Skip to main content

Two novel deep-sea sediment metagenome-derived esterases: residue 199 is the determinant of substrate specificity and preference

Abstract

Background

The deep-sea environment harbors a vast pool of novel enzymes. Owing to the limitations of cultivation, cultivation-independent has become an effective method for mining novel enzymes from the environment. Based on a deep-sea sediment metagenomics library, lipolytic-positive clones were obtained by activity-based screening methods.

Results

Two novel esterases, DMWf18-543 and DMWf18-558, were obtained from a deep-sea metagenomic library through activity-based screening and high-throughput sequencing methods. These esterases shared 80.7% amino acid identity with each other and were determined to be new members of bacterial lipolytic enzyme family IV. The two enzymes showed the highest activities toward p-nitrophenyl (p-NP) butyrate at pH 7.0 and 35–40 °C and were found to be resistant to some metal ions (Ba2+, Mg2+, and Sr2+) and detergents (Triton X-100, Tween 20, and Tween 80). DMWf18-543 and DMWf18-558 exhibited distinct substrate specificities and preferences. DMWf18-543 showed a catalytic range for substrates of C2–C8, whereas DMWf18-558 presented a wider range of C2–C14. Additionally, DMWf18-543 preferred p-NP butyrate, whereas DMWf18-558 preferred both p-NP butyrate and p-NP hexanoate. To investigate the mechanism underlying the phenotypic differences between the esterases, their three-dimensional structures were compared by using homology modeling. The results suggested that residue Leu199 of DMWf18-543 shortens and blocks the substrate-binding pocket. This hypothesis was confirmed by the finding that the DMWf18-558-A199L mutant showed a similar substrate specificity profile to that of DMWf18-543.

Conclusions

This study characterized two novel homologous esterases obtained from a deep-sea sediment metagenomic library. The structural modeling and mutagenesis analysis provided insight into the determinants of their substrate specificity and preference. The characterization and mechanistic analyses of these two novel enzymes should provide a basis for further exploration of their potential biotechnological applications.

Background

Esterases (EC 3.1.1.1) are lipolytic enzymes that catalyze the cleavage or formation of water-soluble short-chain fatty esters (< 10 carbon chain), whereas lipases (EC 3.1.1.1) prefer water-insoluble long-chain fatty esters (> 10 carbon chain) [1]. A considerable number of microbial esterases have been discovered and studied because of their potential for application in the agriculture, food, pharmaceutical and bioremediation industries [2, 3]. Owing to the limitations of cultivation, activity-based or sequence-based screening of enzymes from metagenomic libraries has become an effective and valuable approach for directly mining esterases from environment samples [4,5,6].

Bacterial lipolytic enzymes were classified into 17 families (I to XVII) [1, 7, 8]. Among these families, family IV (also known as the HSL family) esterases share remarkable sequence similarity with mammalian hormone-sensitive lipase (HSL) [1], which plays an important role in the regulation of fat cell lipolysis. Recently, numbers of family IV esterases have been isolated from various environments, such as marine environments [9,10,11,12], soil [13, 14], activated sludge [15] and the bovine rumen [16], through metagenomic methods.

Pairs of enzymes showing high sequence identity but some phenotypic differences are good materials for studying the mechanisms of catalysis. Their amino acid sequences and crystal structures or structural models can be compared to reveal the sequence or structural differences that cause phenotypic differences. For example, a comparison of the structures of the esterases RmEstA (preferring longer-chain esters) and RmEstB (preferring shorter-chain esters) has revealed that residues Phe222 and Trp92 of RmEstB are related to the shape of the substrate-binding pocket, thereby affecting substrate specificity [17]. Additionally, structural and biochemical analyses of the esterases EstFa_R (pH optimum of 5.0) and SshEstI (pH optimum of 8.0) have been carried out to investigate the mechanism underlying low-pH adaptation, and the unique extended hydrogen bond network around the catalytic triad and the negatively charged surface around the active site have been found to result in a low-pH optimum of EstFa_R [18].

A metagenomic library has previously been constructed from Pacific Ocean deep-sea sediment, from which several lipolytic enzymes have been screened [10]. In the present study, further activity-based screening for lipolytic enzymes was performed; two novel esterase genes (dmwf18-543 and dmwf18-558) were obtained using high-throughput sequencing method. The encoded enzymes, DMWf18-543 and DMWf18-558, showed high amino acid sequence identities but different enzymatic characteristics compared with esterases from the same metagenomic library previously obtained by Jiang et al. [10]. On the basis of the high sequence identity and the differences between the two enzymes in terms of substrate specificity and preference, their sequences and structural models were compared, and insights into the determinants of their phenotypic differences were obtained.

Methods

Metagenome sequencing and analysis

A deep-sea sediment sample (depth of 5886 m) was collected from the skirt of a seamount in the central Pacific Ocean and used to construct a fosmid metagenomic library, as described previously [10]. In this study, Escherichia coli EPI300 cells harboring fosmids were spread on Luria–Bertani (LB) agar medium supplemented with 12.5 µg/ml chloramphenicol and 1% tributyrin, and lipolytic-positive clones were screened by using the clear zone method [10]. The LB medium contained 10 g/L NaCl, 10 g/L tryptone, and 5 g/L yeast extract (BD, USA), at pH 7.0. To harvest large amounts of pCC2FOS fosmid DNA for sequencing, the E. coli EPI300 cells were cultivated with 2 μl/mL CopyControl™ Fosmid Autoinduction Solution (Epicentre Biotechnologies, USA) for 17 h at 250 rpm. The fosmid DNA was extracted using Axygen Plasmid Miniprep Kit (Corning, USA) and treated with plasmid-safe ATP-dependent DNase (Epicentre Biotechnologies, USA) to remove chromosomal DNA contamination from the host strain.

High-throughput sequencing of the fosmid vectors was carried out on the Illumina HiSeq 2000 platform by Novogene Bioinformatics Technology Co. Ltd. (Beijing). One paired-end (2 × 125 bp) library was constructed, with an approximate insert size of 500 bp. Reads were assembled de novo into contigs by using ABySS version 1.5.2 [19]. Assembly k-values from k = 48 to 64 were tested to identify the optimal value, of k = 62, by using the abyss-pe script. Vector contamination was filtered out via BLAST searches against the pCC2FOS2™ fosmid sequence (NCBI Accession Number EU140752). Open reading frame (ORF) prediction was performed by using MetaGeneMark [20]. The functional annotation of amino acid sequences of ORFs was performed with the BLASTP program (from the NCBI-Blast-2.2.29 + command-line package) [21] against the GenBank nr [22] and Cluster of Orthologous Groups (COG) [23] databases as well as with the PROKKA package [24].

Sequence analysis of esterase genes

Two highly related putative esterase genes designated dmwf18-543 and dmwf18-558 were screened, and their deduced amino acid sequences were analyzed using the BLASTP program (https://blast.ncbi.nlm.nih.gov) [25]. Multiple sequence alignment of their amino acid sequences was performed using Clustal X version 2 [26] and ESPript 3.0 [27]. The corresponding phylogenetic tree was constructed using the neighbor-joining method [28] with MEGA version 7.0 software [29].

Homology modeling and putative structure analysis

The three-dimensional (3D) structures of DMWf18-543 and DMWf18-558 were modeled using the SWISS-MODEL server (https://swissmodel.expasy.org/) [30, 31]. Structural figures were generated using PyMOL software (http://pymol.sourceforge.net).

Cloning, mutation, expression, and purification

The genes were amplified using PrimeSTAR HS DNA polymerase (TaKaRa, China). The primers 5ʹ-TCGCGGATCCATGGCCAGCCCACAGCT-3ʹ (BamHI site underlined) and 5ʹ-TCCGCTCGAGCTAGCGTGCGGCGGCGG-3ʹ (XhoI site underlined) were used to amplify the full-length dmwf18-543 gene; and the primers 5ʹ-TCGCGGATCCATGGCGAGTCCACAGCTCC-3ʹ (BamHI site underlined) and 5ʹ-ATTTGCGGCCGCCTAGCGTGCGGCGGC-3ʹ (NotI site underlined) were used to amplify dmwf18-558. The products were digested by corresponding restriction endonucleases (New England Biolabs, USA) and cloned into pSMT3 expression vector that had been digested with the same enzymes using T4 DNA ligase (New England Biolabs, USA). The recombinant plasmids were then transformed into E. coli Rosetta (DE3) cells for protein expression. Transformants harboring the recombinant plasmids were identified via PCR and further confirmed through DNA sequencing. Point mutants were generated by site-directed mutagenesis using the Fast Mutagenesis System (Transgene Biotech, China), with wild-type plasmids as templates. The cells were cultivated at 37 °C in LB medium with 50 µg/mL kanamycin and 200 rpm until the optical density (OD600) reached approximately 0.6 and were then induced with 0.5 mM of isopropyl-β-d-thiogalactopyranoside (IPTG) at 20 °C and 200 rpm. After cultivation for 16 h, the cells were collected via centrifugation at 12,000 rpm and 4 °C and then washed with phosphate-buffered saline (0.8% NaCl, 0.02% KCl, 0.142% Na2HPO4, 0.027% KH2PO4, pH 7.4). Next, the cells were suspended in 20 mM imidazole buffer (500 mM NaCl, 20 mM Tris–HCl, pH 8.0) and subjected to ultrasonic disruption (350 W). After centrifugation at 12,000 rpm and 4 °C for 30 min, the supernatant was purified with Ni Sepharose (GE, USA) to obtain the N-terminal His-tagged small ubiquitin-related modifier (SUMO) fusion. The fusion protein was cleaved with ubiquitin-like specific protease 1 (ULP1) with overnight dialysis at 4 °C. Subsequently, the products were passed through the Ni Sepharose column again to capture the His-tagged SUMO. The recombinant protein in the eluate was verified via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) using 12% polyacrylamide gels.

Enzyme activity assay

Esterase activity assays were performed using a spectrophotometric method. The standard reaction mixture contained 10 µL of 100 mM p-NP butyrate, 980 µL of phosphate buffer (100 mM, pH 7.5), and the purified enzyme in a final volume of 1 mL. The activity of the enzyme was quantified at 35 °C, and the release of p-nitrophenol was measured at 405 nm over 2 min with a DU800 ultraviolet–visible spectrophotometer (Beckman, USA). All values were determined in triplicate, and reactions with the added thermally inactivated enzyme were used as controls. One unit of enzyme activity was defined as the amount of esterase required to release 1 µmol of p-nitrophenol per minute from the p-NP ester.

Enzyme characterization

The kinetic parameters were obtained using p-NP butyrate and p-NP hexanoate as substrates at various concentrations (0.05, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.5, 1.8, and 2.0 mM). The kinetic parameters were calculated by analyzing the slopes of the Michaelis–Menten equation by using GraphPad software (GraphPad Inc., USA).

To determine substrate specificity, p-NP esters with various acyl chain lengths (C2–C16) were added to the reaction mixture at a final concentration of 1 mM. The substrates used in the study were p-nitrophenyl (p-NP) acetate (C2), p-NP butyrate (C4), p-NP caprylate (C8), p-NP decanoate (C10), p-NP laurate (C12), p-NP myristate (C14), and p-NP palmitate (C16) from Sigma-Aldrich (USA), and p-NP hexanoate (C6) from TCI (Japan).

The optimum temperature for enzyme activity was assessed over a range of 15–60 °C at intervals of 5 °C. The optimum pH for enzyme activity was determined over a pH range from 3.0 to 10.0. The release of p-nitrophenol at different pH values was measured at 348 nm, the pH-independent isosbestic wavelength of p-nitrophenol and p-nitrophenolate. The buffers used were 100 mM citrate buffer (pH 3.0–6.0), 100 mM phosphate buffer (pH 6.0–7.5), 100 mM tricine buffer (pH 7.5–9.0), and 50 mM CHES buffer (pH 9.0–10.0).

The effect of the chelating agent ethylenediaminetetraacetic acid (EDTA) was evaluated at a final concentration of 10 mM. The effects of various metal ions (Ba2+, Ca2+, Co2+, Cu2+, Mg2+, Mn2+, Ni2+, Sr2+ and Zn2+) were examined at a final concentration of 10 mM. The effects of various detergents, including SDS, Triton X-100, Tween-20, and Tween-80, were determined at a final concentration of 1% (v/v, except w/v for SDS). The effects of various organic solvents, including acetone, acetonitrile, ethanol, N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), glycerol, isopropanol, and methanol, were measured at final concentrations of 5 and 15% (v/v).

All values were determined in triplicate. Data were presented as mean ± SD. Statistical analyses were performed with two-tailed unpaired Student’s t-tests. P values less than 0.05 were considered statistically significant.

Nucleotide sequence accession numbers

The nucleotide sequences of contigs S36 and S37 have been deposited into the GenBank database under Accession Numbers MF770983 and MF770984. The locus_tags of dmwf18-543 and dmwf18-558 esterase genes are S36_0543 and S37_0558.

Results

Sequence analysis of fosmid clones

Eighteen lipolytic-positive clones were screened through activity-based screening and identified on the basis of clear zones around the colonies on LB agar medium supplemented with 1% tributyrin [10]. The fosmid clones were then mixed and used in high-throughput sequencing. In total, 40 contigs were assembled and annotated (data not shown). Among these contigs, S36 and S37 were 11,479 bp and 11,464 bp long and showed high sequence similarity with each other (97.3%, 11,176/11,488). Both of the contigs contained 14 ORFs with the same gene arrangement (Additional file 1: Table S1). The ORFs of the two contigs exhibited high sequence identities: 72.2–100.0% for their nucleotide sequences and 83.7–100.0% for their deduced amino acid sequences (Additional file 1: Table S1). The deduced amino acid sequences indicated that 8 out of the 14 ORFs could be assigned by using the COG classification system. Of these 8 ORFs, three encoded functions related to energy production and conversion, two related to lipid transport and metabolism, and one related to replication, recombination and repair.

Sequence analysis of the novel esterases

Two putative lipolytic enzyme genes of 909 bp were identified, encoding proteins of 302 amino acids; these genes were assigned as lipid transport and metabolism genes according to COG categories and designated dmwf18-543 and dmwf18-558, respectively (Additional file 1: Table S1). These proteins shared 80.7% (234/290) amino acid sequence identity with each other. Comparison of the amino acid sequences with known esterases in the GenBank nr database showed that DMWf18-543 and DMWf18-558 were similar (> 50% identities) to several esterases from metagenomes (Table 1). DMWf18-543 and DMWf18-558 shared 81.4% and 82.4% sequence identity (246/302 and 249/302) with esterase Est6 and 55.0 and 57.0% identity with Est2 or Est4 identified previously from the same metagenome (GenBank Accession No. AFB82690, AFB82678, and AFB82687) [10]; 54.0–57.5% identity with EstMY and EstMY09-02 from an activated sludge metagenome (ADM67447 and ADM67446) [15]; and 50.5–52.6% identity with esterases from soil metagenomes (AGF91877, AFC77925, AAS77236, AAS77233, and AAS77238) [32,33,34].

Table 1 Comparison of DMWf18-543 and DMWf18-558 with similar relatives

Phylogenetic analysis was carried out to reveal the relationships between the two esterases and other known bacterial lipolytic enzymes. A phylogenetic tree constructed with 17 bacterial lipolytic enzyme families showed that DMWf18-543 and DMWf18-558 belong to family IV (Fig. 1). Multiple sequence alignment of DMWf18-543 and DMWf18-558 with highly related homologs indicated that their catalytic triad is composed of residues Ser144, Glu238, and His268 (Fig. 2). The catalytic residue Ser144 and the oxyanion hole residues Gly75 and Gly76 are located in the GXSXG (GDSAG, position 142–146) and HGGG (positions 74–77) motifs, which are conserved in the family IV lipolytic enzymes.

Fig. 1
figure 1

Neighbor-joining phylogenetic tree based on the amino acid sequences of DMWf18-543, DMWf18-558 and related lipolytic enzymes. Sequence alignment was performed using ClustalX, and the tree was constructed using MEGA software. Bootstrap values are based on 1000 replicates, and only values > 50% are shown. The scale bar indicates the number of amino acid substitutions per site

Fig. 2
figure 2

Amino acid sequence alignment of DMWf18-543- and DMWf18-558-related lipolytic enzymes. The accession numbers of the enzymes in the GenBank database are given for DMWf18-543 and DMWf18-558 (from this study), Est6 (AFB82690), Est4 (AFB82689), EstMY (ADM67447), and ArmEst1 (AGF91877). Sequence alignment was performed using the ClustalX and ESPript programs. Identical and similar residues among groups are indicated in white text on a red background and in red text on a white background, respectively. Solid circles indicate the locations of the residues involved in the oxyanion hole (glycine (G)). The triangles indicate the locations of the catalytic active site residues (serine (S), aspartate (D), and histidine (H)). The square indicates the location of residue Leu199 of DMWf18-543 and residue Ala199 of DMWf18-558. The conserved HGGG and GXSXG motifs, in which the oxyanion hole and catalytic triad are located, are outlined with boxes

Expression and characterization

The gene fragments encoding the enzymes were cloned into the pSMT3 vector and expressed in E. coli Rosetta (DE3). After induction of expression with IPTG at 20 °C for 12 h, the recombinant proteins were purified using His-tag affinity chromatography. The calculated molecular weights (MW) of DMWf18-543 and DMWf18-558 were 32.32 and 32.12 kDa. SDS-PAGE analysis of the purified proteins revealed an approximate MW of 32 kDa, which was consistent with the calculated value of DMWf18-543 and DMWf18-558 (Additional file 2: Figure S1).

The kinetic parameters of purified DMWf18-543 and DMWf18-558 were determined by using p-NP butyrate and p-NP hexanoate as substrates, and the results are shown in Table 2. When p-NP butyrate was used as a substrate, the Vmax and Km of DMWf18-543 and DMWf18-558 were 5957 ± 112 µmol/mg/min and 0.33 ± 0.02 mM and 5523 ± 228 µmol/mg/min and 0.60 ± 0.06 mM, respectively.

Table 2 Kinetic parameters of DMWf18-543, DMWf18-558 and the mutant protein

The substrate specificities of the enzymes were determined by using p-NP esters with various acyl chain lengths (C2–C16) (Fig. 3a). Among the esters tested, DMWf18-543 exhibited the highest activity toward p-NP butyrate (4757 U/mg) and only weak activity toward p-NP acetate, p-NP hexanoate, and p-NP caprylate (10, 6, and 1% relative activities). Additionally, no activity was detected toward p-NP esters with side chains longer than C10. Nevertheless, DMWf18-558 exhibited high activity toward p-NP butyrate (4520 U/mg) and p-NP hexanoate (4054 U/mg). DMWf18-558 also retained over 14% and 27% relative activity toward p-NP acetate and p-NP caprylate, respectively, in addition to showing weak activity toward p-NP decanoate, p-NP laurate, and p-NP myristate (10, 4, and 3%) (Fig. 3a). The optimum activities of the enzymes were measured over a pH range of 3.0–10.0 and a temperature range of 15–60 °C, by using p-NP butyrate as the substrate. DMWf18-543 showed the highest activity at pH 7.0 and 35–40 °C and DMWf18-558 at pH 7.0 and 35 °C (Fig. 3b, c).

Fig. 3
figure 3

Characterization of DMWf18-543 and DMWf18-558. a Substrate specificity was determined using the p-NP esters, including p-NP acetate (C2), p-NP butyrate (C4), p-NP caprylate (C8), p-NP decanoate (C10), p-NP laurate (C12), p-NP myristate (C14), and p-NP palmitate (C16). All of the tests were performed at 35 °C and pH 7.5. b Effects of pH on the activity were determined in different buffers: 100 mM citrate buffer (pH 3.0–6.0), 100 mM phosphate buffer (pH 6.0–7.5), 100 mM tricine buffer (pH 7.5–9.0), and 50 mM CHES buffer (pH 9.0–10.0). All of the tests were performed at 35 °C using p-NP butyrate as the substrate. c Effects of temperature on the activity were determined at various temperatures at pH 7.5 using p-NP butyrate as the substrate. The highest activity was taken as 100%. Data are presented as the mean ± SD (n = 3)

DMWf18-543 and DMWf18-558 were highly resistant to 10 mM Ba2+, Mg2+, or Sr2+, retaining over 80% of their initial activity. However, their activities were strongly or completely inhibited by Cu2+, Ni2+, and Zn2+ (Table 3). The addition of all tested solvents at 5 and 15% (v/v) inhibited the activities of DMWf18-543 and DMWf18-558, except for glycerol, and over 85% of the initial activity of these enzymes was retained (Table 4). The addition of 1% SDS (w/v) inactivated DMWf18-543 and DMWf18-558. Furthermore, the activity of DMWf18-543 decreased to 45–67% when 1% Triton X-100, Tween 20, or Tween 80 (v/v) was added, whereas the activity of DMWf18-558 decreased to 10–29% when the detergents were added at 1% (Table 4).

Table 3 Effects of various metal ions and chelation on the activity of DMWf18-543 and DMWf18-558
Table 4 Effects of various organic solvents and detergents on the activity of DMWf18-543 and DMWf18-558

Overall structural models

The 3D structures of DMWf18-543 and DMWf18-558 were modeled using the SWISS-MODEL server. Both structures could be divided into two domains: a catalytic domain (residues 45–175 and 217–295 for DMWf18-543 and DMWf18-558) with a canonical α/β-hydrolase fold consisting of eight parallel β strands surrounded by five α helices and a cap domain (residues 4–44 and 176–216 for DMWf18-543, residues 1–44 and 176–216 for DMWf18-558) (Fig. 4).

Fig. 4
figure 4

Cartoon representation of 3D structural models of DMWf18-543 (a) and DMWf18-558 (b). The catalytic domains are shown in green/blue and yellow, and the cap domains are shown in magenta. The catalytic triad residues are indicated as stick models

Comparison of substrate-binding pockets

Superposition of the surfaces of DMWf18-543 and DMWf18-558 showed differences in their substrate-binding pockets (Fig. 5). The substrate-binding pocket of DMWf18-543 exhibited a short channel, whereas that of DMWf18-558 had a longer channel (~ 8 Å longer) (Fig. 5a, b). The difference in the shape of the substrate-binding pockets of the two esterases results in differences in the favored carbon chain lengths of the ester substrates (Fig. 3a). Superposition of the surface of DMWf18-558 and sticks of DMWf18-543 showed that residue Leu199 of DMWf18-543 might shorten and block the substrate-binding pocket (Fig. 5c), thus potentially leading to little DMWf18-543 activity toward p-NP esters with side chains longer than C6. Additionally, DMWf18-558, with relatively high activity toward p-NP hexanoate and p-NP caprylate, exhibited the relatively small side-chain residue Ala199 at the same location.

Fig. 5
figure 5

Substrate-binding pockets of DMWf18-543 and DMWf18-558. Surface view of the structures showing the differences in the substrate-binding pockets of DMWf18-543 (a) and DMWf18-558 (b). The substrate-binding pockets are indicated with red dashed lines. Residues of the catalytic triad are shown as stick models in yellow. c Superposition of the surfaces of DMWf18-543 (green) and DMWf18-558 (gray). Leu199 of DMWf18-543 and Ala199 of DMWf18-558 are shown as stick models

To verify the above hypothesis, two mutants (DMWf18-543-L199A and DMWf18-558-A199L) were designed, and only DMWf18-558-A199L was successfully expressed. The substrate specificity of the mutant was determined. Compared with the wild-type enzymes, the activity of the DMWf18-558-A199L mutant toward p-NP hexanoate and p-NP caprylate decreased markedly to 18 and 7% (Fig. 6). Additionally, little activity was detected toward p-NP esters with side chains longer than C10 (Fig. 6). The results suggested that residue 199 is the determinant of substrate specificity and preference.

Fig. 6
figure 6

Substrate specificity of DMWf18-558-A199L. The esterase activity of the mutant was determined using p-NP esters. The highest activity was taken as 100%. Data are presented as the mean ± SD (n = 3)

Discussion

In this study, we identified two novel esterase genes through activity-based screening and high-throughput fosmid sequencing from a metagenomic library from Pacific Ocean deep-sea sediment. We analyzed and compared the biochemical characteristics and structural models of the two esterases.

Forty contigs were obtained after 18 lipolytic-positive fosmid clones were sequenced and assembled. The two novel esterase genes were located on two contigs showing high sequence similarity and the same gene arrangement. Each contig contained 14 ORFs, and half of the ORFs (7 out of 14) presented the most significant BLAST hits to members of Chloroflexi (Additional file 1: Table S1), thus indicating that the two genome fragments might belong to uncultured Chloroflexi bacteria. Chloroflexi are quite frequently found in deep-sea surface sediment environments [35,36,37]. Additionally, a Chloroflexi genome fragment has previously been found and sequenced in the same metagenomic library [38].

The two novel esterases, DMWf18-543 and DMWf18-558, shared high amino acid identity with each other (80.7%) and showed the highest sequence identity to Est6, Est2 and Est4 among members of the database (55.0–82.4%), all of which were identified from the same metagenomic library through function-driven screening and subcloning [10]. The enzymatic characteristics of these esterases, which exhibited the same origin and shared high sequence identity, were compared. Est6 is a cold-activated esterase and exhibited its highest activity at 20 °C [10], whereas Est2 and Est4 exhibited their highest activity at higher temperatures (40–45 °C, data not shown), and DMWf18-543 and DMWf18-558 showed their highest activity at 35–40 °C. A comparison of DMWf18-543 with DMWf18-558 indicated that they displayed similar temperature and pH optimums, and the differences in the effects of various organic solvents, detergents and metals between them were not very large. However, in terms of their activity toward p-NP esters with different side-chain lengths, DMWf18-543 and DMWf18-558 showed notable differences. DMWf18-543 exhibited the highest activity toward p-NP butyrate and little activity toward p-NP hexanoate or p-NP esters with longer side chains. However, DMWf18-558 preferred both p-NP butyrate and p-NP hexanoate (about 90%) and retained 27% activity toward p-NP caprylate and even some activity toward p-NP esters with side chains of C10–C14.

To investigate the structural basis of the different substrate specificities and preferences of the enzymes, we attempted to obtain their crystal structures. Unfortunately, crystals did not appear and grow (data not shown). Thus, structural models of DMWf18-543 and DMWf18-558 were constructed and compared. The model comparison results suggested that DMWf18-543 has a short substrate-binding channel, whereas DMWf18-558 has a relatively long substrate-binding channel (Fig. 5a, b). The substrate-binding channel of DMWf18-543 was shortened by residue Leu199 (Fig. 5c), which might result in low or no activity toward p-NP esters with longer side chains. Residues Leu199 of DMWf18-543 and Ala199 of DMWf18-558 were selected for site-directed mutagenesis to investigate their roles in the substrate accommodation of substrate-binding pockets. Finally, DMWf18-558-A199L was induced and expressed successfully. The substitution of leucine for alanine caused the substrate-binding pocket to shorten, and the substrate specificity profile of DMWf18-558-A199L was similar to that of DMWf18-543 (Figs. 3a, 6). Furthermore, the DMWf18-558-A199L mutant retained little activity toward p-NP esters with side chains longer than C6.

The substrate specificity or preference of esterases toward esters with different acyl chain lengths is usually attributed to the shape of the substrate-binding pocket. A previous comparison of the crystal structures of two family IV esterases (RmEstA and RmEstB) from Rhizomucor miehei [17] has shown that two aromatic amino acids (Phe222 and Trp92) in the substrate-binding pocket of RmEstB narrow its substrate-binding pocket as well as its substrate specificity. Phe222 and Trp92 of RmEstB correspond to Tyr78 and Ala203 of DMWf18-543 and DMWf18-558, which are not located in their substrate-binding pockets. Thus, these two residues were not considered to be determinants of substrate specificity or preference on the basis of present study.

The mutation of residue Ala199 also affected the catalytic activity and substrate affinity of the enzyme. A decrease in the Km value and an increase in the kcat value toward p-NP butyrate were observed (from 0.60 ± 0.06 mM and 2957 ± 122/s to 0.16 ± 0.01 mM and 1126 ± 17/s, respectively), thus suggesting that the ability to bind substrate was enhanced and that the turnover rate of the enzyme–substrate complex to product and enzyme increased. Therefore, the catalytic efficiency of DMWf18-558-A199L against p-NP butyrate was higher than that of wild-type DMWf18-558, as indicated by a kcat/Km value of 7239/mM/s (Table 2).

The stronger substrate affinity and higher catalytic efficiency of DMWf18-558-A199L might make it more advantageous in industrial applications. In addition, the metal ion and detergent tolerant properties make DMWf18-543 and DMWf18-558 good candidates for biocatalytic processes requiring or containing metal ions or detergents, such as laundry detergent, textile, bioremediation and waste treatment.

In conclusion, two novel esterase genes with high similarity were screened, cloned and expressed from a deep-sea sediment metagenomic library. The enzymes were characterized and showed different hydrolysis abilities toward esters with different acyl chain lengths. Additionally, the structural modeling and mutagenesis of DMWf18-543 and DMWf18-558 provided insight into the determinants of their substrate specificity and preference. The characterization and mechanistic analysis of these enzymes should provide a basis for further exploration of their potential biotechnological applications.

Abbreviations

3D:

three-dimension

COG:

Cluster of Orthologous Groups

DMF:

N,N-dimethylformamide

DMSO:

dimethyl sulfoxide

EDTA:

ethylenediaminetetraacetic acid

HSL:

hormone-sensitive lipase

IPTG:

isopropyl-β-d-thiogalactopyranoside

LB:

Luria–Bertani

p-NP:

p-nitrophenyl

ORF:

open reading frame

SDS-PAGE:

sodium dodecyl sulfate polyacrylamide gel electrophoresis

References

  1. Arpigny JL, Jaeger KE. Bacterial lipolytic enzymes: classification and properties. Biochem J. 1999;343(Pt 1):177–83.

    Article  CAS  Google Scholar 

  2. Bornscheuer UT. Microbial carboxyl esterases: classification, properties and application in biocatalysis. FEMS Microbiol Rev. 2002;26:73–81.

    Article  CAS  Google Scholar 

  3. Panda T, Gowrishankar BS. Production and applications of esterases. Appl Microbiol Biotechnol. 2005;67:160–9.

    Article  CAS  Google Scholar 

  4. Lorenz P, Liebeton K, Niehaus F, Eck J. Screening for novel enzymes for biocatalytic processes: accessing the metagenome as a resource of novel functional sequence space. Curr Opin Biotechnol. 2002;13:572–7.

    Article  CAS  Google Scholar 

  5. Uchiyama T, Miyazaki K. Functional metagenomics for enzyme discovery: challenges to efficient screening. Curr Opin Biotechnol. 2009;20:616–22.

    Article  CAS  Google Scholar 

  6. Lorenz P, Schleper C. Metagenome—a challenging source of enzyme discovery. J Mol Catal B Enzym. 2002;19:13–9.

    Article  Google Scholar 

  7. Lenfant N, Hotelier T, Velluet E, Bourne Y, Marchot P, Chatonnet A. ESTHER, the database of the α/β-hydrolase fold superfamily of proteins: tools to explore diversity of functions. Nucleic Acids Res. 2013;41(D1):D423–9.

    Article  CAS  Google Scholar 

  8. Castilla A, Panizza P, Rodriguez D, Bonino L, Diaz P, Irazoqui G, et al. A novel thermophilic and halophilic esterase from Janibacter sp. R02, the first member of a new lipase family (family XVII). Enzyme Microb Technol. 2017;98:86–95.

    Article  CAS  Google Scholar 

  9. Oh KH, Nguyen GS, Kim EY, Kourist R, Bornscheuer U, Oh TK, et al. Characterization of a novel esterase isolated from intertidal flat metagenome and its tertiary alcohols synthesis. J Mol Catal B Enzym. 2012;80:67–73.

    Article  CAS  Google Scholar 

  10. Jiang X, Xu X, Huo Y, Wu Y, Zhu X, Zhang X, et al. Identification and characterization of novel esterases from a deep-sea sediment metagenome. Arch Microbiol. 2012;194:207–14.

    Article  CAS  Google Scholar 

  11. Chu X, He H, Guo C, Sun B. Identification of two novel esterases from a marine metagenomic library derived from South China Sea. Appl Microbiol Biotechnol. 2008;80:615–25.

    Article  CAS  Google Scholar 

  12. Li PY, Ji P, Li CY, Zhang Y, Wang GL, Zhang XY, et al. Structural basis for dimerization and catalysis of a novel esterase from the GTSAG motif subfamily of the bacterial hormone-sensitive lipase family. J Biol Chem. 2014;289:19031–41.

    Article  CAS  Google Scholar 

  13. Choi JE, Kwon MA, Na HY, Hahm DH, Song JK. Isolation and characterization of a metagenome-derived thermoalkaliphilic esterase with high stability over a broad pH range. Extremophiles. 2013;17:1013–21.

    Article  CAS  Google Scholar 

  14. Bunterngsook B, Kanokratana P, Thongaram T, Tanapongpipat S, Uengwetwanit T, Rachdawong S, et al. Identification and characterization of lipolytic enzymes from a peat-swamp forest soil metagenome. Biosci Biotechnol Biochem. 2010;74:1848–54.

    Article  CAS  Google Scholar 

  15. Li JG, Zhang KG, Han WJ. Cloning and biochemical characterization of a novel lipolytic gene from activated sludge metagenome, and its gene product. Microb Cell Fact. 2010;9:83.

    Article  Google Scholar 

  16. Prive F, Newbold CJ, Kaderbhai NN, Girdwood SG, Golyshina OV, Golyshin PN, et al. Isolation and characterization of novel lipases/esterases from a bovine rumen metagenome. Appl Microbiol Biotechnol. 2015;99:5475–85.

    Article  CAS  Google Scholar 

  17. Yang S, Qin Z, Duan X, Yan Q, Jiang Z. Structural insights into the substrate specificity of two esterases from the thermophilic Rhizomucor miehei. J Lipid Res. 2015;56:1616–24.

    Article  CAS  Google Scholar 

  18. Ohara K, Unno H, Oshima Y, Hosoya M, Fujino N, Hirooka K, et al. Structural insights into the low pH adaptation of a unique carboxylesterase from Ferroplasma: altering the pH optima of two carboxylesterases. J Biol Chem. 2014;289:24499–510.

    Article  CAS  Google Scholar 

  19. Simpson JT, Wong K, Jackman SD, Schein JE, Jones SJ, Birol I. ABySS: a parallel assembler for short read sequence data. Genome Res. 2009;19:1117–23.

    Article  CAS  Google Scholar 

  20. Zhu W, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 2010;38:e132.

    Article  Google Scholar 

  21. Cock PJ, Chilton JM, Grüning B, Johnson JE, Soranzo N. NCBI BLAST+ integrated into Galaxy. GigaScience. 2015;4:39.

    Article  Google Scholar 

  22. NCBI Resource Coordinators. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2013;41:D8.

    Article  Google Scholar 

  23. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28:33–6.

    Article  CAS  Google Scholar 

  24. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.

    Article  CAS  Google Scholar 

  25. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.

    Article  CAS  Google Scholar 

  26. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23:2947–8.

    Article  CAS  Google Scholar 

  27. Robert X, Gouet P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 2014;42:W320–4.

    Article  CAS  Google Scholar 

  28. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987;4:406–25.

    CAS  Google Scholar 

  29. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.

    Article  CAS  Google Scholar 

  30. Arnold K, Bordoli L, Kopp J, Schwede T. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics. 2006;22:195–201.

    Article  CAS  Google Scholar 

  31. Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, et al. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res. 2014;42:W252–8.

    Article  CAS  Google Scholar 

  32. Jin P, Pei X, Du P, Yin X, Xiong X, Wu H, et al. Overexpression and characterization of a new organic solvent-tolerant esterase derived from soil metagenomic DNA. Bioresour Technol. 2012;116:234–40.

    Article  CAS  Google Scholar 

  33. Lee SW, Won K, Lim HK, Kim JC, Choi GJ, Cho KY. Screening for novel lipolytic enzymes from uncultured soil microorganisms. Appl Microbiol Biotechnol. 2004;65:720–6.

    Article  CAS  Google Scholar 

  34. Zhang A, Zhao R, Jin P, Ma L, Xiong X, Xie T, et al. Discovery of a novel esterase subfamily sharing an identified arm sequence (ArmEst) by gene-specific metagenomic PCR. Biotechnol Lett. 2013;35:1937–44.

    Article  CAS  Google Scholar 

  35. Heijs SK, Laverman AM, Forney LJ, Hardoim PR, van Elsas JD. Comparison of deep-sea sediment microbial communities in the Eastern Mediterranean. FEMS Microbiol Ecol. 2008;64:362–77.

    Article  CAS  Google Scholar 

  36. Nunoura T, Takaki Y, Kazama H, Hirai M, Ashi J, Imachi H, et al. Microbial diversity in deep-sea methane seep sediments presented by SSU rRNA gene tag sequencing. Microbes Environ. 2012;27:382–90.

    Article  Google Scholar 

  37. Schauer R, Bienhold C, Ramette A, Harder J. Bacterial diversity and biogeography in deep-sea surface sediments of the South Atlantic Ocean. ISME J. 2010;4:159–70.

    Article  CAS  Google Scholar 

  38. Huo Y, Cheng H, Post AF, Wang C, Jiang X, Pan J, et al. Ecological functions of uncultured microorganisms in the cobalt-rich ferromanganese crust of a seamount in the central Pacific are elucidated by fosmid sequencing. Acta Oceanol Sin. 2015;34:92.

    Article  CAS  Google Scholar 

Download references

Authors’ contributions

XWX and YYH designed the study. YYH, SLJ, HC, ZR and HLC carried out the study. HC analyzed the metagenomic sequencing data. YYH and XWX analyzed the data and wrote the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We thank Nature Research Editing Service for the English language editing. This work was supported by grants from the National Natural Science Foundation of China (41506183 and 31770004), the Scientific Research Fund of the Second Institute of Oceanography, SOA (JG1623), the Top-Notch Young Talents Program of China and the China Postdoctoral Science Foundation (2016M590526).

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

The design of the study and collection and analysis of data were funded by the National Natural Science Foundation of China (41506183 and 31770004). The analysis of metagenomics data was funded by the Scientific Research Fund of the Second Institute of Oceanography, SOA (JG1623) and the China Postdoctoral Science Foundation (2016M590526). The labour fees for interpretation of data and writing the manuscript as well as English edit of the manuscript were funded by the Top-Notch Young Talents Program of China.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xue-Wei Xu.

Additional files

Additional file 1: Table S1.

Predicted protiens encoded by the fosmid clones.

Additional file 2: Figure S1.

SDS-PAGE of purified DMWf18-543 and DMWf18-558. Lane 1, purified DMWf18-543; Lane 2, purified DMWf18-558; Lane M, marker.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huo, YY., Jian, SL., Cheng, H. et al. Two novel deep-sea sediment metagenome-derived esterases: residue 199 is the determinant of substrate specificity and preference. Microb Cell Fact 17, 16 (2018). https://doi.org/10.1186/s12934-018-0864-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12934-018-0864-4

Keywords