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The present invention discloses an intestinal microbiota Bacteroides fragilis toxin-neutralizing nanobody and its application. By deeply studying the enterotoxigenic Bacteroides fragilis and the toxin BFT secreted by it in the bodies of patients with colorectal cancer and breast cancer, nanobodies against BFT are expressed by phage display technology; nanobodies with high binding affinity to the antigen are screened out through biopanning technology; a nanobody with the ability to neutralize the toxicity of BFT, also known as Nb2.43, is obtained. The present invention expresses and optimizes to obtain a BFT nanobody protein with high affinity, stability and uniformity, opening up a new field for the treatment of colorectal cancer and breast cancer with nanobodies targeting BFT, and having good research value and application prospects.

This invention discloses a methanogenic lyase homologous to PeiR lyase and its applications. The PeiR lyase protein, targeting the peptide bonds of the methanogenic cell wall, participates in the biological process of hydrolyzing the archaea cell wall, effectively killing methanogens and reducing methane production. Proteins homologous to this lyase possess potential methane-reducing potential. This invention utilizes a series of bioinformatics software to identify protein sequences encoded by methanogenic viruses from a large amount of rumen microbial virome sequencing data, and analyzes the structural homology between these proteins and PeiR. Ultimately, this invention successfully obtained a series of methanogenic lyases homologous to PeiR. To achieve the expression of these lyases, this invention designed multiple primers to synthesize the target sequences and successfully expressed them in a prokaryotic expression system. In vitro gas production experiments with the crude enzyme solution showed that these lyases are effective in reducing methane production.

The application discloses an antibacterial peptide designed by a generative artificial intelligence framework and targeting gram-negative bacteria and an application thereof, and belongs to the fields of artificial intelligence and biotechnology. The application designs and successfully obtains a novel antibacterial peptide by a generative artificial intelligence framework, the antibacterial peptide targeting gram-negative bacteria and having good antibacterial activity. It is verified by experiments that the antibacterial peptide MTAMP003 has good bacteriostatic capacity on E. coli, S. typhimurium, P. aeruginosa and A. baumannii, exhibits low cytotoxicity on human gastric mucosa epithelium and low hemolyticity on rabbit red blood cells, and has good application prospect and research value.

The application belongs to the technical field of biological medicine, and relates to a BCLAF1 protein Ser564 site phosphorylation antigen peptide, a specific antibody and a preparation method and application thereof. The application identifies BCLAF1 protein Ser564 as a key phosphorylation site through SIK2 kinase screening, and designs and synthesizes a phosphorylation antigen peptide based on the site. After immunizing animals, a polyclonal antibody specifically recognizing BCLAF1 Ser564 site phosphorylation modification is successfully prepared. The antibody has high sensitivity and strong specificity, is suitable for various detection platforms such as immunohistochemistry and immunoblotting, and can be used for evaluating tumor immunotherapy efficacy. The application provides a key tool for analyzing BCLAF1 phosphorylation regulation mechanism, and lays a theoretical foundation for developing an immune combined therapy strategy targeting a SIK2-BCLAF1-CCL5 axis.