Analysis of the Sequence Characteristics of Antifreeze Protein.
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ABSTRACT:
SUBMITTER: Zhang YH
PROVIDER: S-EPMC8226703 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: Highly repetitive sequences are the bane of genome sequence assembly, and the short read lengths produced by current next generation sequencing technologies further exacerbates this obstacle. An adopted practice is to exclude repetitive sequences in genome data assembly, as the majority of repeats lack protein-coding genes. However, this could result in the exclusion of important genotypes in newly sequenced non-model species. The absence of the antifreeze glycoproteins (AFGP) gene family in the recently sequenced Atlantic cod genome serves as an example. RESULTS: The Atlantic cod (Gadus morhua) genome was assembled entirely from Roche 454 short reads, demonstrating the feasibility of this approach. However, a well-known major adaptive trait, the AFGP, essential for survival in frigid Arctic marine habitats was absent in the annotated genome. To assess whether this resulted from population difference, we performed Southern blot analysis of genomic DNA from multiple individuals from the North East Arctic cod population that the sequenced cod belonged, and verified that the AFGP genotype is indeed present. We searched the raw assemblies of the Atlantic cod using our G. morhua AFGP gene, and located partial AFGP coding sequences in two sequence scaffolds. We found these two scaffolds constitute a partial genomic AFGP locus through comparative sequence analyses with our newly assembled genomic AFGP locus of the related polar cod, Boreogadus saida. By examining the sequence assembly and annotation methodologies used for the Atlantic cod genome, we deduced the primary cause of the absence of the AFGP gene family from the annotated genome was the removal of all repetitive Roche 454 short reads before sequence assembly, which would exclude most of the highly repetitive AFGP coding sequences. Secondarily, the model teleost genomes used in projection annotation of the Atlantic cod genome have no antifreeze trait, perpetuating the unawareness that the AFGP gene family is missing. CONCLUSIONS: We recovered some of the missing AFGP coding sequences and reconstructed a partial AFGP locus in the Atlantic cod genome, bringing to light that not all repetitive sequences lack protein coding information. Also, reliance on genomes of model organisms as reference for annotating protein-coding gene content of a newly sequenced non-model species could lead to omission of novel genetic traits.
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Project description:Antifreeze proteins (AFPs) play a pivotal role in the antifreeze effect of overwintering organisms. They have a wide range of applications in numerous fields, such as improving the production of crops and the quality of frozen foods. Accurate identification of AFPs may provide important clues to decipher the underlying mechanisms of AFPs in ice-binding and to facilitate the selection of the most appropriate AFPs for several applications. Based on an ensemble learning technique, this study proposes an AFP identification system called AFP-Ensemble. In this system, random forest classifiers are trained by different training subsets and then aggregated into a consensus classifier by majority voting. The resulting predictor yields a sensitivity of 0.892, a specificity of 0.940, an accuracy of 0.938 and a balanced accuracy of 0.916 on an independent dataset, which are far better than the results obtained by previous methods. These results reveal that AFP-Ensemble is an effective and promising predictor for large-scale determination of AFPs. The detailed feature analysis in this study may give useful insights into the molecular mechanisms of AFP-ice interactions and provide guidance for the related experimental validation. A web server has been designed to implement the proposed method.
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Project description:The reported NMR structure of RD3, a naturally occurring two-domain antifreeze protein, suggests that the two nearly identical domains are oriented to allow simultaneous binding of their active regions to the ice surface. It is implied that the nine residues linking the two domains play a role in this alignment, but this has not been established. We have designed and expressed a modified form of RD3 that replaces the nine-residue linker with a generic sequence of one serine and eight glycine residues to test the importance of the linker amino acid sequence. The modified linker is shown to have significantly different characteristics compared to the original linker. Heteronuclear nuclear Overhauser effect experiments show that the new linker residues have more mobility than the linker residues in the native protein. Further, NMR data show that the folding of the C-terminal domain is somewhat perturbed by the altered linker. Finally, distributions of residual dipolar couplings indicate that the two domains tumble and move independently of each other. Nevertheless, the thermal hysteresis activity of the modified protein is indistinguishable from that of native RD3, proving that increased activity of the two-domain antifreeze protein is not dependent on structure of the linker.
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Project description:Various cold-adapted organisms produce antifreeze proteins (AFPs), which prevent the freezing of cell fluids by inhibiting the growth of ice crystals. AFPs are currently being recognized in various organisms, living in extremely low temperatures. AFPs have several important applications in increasing freeze tolerance of plants, maintaining the tissue in frozen conditions and producing cold-hardy plants by applying transgenic technology. Substantial differences in the sequence and structure of the AFPs, pose a challenge for researchers to identify these proteins. In this paper, we proposed a novel method to identify AFPs, using supportive vector machine (SVM) by incorporating 4 types of features. Results of the two used benchmark datasets, revealed the strength of the proposed method in AFP prediction. According to the results of an independent test setup, our method outperformed the current state-of-the-art methods. In addition, the comparison results of the discrimination power of different feature types revealed that physicochemical descriptors are the most contributing features in AFP detection. This method has been implemented as a stand-alone tool, named afpCOOL, for various operating systems to predict AFPs with a user friendly graphical interface.
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Project description:Antifreeze proteins (AFPs) are proteins that protect cellular fluids and body fluids from freezing by inhibiting the nucleation and growth of ice crystals and preventing ice recrystallization, thereby contributing to the maintenance of life in living organisms. They exist in fish, insects, microorganisms, and fungi. However, the number of known AFPs is currently limited, and it is essential to construct a reliable dataset of AFPs and develop a bioinformatics tool to predict AFPs. In this work, we first collected AFPs sequences from UniProtKB considering the reliability of annotations and, based on these datasets, developed a prediction system using random forest. We achieved accuracies of 0.961 and 0.947 for non-redundant sequences with less than 90% and 30% identities and achieved the accuracy of 0.953 for representative sequences for each species. Using the ability of random forest, we identified the sequence features that contributed to the prediction. Some sequence features were common to AFPs from different species. These features include the Cys content, Ala-Ala content, Trp-Gly content, and the amino acids' distribution related to the disorder propensity. The computer program and the dataset developed in this work are available from the GitHub site: https://github.com/ryomiya/Prediction-and-analysis-of-antifreeze-proteins.
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