Novel nylon-degrading enzyme based on sequence space mining and application thereof

Abstract

The present application relates to the technical field of bioinformatics and enzyme engineering, and particularly relates to a novel nylon-degrading enzyme based on sequence space mining and application thereof. The amino acid sequence of the novel nylon-degrading enzyme is shown in any one of SEQ ID NO: 1-10. Based on the method of sequence space mining, a series of novel nylon-degrading enzymes are mined, and two most representative nylon-degrading enzymes NylC-E4 and NylC-E10 are identified. Compared with the wild type NylCp2-TS, the nylon-6 hydrolysis specific activity of NylC-E4 is increased by 10.1 times, and the melting temperature is 97.2 DEG C; the specific activity of NylC-E10 is increased by 18.1 times, and the melting temperature is 97.9 DEG C. The present application provides novel nylon-degrading enzymes with ultrahigh thermal stability and catalytic activity, which have important application value in the field of green biodegradation of nylon waste.

Description

Technical Field

[0001] This invention relates to the fields of bioinformatics and enzyme engineering, specifically to a novel nylon-degrading enzyme based on sequence space mining and its applications. Background Technology

[0002] Polyamide (nylon) is widely used in textiles, automobiles, electronics, and other fields due to its excellent mechanical properties and chemical stability. However, nylon is extremely difficult to degrade in the natural environment, and large amounts of waste nylon cause serious "white pollution." Traditional physical recycling and chemical degradation methods suffer from high energy consumption, high costs, and the generation of harmful byproducts. Bio-enzymatic hydrolysis, due to its mild reaction conditions and environmental friendliness, has become a research hotspot for nylon waste treatment.

[0003] Nylon-degrading enzymes catalyze the hydrolysis of amide bonds in nylon oligomers or polymers. Based on substrate specificity, nylonases can be classified into NylA, NylB, and NylC types. Among them, the NylC type nylonase (EC 3.5.1.117) exhibits high hydrolytic activity against nylon-6 and its linear oligomers. Currently, the most effective NylC type nylon-degrading enzyme reported in the literature is derived from... Arthrobacter NylCp2-TS (wild-type) of sp. KI72. However, the number of experimentally validated NylC-type nylon degrading enzyme sequences in public enzyme databases (such as BRENDA) is extremely limited, and the known sequence diversity is very narrow, severely restricting the development of high-performance nylon degrading enzymes. Traditional functional screening methods are time-consuming and laborious, and cannot cover a broad sequence space.

[0004] Therefore, there is an urgent need for a systematic and efficient bioinformatics mining strategy to discover highly efficient nylon-degrading enzymes from the massive protein sequences in nature. In view of this, the present invention provides a novel nylon-degrading enzyme based on sequence space mining and its applications. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide a novel nylon degrading enzyme based on sequence space mining and its application. The aim is to successfully obtain a novel nylon degrading enzyme with superior catalytic activity and thermostability compared to wild-type NylCp2-TS by establishing a complete sequence similarity network mining process for NylC-type nylon degrading enzymes.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: In a first aspect, a novel nylon degrading enzyme based on sequence space mining, wherein the amino acid sequence of the novel nylon degrading enzyme is shown in any one of SEQ ID NO:1-10.

[0007] Based on the above technical solution, the present invention can be further improved as follows.

[0008] Furthermore, the amino acid sequence of the novel nylon degrading enzyme is shown in either SEQ ID NO:4 or SEQ ID NO:10.

[0009] Secondly, a nucleic acid molecule encodes the novel nylon-degrading enzyme described above, based on sequence space mining.

[0010] Furthermore, the sequence of the nucleic acid molecule is any one of SEQ ID NO:11-20.

[0011] Thirdly, a recombinant expression vector containing the aforementioned nucleic acid molecule.

[0012] Fourthly, a transformant obtained by introducing the nucleic acid molecule into a host, or by introducing the nucleic acid molecule into a host via the recombinant expression vector.

[0013] Fifthly, a method for sequence spatial mining of a novel nylon-degrading enzyme includes the following steps: (1) PSI-BLAST iterative search and sequence filtering: using NylC type nylonase NylCp2-TS (derived from Arthrobacter sp. KI72) is the seed sequence. PSI-BLAST search is performed to retain candidate sequences that have a bidirectional coverage of ≥90% and a sequence identity of ≥30% with the seed sequence. (2) Sequence Similarity Network (SSN) Construction and Visualization: Construct the sequence similarity network of the candidate sequences and identify the core clusters containing the seed sequences; (3) Multiple sequence alignment and phylogenetic analysis: Phylogenetic analysis was performed on the core clusters to divide them into evolutionary branches; (4) Selection of representative sequences: Select the sequence that is closest in average distance (i.e., the most conservative representative) and has complete sequence coverage from each evolutionary branch as the representative sequence; (5) The representative sequence is functionally verified to obtain the novel nylon degrading enzyme based on sequence space mining.

[0014] Furthermore, a novel method for sequence spatial mining of nylon-degrading enzymes includes the following steps: (1) PSI-BLAST iterative search and sequence filtering: Seed sequence: NylCp2-TS (derived from...) Arthrobacter sp. KI72) is the seed sequence.

[0015] Iterative search: Three rounds of PSI-BLAST search were performed on the NCBI non-redundant protein database (E-value < 0.005).

[0016] Strict filtering: Candidate sequences with bidirectional coverage ≥90% and sequence identity ≥30% with the seed sequence were retained, resulting in 631 putative NylC type nylonases.

[0017] (2) Construction and visualization of sequence similarity network (SSN): SSN analysis: Using the EFI-EST tool, a sequence similarity network was constructed with a 40% sequence identity threshold, and it was found that NylCp2-TS is located in a NylC core cluster containing 203 sequences.

[0018] (3) Multiple sequence alignment and phylogenetic analysis: The phylogenetic tree was constructed using the maximum likelihood method, and the cluster was divided into four evolutionary branches (branch-1 to branch-4). NylCp2-TS belongs to branch-4.

[0019] (4) Selection of representative sequences: The Sequence Demarcation Tool (SDT) is used to select representative sequences from each branch. There is a subbranch-nylon with 27 members in Branch-4. NylC-E4 and NylC-E5 to NylC-E10 are selected from it. NylC-E4 is the representative of branch-4, and NylC-E10 is the high-performance representative in the subbranch.

[0020] Sixthly, a method for preparing the protein of the novel nylon-degrading enzyme based on sequence space mining, wherein the seed culture of the transformant is inoculated into a fermentation medium and cultured to express the protein of the novel nylon-degrading enzyme based on sequence space mining.

[0021] The seventh aspect concerns the application of the novel nylon-degrading enzyme based on sequence space mining, the nucleic acid molecule, the recombinant expression vector, or the transformant in the degradation of nylon materials.

[0022] The nylon material includes at least one of nylon 6, nylon 66, nylon oligomers, nylon films, nylon particles, nylon fibers, and nylon-containing plastic waste.

[0023] Eighthly, a method for degrading nylon material includes the following steps: reacting the novel nylon-degrading enzyme based on sequence space mining with a substrate containing nylon material in a degradation reaction; The conditions for the degradation reaction are: temperature 25-95°C and pH 4.0-10.0.

[0024] The beneficial effects of this invention are: This invention is the first to combine PSI-BLAST iterative search, strict bidirectional coverage / identity filtering, SSN network analysis, and phylogenetic branch-guided functional verification to systematically uncover the unknown diversity of NylC-type nylon degrading enzymes. This invention discovered that branch-4 is a high-activity enrichment evolutionary lineage, from which two highly active and thermostable nylon degrading enzymes (NylC-E4 and NylC-E10) were identified. Among them, NylC-E4 and NylC-E10 have Tm values ​​close to 100℃, making them suitable for high-temperature reaction conditions, which is beneficial for improving reaction rates and substrate solubility, and has significant advantages in practical industrial applications. The provided discovery strategy can be extended to the discovery of other environmental enzymes (such as PET degrading enzymes and cellulases). Attached Figure Description

[0025] Figure 1 The results of mining nylon degrading enzymes based on sequence similarity networks are shown in Figure a, where SSN-based nylon enzyme mining process and evolutionary relationship are shown in Figure b, and phylogenetic analysis of NylC type nylon enzymes is shown in Figure b.

[0026] Figure 2 The results show the activity characterization and thermal stability (Tm) characterization of a representative novel nylon-degrading enzyme. Detailed Implementation

[0027] The principles and features of this invention are described below. The examples given are for illustrative purposes only and are not intended to limit the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they should be performed according to the techniques or conditions described in the literature in this field, or according to the product instructions. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased through legitimate channels.

[0028] Example 1. Discovery of NylC-type nylon degrading enzymes based on sequence similarity networks (SSN).

[0029] This embodiment uses the experimentally verified nylonase NylCp2-TS (derived from...). Arthrobacter Using sp. KI72, EC3.5.1.117 (SEQ ID NO: 21) as a seed, novel NylC-type nylonases were systematically discovered through the following steps: 1.1 PSI-BLAST Iterative Search and Sequence Filtering: Using the amino acid sequence of NylCp2-TS as the query sequence, three rounds of position-specific iterative BLAST (PSI-BLAST) were performed on the NCBI non-redundant protein database (nr database, March 2024 version). Parameter settings: E-value threshold 0.005; newly detected significant sequences were added to the position-specific score matrix in each iteration to expand the search range.

[0030] After obtaining several candidate sequences in the initial search, the following filtering criteria were adopted: sequence identity with NylCp2-TS ≥ 30%; bidirectional sequence coverage ≥ 90%.

[0031] Further analysis was performed using MMseqs2 software (version 13.45111) with default parameters to remove redundant and incomplete sequences (such as sequences that are too short or contain a large number of uncertain residues). A total of 631 putative NylC type nylonase sequences were obtained for subsequent analysis.

[0032] 1.2 Sequence Similarity Network (SSN) Construction and Visualization: A sequence similarity network was constructed using the Enzyme Function Initiative – Enzyme Similarity Tool (EFI-EST, https: / / efi.igb.illinois.edu / efi-est / ). The 631 sequences mentioned above were submitted to the EFI-EST server, and SSNs were generated based on pairwise BLAST similarity scores. Parameter settings: the Finalization value was set to 100 (i.e., 100 most similar edges were retained for each sequence), and the sequence identity threshold was adjusted according to the network density, ultimately using 40% as the connection threshold.

[0033] The generated network file was imported into Cytoscape software (version 3.10.2) for visualization and analysis. Clusters were defined based on network connectivity and sequence similarity. The results showed that NylCp2-TS is located in a well-defined NylC-type core cluster, which contains 203 closely related sequences (defined as the NylC core cluster).

[0034] 1.3 Multiple sequence alignment and phylogenetic analysis: Multiple sequence alignment (MSA) was performed on 203 sequences from the NylC core cluster. The alignment was performed using MAFFT software (version 7.525) with default parameters (automatic alignment strategy selection, G-INS-i algorithm). The alignment results were manually checked or gap-rich regions were removed using TrimAl (gap threshold set to 0.2).

[0035] Phylogenetic trees were constructed using the maximum likelihood method. Analysis was performed using IQ-TREE software (version 2.2.0): Model selection employed the ModelFinder automatic evaluation (BIC criterion), with the best alternative model (e.g., LG+F+G4) chosen, and the bootstrap value set to 1000 repetitions. The constructed phylogenetic trees were visualized and annotated using the iTOL online tool (https: / / itol.embl.de / ).

[0036] Based on the topological structure and branch support of the phylogenetic tree, the 203 sequences were divided into four distinct monophyletic branches, named branch-1, branch-2, branch-3, and branch-4. The known NylCp2-TS belongs to branch-4. Further observation revealed that branch-4 contains a subbranch (named subbranch-nylon) consisting of 27 sequences, which forms a tight, independent cluster on the tree.

[0037] 1.4 Selection of representative sequences: The Sequence Demarcation Tool (SDT, version 1.3, implemented in Python) was used to compute the pairwise sequence identity matrix of each sequence with other sequences within the branch. From each evolutionary branch, the representative sequence was selected as (i) the sequence with the closest average distance to other sequences within the branch (i.e., the most conservative representative) and (ii) the sequence coverage was complete.

[0038] Selected according to the above criteria: branch-1 represents: NylC-E1 (SEQ ID NO:1); branch-2 represents: NylC-E2 (SEQ ID NO: 2); branch-3 represents: NylC-E3 (SEQ ID NO:3); branch-4 represents: NylC-E4 (SEQ ID NO:4) (as a representative of branch-4 as a whole) and NylC-E5 (SEQ ID NO:5), NylC-E6 (SEQ ID NO:6), NylC-E7 (SEQ ID NO:7), NylC-E8 (SEQ ID NO:8), NylC-E9 (SEQ ID NO:9), and NylC-E10 (SEQ ID NO:10) (covering the major subclusters of subbranch-nylon) selected from subbranch-nylon. Figure 1 (ab).

[0039] 2. Expression and purification of novel nylon-degrading enzymes.

[0040] Genes encoding NylC-E1 to NylC-E10 (gene sequences shown in SEQ ID NO: 11-20) were synthesized, cloned into the pET-28a(+) expression vector (purchased from Beijing Qingke Biotechnology Co., Ltd.), and transformed into *E. coli* BL21(DE3) competent cells (purchased from Beijing Qingke Biotechnology Co., Ltd.). Single colonies were picked and inoculated into LB medium containing 50 µg / mL kanamycin and cultured at 37°C with shaking until OD... 600 Approximately 0.6–0.8 μL of 0.1 mM IPTG was added, and expression was induced at 18°C ​​for 20 hours. The bacterial cells were collected by centrifugation, sonicated, and then purified using nickel affinity chromatography. Purification was performed using buffer A (20 mM imidazole, 50 mM Tris, 500 mM NaCl, pH 7.5), buffer B (50 mM imidazole, 50 mM Tris, 500 mM NaCl, pH 7.5), and buffer C (500 mM imidazole, 50 mM Tris, 500 mM NaCl, pH 7.5). A 50 mM Tris-HCl buffer at pH 7.5 was used for desalting. Purity was verified by SDS-PAGE, and protein concentration was determined using the BCA method.

[0041] 3. Nylonase activity assay.

[0042] Nylon-6 (PA6 membrane (0.2 mm thickness, Goodfellpw)) was used as the substrate. The reaction system contained 50 mM Tris-HCl buffer (pH 8.0) and an enzyme-substrate ratio of 0.04 mM Menzyme / g PA6. The reaction was carried out at 60 °C for 24 hours. High-performance liquid chromatography (HPLC) was used to quantitatively detect the hydrolysis products (mobile phase: acetonitrile to water, volume ratio 3:1; detection wavelength: 220 nm; column: C18, 150 Å, 5 µm). The results showed that the representative enzymes (NylC-E1, E2, E3) in branches 1 to 3 had activities comparable to wild-type NylCp2-TS; the activity of NylC-E4 in branch 4 was significantly increased (10.1 times that of wild-type); and the NylC-E10 in subbranch-nylon had the highest activity (18.1 times that of wild-type). Figure 2 ).

[0043] 4. Thermal stability determination.

[0044] The melting temperature (Tm) of the enzymes was determined using differential scanning calorimetry (DSC). The temperature was increased from 30℃ to 110℃ at a rate of 1℃ / min, and the thermal denaturation curves were recorded. The results showed that the Tm of NylC-E4 was 97.2±0.1℃, the Tm of NylC-E10 was 97.9±0.2℃, and the Tm of wild-type NylCp2-TS was 77.1±0.1℃. Figure 2 ).

[0045] In summary, this invention is the first to combine PSI-BLAST iterative search, rigorous bidirectional coverage / identity filtering, SSN network analysis, and phylogenetic branch-guided functional verification to systematically uncover the unknown diversity of NylC-type nylon degrading enzymes. This invention discovered branch-4 as a high-activity enrichment evolutionary lineage and identified two highly active and thermostable nylon degrading enzymes (NylC-E4 and NylC-E10). The Tm values ​​of NylC-E4 and NylC-E10 are close to 100°C, making them suitable for high-temperature reaction conditions, which is beneficial for improving reaction rates and substrate solubility, and has significant advantages in practical industrial applications. The provided discovery strategy can be extended to the discovery of other environmental enzymes (such as PET degrading enzymes and cellulases).

[0046] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A novel nylon-degrading enzyme based on sequence space mining, characterized in that, The amino acid sequence of the novel nylon degrading enzyme is shown in any one of SEQ ID NO:1-10.

2. The novel nylon-degrading enzyme based on sequence space mining according to claim 1, characterized in that, The amino acid sequence of the novel nylon degrading enzyme is shown in either SEQ ID NO:4 or SEQ ID NO:

10.

3. A nucleic acid molecule, characterized in that, Encodes the novel nylon-degrading enzyme based on sequence space mining as described in claim 1 or 2.

4. A nucleic acid molecule according to claim 3, characterized in that, The sequence of the nucleic acid molecule is any one of SEQ ID NO:11-20.

5. A recombinant expression vector, characterized in that, It contains the nucleic acid molecule as described in claim 3 or 4.

6. A transformant, characterized in that, The transformant is obtained by introducing the nucleic acid molecule of claim 3 or 4 into the host, or by introducing the nucleic acid molecule of claim 3 or 4 into the host through the recombinant expression vector of claim 4.

7. A method for sequence spatial mining of a novel nylon-degrading enzyme, characterized in that, Includes the following steps: (1) PSI-BLAST iterative search and sequence filtering: Using NylC type nylonase NylCp2-TS as the seed sequence, PSI-BLAST search is performed to retain candidate sequences with bidirectional coverage ≥90% and sequence identity ≥30% with the seed sequence; (2) Sequence similarity network construction and visualization: Construct the sequence similarity network of the candidate sequences and identify the core clusters containing the seed sequences; (3) Multiple sequence alignment and phylogenetic analysis: Phylogenetic analysis was performed on the core clusters to divide them into evolutionary branches; (4) Selection of representative sequences: Select the sequence that is closest in average distance to other sequences within the same evolutionary branch and has complete sequence coverage from each evolutionary branch as the representative sequence; (5) Perform functional verification on the representative sequence to obtain the novel nylon degrading enzyme based on sequence space mining as described in claim 1 or 2.

8. A method for preparing the protein of the novel nylon-degrading enzyme based on sequence space mining as described in claim 1 or 2, characterized in that, The seed culture of the transformant according to claim 6 is inoculated into a fermentation medium and cultured to express the protein of the novel nylon-degrading enzyme based on sequence space mining.

9. The application of the novel nylon-degrading enzyme based on sequence space mining as described in claim 1 or 2, the nucleic acid molecule as described in claim 3 or 4, the recombinant expression vector as described in claim 5, or the transformant as described in claim 6 in the degradation of nylon materials.

10. A method for degrading nylon material, characterized in that, The process includes the following steps: reacting the novel nylon-degrading enzyme based on sequence space mining as described in claim 1 or 2 with a substrate containing nylon material to perform a degradation reaction; The conditions for the degradation reaction are: temperature 25-95°C and pH 4.0-10.0.

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