Bt Research 2025, Vol.16, No.4, 136-146 http://microbescipublisher.com/index.php/bt 142 insecticidal-related gene clusters, while the B. cereus plasmid is mostly associated with food poisoning toxins (Carroll et al., 2017). Comparative analysis also showed that most Bt strains lacked the functional Cap virulence gene (anthrax virulence capsule synthetic gene), while Bacillus anthrax carries this gene through the pXO2 plasmid, which is one of the important reasons why Bt does not cause disease in mammals. On the other hand, some unique genes that Bt has are also worth paying attention to. 6.3 Analysis of molecular evolution rate and selection pressure To gain insight into the evolutionary dynamics of the Bt genome, researchers perform molecular evolution rate and selection pressure analysis for specific genes or gene sets. A common method is to calculate the ratio of non-synonymous substitution (dN) to synonymous substitution (dS), i.e. ω ratio, to determine whether there is a positive selection for the gene. By aligning multiple Bt strains or homologous gene sequences of Bt and lyrespective bacteria, using modules in PAML or MEGA to calculate dN/dS, the candidate genes that are positively selected can be screened out. For example, studies have compared multiple virulence-related genes in different Bt strains and found that the ω value of most cry toxin genes is close to 0, indicating that they are highly conserved in evolution, but a few toxin genes such as ω>1 of the vip3 subfamily, suggesting that these genes may have experienced positive selection and may be related to the host-pathogen arms race (Wang et al., 2020). To determine the selection pressure for specific amino acid sites, the Branch-site model or BEB analysis can be used to estimate ω of each site in the sequence alignment. This will identify the important functional domain residues that may be selected in toxin proteins. In addition to protein-encoded genes, repeats and insertion sequences can also affect genome evolution. There are a large number of insertion sequences in the Bt genome. The expansion time and rate can be estimated using the molecular clock model, thereby inferring the historical stage of the expansion of the Bt genome. Even events that speculative gene acquisition or loss can also occur in combination with phylogenetics. 7 Protein Structure and Function Prediction Tools 7.1 Cry toxin protein structure prediction and modeling tool The three-dimensional structure of Bt insecticidal crystal toxin (Cry protein) is very important for understanding its toxic mechanism. In recent years, AlphaFold, a protein structure prediction tool driven by artificial intelligence, has emerged, achieving high-precision structural prediction of any protein. AlphaFold2 achieved a breakthrough success in the 14th CASP evaluation and was able to predict protein folding structure with close experimental analytical accuracy. For macromolecules with multidomain such as Bt Cry toxins, AlphaFold can also give a reasonable folding model and domain arrangement. Researchers have begun applying AlphaFold to Cry protein research. AlphaFold was used to predict toxins that lack structural information in the past, such as Cry1Ia and Cry7Ca, and the results showed that typical three-domain structures (type I α-helical bundle, type II β-sheet cotton swab structure and type III β-sauna barrel structure), which were consistent with the known Cry model (Figure 2) (Torres et al., 2023). Panwar et al. designed a series of short peptides that simulate the common structure of Cry toxins and used molecular modeling (AlphaFold et al.) to predict their spatial configuration. The results showed that the artificially designed long-chain polypeptide (Bt Cry-GXJG-11) successfully folded to form a domain similar to natural Cry toxins and had a stable tertiary structure. This demonstrates the feasibility of artificially modified toxins that can be evaluated through structural predictions (Panwar et al., 2018). In addition to Cry toxins, Bt also produces other protein toxins (such as Vip, Cyt) and various enzymes, and structural prediction is equally important. With tools like AlphaFold, a highly reliable structural model can be quickly obtained with only amino acid sequences, greatly saving time and cost of experimental determination. 7.2 Protein-receptor interaction prediction (docking tool) The mechanism of action of Bt toxin involves the specific binding of toxin proteins to insect intestinal receptor molecules and membrane perforation. Therefore, predicting the interaction interface between toxin protein and receptor is crucial to understanding the virulence spectrum and resistance mechanisms. Molecular docking tools can be used to simulate binding patterns between toxins and receptors. For Cry toxins, some studies have been reported with receptors (such as the receptor proteins Cadherin, APN or ALP in the insect midgut epithelium).
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