Methanogen lyase homologous with high-dimensional characteristics of PeiW lyase and application of methanogen lyase

Abstract

The invention discloses methanogen lyase homologous with high-dimensional characteristics of PeiW lyase and application of the methanogen lyase, and aims to solve the problem that PeiW lyase protein of methanogen cell wall peptide bonds can participate in the biological process of hydrolyzing archaea cell walls, effectively kill methanogen and reduce methane production, and protein homologous with the protein has potential methane reduction potential. According to the method, a series of bioinformatics software is utilized, a protein sequence coded by methanogens virus is identified from a large amount of rumen microorganism virus group sequencing data, the high-dimensional homology of a deep learning model between the protein sequence and PeiW is analyzed, and two methanogens lyases similar to the high-dimensional characteristics obtained by the PeiW model are obtained. In order to realize the expression of the lyase, multiple segments of primers are designed to synthesize a target sequence, and the target sequence is successfully expressed in a prokaryotic expression system. Through detection of a crude enzyme solution, the effectiveness of the lyase in the aspect of reducing the yield of methane is verified in an in-vitro gas production test.

Description

Technical Field

[0001] The present invention relates to the field of protein function prediction and genetic engineering, and specifically relates to a methanogenic archaeal lyase homologous to the high-dimensional features of PeiW lyase and its applications. Background Art

[0002] Methane has a significant impact on global climate change and is the second largest greenhouse gas after carbon dioxide. Ruminants produce a large amount of methane during digestion and are an important source of methane emissions. Rumen microorganisms can decompose plant cell wall components such as cellulose and hemicellulose to produce intermediate products such as volatile fatty acids, CO2, and hydrogen, which are then utilized by methanogenic archaea to generate methane.

[0003] Methanogenic archaea belong to archaea and are a unique class of microorganisms with a distinct phylogenetic evolution different from bacteria. Their cell wall composition is very different from that of bacteria. Pseudopeptidoglycan is one of the different cell wall polymers present in archaea and is only found in the orders Methanobacteriales and Methanopyrales. Pseudopeptidoglycan has a similar overall three-dimensional structure to bacterial cell wall peptidoglycan. The particularity of the methanogenic archaeal pseudopeptidoglycan cell wall is mainly reflected in the following aspects. First, the pseudopeptidoglycan cell wall contains archaeal-specific sugars, and its glycan backbone is N-acetyltalosaminuronic acid. Second, β-1,3-glycosidic bonds are used to link N-acetylglucosamine or N-acetylgalactosamine to the glycan backbone. Finally, D-amino acids are absent in the peptide chain, and ε- and γ-isopeptide bonds are used in peptide and peptide cross-linking. These differences result in methanogenic archaea containing a pseudopeptidoglycan layer being resistant to lysozyme and other bacterial cell wall hydrolases. Therefore, it is necessary to deeply research and develop enzymes that can hydrolyze methanogenic archaeal pseudopeptidoglycan.

[0004] PeiW is a known methanogen lyase that can cleave the isopeptide bond Ala-ε-Lys in pseudomurein, thereby causing the lysis of the methanogen cell wall (Reference: Pseudomurein endoisopeptidases PeiW and PeiP, two moderately related members of a novel family of proteases produced in Methanothermobacter strains). PeiW is from the genome of the methanogen Methanothermobacter wolfeii and not from the rumen. Enzymatic property analysis shows that the lyase has low activity in the rumen environment. Therefore, in this invention, a deep learning model TM-Vec was used to evaluate the homology of these proteins with PeiW, and two novel methanogen lyases were discovered. Their characteristics were characterized by heterologous expression. The protein significantly reduced methane production in in vitro gas production tests, indicating its important application value in precisely regulating rumen methane production and reducing methane emissions from ruminants, etc. Summary of the Invention

[0005] The purpose of this invention is to address the current situation in the livestock industry, especially in ruminant production, where methane production is high and there is a lack of green and effective methane inhibitors. By using the growing microbial group sequencing data resources and the hot technologies in the fields of deep learning and computational biology, two methanogen lyases Pei317 and Pei479 that are homologous to the high-dimensional features of the PeiW lyase were obtained through a series of data mining. After prokaryotic system expression, the crude enzyme solution of the recombinant protein has a good effect on inhibiting methane production.

[0006] The purpose of this invention is achieved through the following technical solutions: A methanogen lyase homologous to the high-dimensional features of the PeiW lyase, and the amino acid sequence of the lyase is one of those shown in SEQ ID NO.1 to SEQ ID NO.2.

[0007] Furthermore, the process of screening the lyase is as follows:

[0008] (1) Collection of rumen metagenomic data and mining of archaeal virus proteins

[0009] By integrating the published rumen metagenome assembly, metagenome-assembled genomes, and virome data, using the virus recognition software geNomad for virus genome screening, using CheckV to remove multi-host contamination, incomplete virus genomes, and clip host sequence contamination, and obtaining viral operational taxonomic units (vOTUs) at the species level by de-redundancy with an average nucleotide similarity of 95% and an alignment coverage of 85% as the threshold; further predicting the potential hosts of vOTUs through iPhoP, screening for virus genomes that infect Archaea of the order Methanobacteriales, and predicting their encoded proteins using prodigal-gv; finally annotating the candidate proteins through the Merops peptidase database and retaining only peptidase proteins;

[0010] (2) Screening by high-dimensional feature homology alignment

[0011] Use the TM-Vec deep learning homology model to determine whether the proteins obtained in step (1) are homologous to PeiW in terms of the high-dimensional features of the model, and obtain a series of novel methanogen lyases homologous to PeiW at the high-dimensional feature level of the Tm-Vec model according to the set TM-Score threshold.

[0012] Furthermore, the specific process of determining whether a protein belongs to a peptidase is as follows: Based on the target substrate being the peptide chain between sugar backbones, the obtained viral proteins are annotated by Diamond blastp alignment with the Merops peptidase database, and the protein sequences that are peptidases are retained for subsequent analysis.

[0013] Furthermore, use the ProtParam module in the Biopython SeqUtils package to predict the stability of the obtained proteins for methanogen lyases.

[0014] Furthermore, use the deep learning model TM-Vec that links sequence and structure levels and allows searching for structure-structure similarity in large sequence libraries for homology alignment. By calculating the TM-score, determine whether the target protein has a homologous relationship with the template protein PeiP in the high-dimensional feature space, and select TM-score ≥ 0.6 as the judgment standard threshold for reliable homology. Proteins that meet this threshold are considered homologous to PeiP.

[0015] Furthermore, based on the recombinant vector and recombinant bacteria containing the methanogen lyase gene, perform fermentation induction expression, obtain the target protein through subsequent purification, and evaluate the effect of the target protein on in vitro microbial methane production.

[0016] On the other hand, the present invention also provides an application of a methanogen lyase that is highly homologous to the PeiW lyase in inhibiting methane production.

[0017] Advantages of the present invention: The present invention has generated and widely collected a large amount of rumen microbial virome sequencing data. Using a series of bioinformatics software, protein sequences encoded by methanogen viruses were identified therefrom, and the high-dimensional homology between these proteins and the PeiW deep learning model was further analyzed. Finally, the present invention successfully obtained two novel methanogen lyases with high-dimensional features similar to those learned by the PeiW model. To achieve the expression of this lyase, the present invention designed multiple primers to synthesize the target sequence and successfully expressed it in a prokaryotic expression system. Through the detection of the crude enzyme solution, the present invention verified the effectiveness of this novel lyase in reducing methane production in an in vitro gas production test. This novel methanogen lyase exhibits good research value and production application potential, laying a foundation for future applications in the field of methane reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following-described drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0019] Figure 1 is the PCR product of cloning the methanogen lyase;

[0020] Figure 2 is the SDS-PAGE analysis diagram of the crude enzyme solution of the recombinant protein;

[0021] Figure 3 is the effect of the recombinant protein on methane production. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following further details the present invention by combining specific implementation schemes. The following implementation schemes will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that any form of change and deformation made to the present invention by those of ordinary skill in the art without departing from the concept of the present invention belongs to the protection scope of the present invention.

[0023] The present invention provides a methanogen lyase homologous to the high-dimensional features of the PeiW lyase, its application, and its mining and characterization methods, and analyzes its application effect in inhibiting methane production, including the processes of microbiome data mining, sequence homology search, gene synthesis, protein expression, and methane inhibition effect evaluation. The specific steps are as follows:

[0024] 1. Microbiome data mining

[0025] Collect publicly published literature related to rumen microbiome and virome, download the corresponding metagenomic assembly data, metagenome-assembled genome data, and viral genome data, and combine with the assembly results of self-tested rumen metagenomic data. Input them into the geNomad software (which can combine gene content and deep neural network information for virus judgment) to mine the viral genomes therein. Use the CheckV software to judge the integrity and contamination degree of the viruses, remove low-quality genomes, and at the same time trim the potential host sequence contamination at both ends of the viral sequences to improve the accuracy of protein-coding function identification. And construct a rumen viral genome database for ruminants by removing redundancy at the species level with an average nucleotide similarity of 95% and an alignment coverage of 85% as the threshold. Further use the virus-host relationship prediction tool iPhoP, and add 791 non-redundant rumen archaeal genomes as candidate hosts on the basis of its original reference host genome library to increase specificity. Predict virus hosts through means such as provirus alignment, CRISPR spacer alignment, and deep learning feature capture of viral genomes, and retain the viral genomes that infect archaea in the order Methanobacteriales. Further use the meta mode of the prodigal-gv software to predict the set of viral proteins encoded. Based on the target substrate being the peptide chain between the sugar backbones in the archaeal cell wall, annotate the viral-encoded proteins by Diamond blastp alignment against the Merops peptidase database, and finally retain the protein sequences of peptidases.

[0026] 2. High-dimensional homology search of the deep learning homology model TM-Vec

[0027] The high-dimensional homology search of the deep learning homology model TM-Vec refers to searching for structural similarity in a large sequence library by combining protein sequence and structure information and using the TM-Vec (1.0.2) model. The TM-Vec software uses a siamese neural network to predict the TM-Score of protein pairs as the structural similarity index, generates protein vectors that can be effectively indexed and queried, without the need for intermediate structure calculations, generates structure-aware vector embeddings for protein sequences, and quickly searches for protein structures by finding the nearest neighbors in the embedding space, thus effectively narrowing the gap between protein sequences and structure information, and providing substantial improvements in terms of speed and sensitivity, with significantly higher efficiency than homology alignment based on predicted structures. Proteins that are homologous to PeiW at the high-dimensional level (TM-Score ≥ 0.6) are classified as PeiW homologous proteins and regarded as novel methanogen lyases. Predict the stability of these homologous proteins through the ProtParam module in the Biopython SeqUtils package. If the instability_index ≤ 40, then it is considered that the protein can exist stably.

[0028] The novel methanogen lyases Pei317, Pei479, and PeiW obtained in the present invention are homologous at the high-dimensional feature level of the deep learning model and can stably exist, as shown in the following table:

[0029]

[0030] 3. Heterologous expression of lyase

[0031] (1) Synthesis of lyase gene and construction of recombinant plasmid

[0032] The gene sequence of the target protein was designed in segments, and multiple segments were assembled into a complete target sequence by Overlap PCR. The pET-30a(+) vector was double-digested and linearized with XhoⅠ and NdeⅠ restriction endonucleases, and the target DNA fragment was ligated to the linearized vector using seamless cloning technology. It was then transformed into Escherichia coli DH5α competent cells, and positive clones were obtained by screening with kanamycin. After amplification culture, they were preserved.

[0033] (2) Transformation of recombinant plasmid and construction of expression strain

[0034] A high-quality recombinant plasmid Pei_pET-30a(+) was extracted using a plasmid miniprep kit and introduced into Escherichia coli BL21(DE3) competent cells by heat shock method. After recovery growth, positive clones were obtained by screening with kanamycin. As Figure 1 shown, after verifying the correctness of the gene sequence by colony PCR identification and Sanger sequencing, the engineered strain was preserved.

[0035] (3) Induced expression of recombinant protein

[0036] The verified engineered strain was inoculated into LB medium containing kanamycin for amplification culture. When the OD 600 of the bacterial solution reached 0.6, isopropyl β-D-1-thiogalactopyranoside (IPTG) with a final concentration of 0.25 mM was added, and induced expression was carried out at 16 °C for 18 hours. After centrifuging to collect the bacterial cells, lysis buffer was added to resuspend and remove cell debris to obtain a crude enzyme solution. Protein expression was verified by SDS-PAGE electrophoresis combined with Coomassie Brilliant Blue staining, and the results are as Figure 2 shown.

[0037] 4. Evaluation of the effect of recombinant protein on in vitro microbial methane production

[0038] The in vitro gas production technique was used to evaluate the effect of recombinant proteins on microbial methane production. The rumen fluid of three dairy cows was extracted by a vacuum pump, mixed, filtered through four layers of gauze, and then injected into a gas production bottle at an addition ratio of 5 mL:45 mL with artificial saliva as the culture substrate. The fermentation substrate was the TMR diet (collected from the pasture), and 500 mg of dry matter feed was added to each gas production bottle. 1 mL of crude enzyme solution was added to the treatment group, and the treatment was repeated 10 times. The control group (CON) was not supplemented with recombinant protein, and 1 mL of pure water was used as the negative control. When cultured in an incubator at 39 °C for 12 h, 24 h, and 48 h, the pressure in the gas production bottle was read using a pressure sensor, and the gas was collected.

[0039] Gas production: calculation formula

[0040] GP t is the gas production (mL) of the sample at time t; P t is the pressure (mPa) read at time t; V0 is the bottle volume; 101.3 is the standard atmospheric pressure (mPa); W is the dry matter weight of the sample. The total cumulative gas production during the gas production process is the sum of the gas production at each time period.

[0041] Methane production: The methane content of the collected gas was measured using a gas chromatograph. Methane production = gas production × methane content. The results showed ( Figure 3 ): Proteins Pei317 and Pei479 could significantly reduce the methane production of rumen microorganisms.

[0042] The above embodiments are used to explain the present invention rather than limit the present invention. Any modifications and changes made within the spirit and scope of the claims of the present invention fall within the protection scope of the present invention.

Claims

1. A methanogen lyase homologous to the high-dimensional features of PeiW lyase, characterized in that, The amino acid sequence of the lyase is one of those shown in SEQ ID NO.1 to SEQ ID NO.

2.

2. The two methanogen lyases homologous to the high-dimensional features of PeiW lyase according to claim 1, wherein The screening process of the lyase is as follows: (1) Collection of rumen metagenomic data and mining of archaeal virus proteins By integrating published rumen metagenomic assemblies, metagenome-assembled genomes and virome data, the virus recognition software geNomad was used to screen for virus genomes. CheckV was used to remove multi-host contaminated and genome-incomplete virus genomes and trim host sequence contamination, and virus operational taxonomic units vOTUs were obtained by de-redundancy at the species level with an average nucleotide similarity of 95% and an alignment coverage of 85% as the threshold; further, iPhoP was used to predict potential hosts of vOTUs, virus genomes infecting archaea of the order Methanobacteriales were screened, and their encoded proteins were predicted using prodigal-gv; finally, candidate proteins were annotated using the Merops peptidase database, and only peptidase proteins were retained; (2) Screening by high-dimensional feature homology alignment The TM-Vec deep learning homology model was used to determine whether the proteins obtained in step (1) were homologous to PeiW in terms of high-dimensional features of the model, and a series of novel methanogen lyases homologous to PeiW at the high-dimensional feature level of the Tm-Vec model were obtained according to the set TM-Score threshold.

3. A methanogen lyase homologous to the high-dimensional characteristics of PeiW lyase according to claim 2, characterized in that, The specific process of determining whether a protein belongs to a peptidase is as follows: based on the target substrate being the peptide chain between sugar backbones, the obtained virus proteins were annotated by Diamond blastp alignment against the Merops peptidase database, and the protein sequences that were peptidases were retained for subsequent analysis.

4. A methanogen lyase homologous to the high-dimensional characteristics of PeiW lyase according to claim 2, characterized in that, The ProtParam module in the Biopython Seq Utils package was used to predict the stability of the obtained proteins for methanogen lyases.

5. A methanogen lyase homologous to the high-dimensional characteristics of PeiW lyase according to claim 2, characterized in that, The TM-Vec deep learning model, which links sequence and structure levels and allows searching for structure-structure similarities in large sequence libraries, was used for homology alignment. By calculating the TM-score, it was determined whether the target protein had a homologous relationship with the template protein PeiP in the high-dimensional feature space. The threshold for judging reliable homology was set as TM-score ≥ 0.6, and proteins meeting this threshold were considered homologous to PeiP.

6. A methanogen lyase homologous to the high-dimensional characteristics of PeiW lyase according to claim 1, characterized in that, Based on the recombinant vector and recombinant bacteria containing the methanogen lyase gene, fermentation induction expression was carried out, and the target protein was obtained through subsequent purification, and the effect of the target protein on in vitro microbial methane production was evaluated.

7. Application of a methanogen lyase highly homologous to the PeiW lyase in inhibiting methane production.

Images