. Gracias, gracias y muchas gracias, por ser mis amigas en la distancia, por escucharme, por soportarme y por hacer una espacio en sus vidas para compartir conmigo cada vez que vuelvo a casa. Hablar con ustedes me llena el corazón de alegría porque sé que tengo dos amigas que valen más que el oro. Las quiero mucho y les deseo lo mejor para ustedes y su familia.

Hermano y papa, gracias por su amor y compañía durante todos estos años. Su cariño y apoyo me han ayudado a lo largo de mi vida y mi educación. Siempre los voy a querer.

Mamá y Joris. Mamá, te quiero con toda mi alma y mi corazón. Gracias, por ser mi mamá, por quererme, por tolerarme, y por darme tantos años de tu vida para cuidarme. Gracias por caminar conmigo a la facultad por muchos años bajo el sol y la lluvia, gracias por esperarme cada día, despertarme cada día, y alcanzarme los libros cuando los olvidaba. Mamá, gracias por compartir tu vida conmigo y por quererme tan desinteresadamente. Perdóname, por haberme ido tan lejos de vos y por vernos tan poco tiempo en los últimos años. Mamá, deseo que Dios te cuide mucho y siempre te de salud y felicidad.

Joris, mi amor eterno. Gracias, por compartir tu vida y tu sabiduría conmigo. Gracias por ayudarme sin esperar nada a cambio. Gracias por acompañarme y estar junto a mí durante todos estos años. Desde el fondo de mi corazón te agradezco por ayudarme a ver la luz en los días más oscuros y especialmente por quererme cada día.

A mis abuelas Laura y Alcira que se fueron hace mucho tiempo. Mis queridas abuelas gracias por todo el trabajo y el amor que siempre pusieron en sus familias y que hoy, algunas generaciones después, da frutos en mi vida. Gracias por cuidarnos, por querernos, y por darnos la vida.

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