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

Abstract

The invention discloses methanogen lyase homologous with high-dimensional characteristics of PeiR lyase and application of the methanogen lyase and aims to solve the problems that PeiR lyase protein of methanogen cell wall peptide bonds can participate in the biological process of hydrolyzing archaea cell walls, methanogen is effectively killed, methane production is reduced, and protein homologous with the protein has potential methane reduction potential. According to the invention, a series of biological information software is utilized to identify protein sequences coded by methanogen viruses from a large amount of rumen microbiome sequencing data, and high-dimensional homology between the proteins and PeiR proteins based on a deep learning model TM-Vec is further analyzed, so that a series of methanogen lyases 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 the detection of crude enzyme liquid, the effectiveness of the lyase in the aspect of reducing the methane yield 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 particularly to a methanogenic archaeal lyase homologous to the high-dimensional features of PeiR lyase and its application. Background Art

[0002] Methane has a significant impact on global climate change. Its global warming potential on a 20-year scale is 82.5 times that of CO2. 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 methanogens to generate methane.

[0003] Methanogens belong to archaea, a unique class of microorganisms with a distinct phylogenetic evolution different from bacteria, and there are significant differences in the composition of their cell walls compared to 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 methanogen pseudopeptidoglycan cell wall is mainly reflected in the following aspects. Firstly, the pseudopeptidoglycan cell wall contains archaeal-specific sugars, and its glycan backbone is N-acetyltalosaminuronic acid. Secondly, β-1,3-glycosidic bonds are used to link N-acetylglucosamine or N-acetylgalactosamine to the glycan backbone. Finally, D-amino acids are lacking in the peptide chain, and ε- and γ-isopeptide bonds are used in peptide and peptide cross-linking. These differences result in methanogens containing a pseudopeptidoglycan layer being resistant to lysozyme and other bacterial cell wall hydrolases. Therefore, it is necessary to conduct in-depth research and development on enzymes capable of hydrolyzing methanogen pseudopeptidoglycan.

[0004] Previous studies have discovered a methanogenic archaeal lyase PeiR from the genome of the rumen methanogen Methanobrevibacter ruminantium M1 (Reference: Tailored Nanoparticles With the Potential to Reduce Ruminant Methane Emissions). However, the structure of PeiR is relatively unstable, which is not conducive to subsequent applications. Therefore, the present invention uses high-dimensional feature homologous search to evaluate the homology of proteins with PeiR, and finally discovers a series of methanogenic archaeal lyases, and characterizes their features through heterologous expression and evaluates their in vitro effects, which is of great significance and application value for practical production aspects such as reducing methane production in animal husbandry and improving feed conversion efficiency. Summary of the Invention

[0005] The object of the present 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 utilizing the growing microbial community sequencing data resources and hot technologies in the field of computational biology, a series of methanogen lyases Pei345, Pei352, Pei380, Pei381, Pei438, Pei473, Pei558, Pei829, Pei850, Pei952, and Pei993 that are homologous to the high-dimensional features of PeiR lyase are 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 object of the present invention is achieved by the following technical solutions: A series of methanogen lyases homologous to the high-dimensional features of PeiR lyase, and the amino acid sequence of the lyase is one of those shown in SEQ ID NO.1 to SEQ ID NO.11.

[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] Collect the published rumen metagenomic assembly data, metagenome-assembled genomes, and virus genome data. Use geNomad to mine and screen virus genomes, use CheckV to remove multi-host contaminated and genome-incomplete virus genomes and trim host sequence contamination, and perform species-level dereplication with an average nucleotide similarity of 95% and an alignment coverage of 85% as the threshold to obtain vOTUs. Use iPhoP to predict the potential hosts of vOTUs and retain the virus genomes that infect methanogenic archaea in the order Methanobacteriales, and use prodigal-gv to predict the encoded proteins; use the Merops peptidase database to annotate whether the obtained proteins belong to peptidases and remove the non-peptidase parts.

[0010] (2) Mining proteins homologous to PeiR based on high-dimensional feature homology:

[0011] Use the TM-Vec model to perform high-dimensional feature homology analysis on the proteins obtained in step (1) to determine whether they have structural-sequence comprehensive similarity with PeiR protein in the deep learning feature space; finally, screen and obtain methanogen lyases homologous to PeiR in the high-dimensional feature dimension of the TM-Vec model.

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

[0013] Furthermore, by calculating the TM-score, it is determined whether the target protein has a homologous relationship with the template protein PeiR in the high-dimensional feature space. TM-score ≥ 0.6 is selected as the judgment criterion for reliable homology, and proteins that meet this threshold are considered homologous to PeiR.

[0014] Furthermore, based on the recombinant vector and recombinant bacteria containing the methanogen lyase gene, fermentation induction expression is carried out, and the target protein is obtained through subsequent purification, and the effect of the target protein on in vitro microbial methane production is evaluated.

[0015] On the other hand, the present invention provides an application of a series of methanogen lyases that are highly homologous to the PeiR lyase in inhibiting methane production.

[0016] Advantages of the present invention: The present invention measures and widely collects a large amount of rumen microbiome sequencing data, uses a series of bioinformatics software to identify the protein sequences encoded by methanogenic viruses therefrom, and further analyzes the high-dimensional homology between these proteins and the PeiR protein based on the deep learning model TM-Vec. Finally, the present invention successfully obtains a series of methanogen lyases. To achieve the expression of these lyases, the present invention designs multiple primers to synthesize the target sequence and successfully expresses it in a prokaryotic expression system. Through the detection of the crude enzyme solution, the present invention verifies the effectiveness of these lyases in reducing methane production in an in vitro gas production experiment. This series of methanogen lyases demonstrates good research value and production application potential, laying a foundation for future applications in the field of methane emission reduction. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description 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.

[0018] Figure 1 is the PCR product of cloning the methanogen lyase;

[0019] Figure 2 is the SDS-PAGE analysis diagram of the crude enzyme solution of the recombinant protein;

[0020] Figure 3 is the effect of the recombinant protein on methane production. Detailed Embodiments

[0021] The present invention will be further described in detail below in conjunction with specific implementation embodiments. The following implementation embodiments 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 for those of ordinary skill in the art, any form of change and deformation made to the present invention without departing from the concept of the present invention falls within the protection scope of the present invention.

[0022] The present invention provides a series of methanogen lyases homologous to the high-dimensional features of PeiR lyase, and methods for their mining and characterization, and analyzes their application effects in inhibiting methane production, including microbiome data mining, sequence homology search, gene synthesis, protein expression, and methane inhibition effect evaluation processes. The specific steps are as follows:

[0023] 1. Microbiome data mining

[0024] Collect literature related to rumen microbiome and virome, download the corresponding metagenomic assembly data, metagenome-assembled genome data, and viral genome data, and add the assembly results of self-tested rumen metagenomic data. Input them into the software geNomad that combines information from gene content and deep neural networks for virus judgment to mine and confirm the viral genomes therein. Use the CheckV software to judge the integrity and contamination degree of the viruses to 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. Use 95% average nucleotide similarity and 85% alignment coverage as thresholds to perform species-level dereplication to obtain the ruminant rumen viral genome database vOTUs. Further use the virus-host relationship prediction tool iPhoP, and add 791 non-redundant rumen archaeal genomes to its original library as candidate hosts to increase specificity. Predict virus hosts by means of provirus alignment, CRISPR spacer alignment, and deep learning feature capture of viral genomes, and retain the viral genomes that infect methanogenic archaea of the order Methanobacteriales. Further use the meta mode of the prodigal-gv software to predict the encoded viral protein set. Based on the target substrate being the peptide chain between sugar skeletons, annotate the obtained viral proteins by Diamond blastp alignment against the Merops peptidase database, and retain the protein sequences that are peptidases for subsequent analysis.

[0025] 2. High-dimensional feature homology search

[0026] High-dimensional feature homology search is based on the deep learning model TM-Vec (v1.0.2), which can effectively mine the structural similarity between proteins in a large sequence database and comprehensively reflect the deep connection between sequence and structural information. The similarity between the target protein and the template protein PeiR in the high-dimensional feature space is evaluated by calculating the TM-score, and pairs with TM-score ≥ 0.6 are selected as reliable homologous results. This method has high sensitivity and accuracy in identifying distant homologous relationships that are difficult to discover by traditional sequence alignment methods. Finally, 11 methanogen lyases obtained are homologous to PeiR in the TM-Vec model dimension, and the specific information is shown in the following table:

[0027]

[0028] 3. Heterologous expression of lyase

[0029] (1) Synthesis of lyase gene and construction of recombinant plasmid

[0030] 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, then transformed into Escherichia coli DH5α competent cells. Positive clones were obtained by screening with kanamycin, and after amplification culture, they were preserved.

[0031] (2) Transformation of recombinant plasmid and construction of expression strain

[0032] The recombinant plasmid Pei_pET-30a(+) with high purity and concentration 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.

[0033] (3) Induced expression of recombinant protein

[0034] The verified engineered strain was inoculated into LB medium containing kanamycin for expansion culture. When the OD600 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 bacteria, the bacteria were resuspended with lysis buffer and cell debris was removed to obtain 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.

[0035] 4. Evaluation of the Effect of Recombinant Proteins on Microbial Methane Production in Vitro

[0036] 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 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. At 12 h, 24 h, and 48 h of incubation in a 39 °C incubator, the pressure in the gas production bottle was read using a pressure sensor, and the gas was collected.

[0037] Gas production: calculation formula

[0038] 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.

[0039] 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 Pei345, Pei352, Pei380, Pei381, Pei438, Pei473, Pei558, Pei829, Pei850, Pei952, and Pei993 could significantly reduce the methane production of rumen microorganisms.

[0040] The above embodiments are used to explain and illustrate the present invention, rather than limiting 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 having high-dimensional homology to PeiR 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.

11.

2. A methanogen lyase having high-dimensional homology to PeiR lyase according to claim 1, characterized in that: The lytic enzyme screening process is as follows: (1) Rumen metagenomic data collection and archaeal viral protein mining Published rumen metagenomic assembly data, metagenomic assembly genomes and viral genome data were collected, geNomad was used to mine and screen viral genomes, CheckV was used to remove multi-host contamination, viral genomes with incomplete genomes and host sequence contamination were removed, and vOTUs were de-redundant at the species level with 95% average nucleotide similarity and 85% alignment coverage as thresholds. iPhoP was used to predict potential hosts of vOTUs and retain viral genomes infecting methanogenic archaea of ​​the Methanobacteriales order. Prodigal-gv was used to predict the encoded proteins. The Merops peptidase database was used to annotate whether the obtained proteins belonged to peptidases and remove the non-peptidase parts. (2) Based on high-dimensional feature homology mining and PeiR homologous proteins: The protein obtained in step (1) was subjected to high-dimensional feature homology analysis using the TM-Vec model to determine whether it had a comprehensive structural-sequence similarity with the PeiR protein in the deep learning feature space; and finally, a methanogenic lyase homologous to PeiR in the high-dimensional feature dimension of the TM-Vec model was screened and obtained.

3. A methanogen lyase having high-dimensional homology to PeiR lyase according to claim 2, characterized in that: The specific process of determining whether a protein is a peptidase is as follows: based on the target substrate being a peptide chain between sugar backbones, the obtained viral protein is compared with the Merops peptidase database annotation by Diamond blastp, and the protein sequence that is a peptidase is retained for subsequent analysis.

4. A methanogen lyase having high-dimensional homology to PeiR lyase according to claim 2, characterized in that: By calculating the TM-score, we determined whether the target protein had homology with the template protein PeiR in the high-dimensional feature space. We selected TM-score ≥ 0.6 as the criterion for reliable homology, and proteins that met this threshold were considered to be homologous to PeiR.

5. A methanogen lyase having high-dimensional homology to PeiR lyase according to claim 1, characterized in that: Based on the recombinant vector and recombinant bacteria containing the methanogen lyase gene, fermentation-induced 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.

6. Application of a methanogenic bacterial lyase with high-dimensional features homologous to PeiR lyase in inhibiting methane production.

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