scholarly journals STUDIES ON THE MICROTUBULES IN HELIOZOA

1969 ◽  
Vol 43 (1) ◽  
pp. 148-165 ◽  
Author(s):  
Lewis G. Tilney ◽  
Breck Byers
Keyword(s):  
Natural Selection ◽  
Low Temperature ◽  
Model Building ◽  
Stable Configuration ◽  
Equilibrium Conditions ◽  
Staining Methods ◽  
Selection Of

On the assumption that the double-coiled pattern of microtubules in the axoneme of Echinosphaerium might be due to links of two sizes between adjacent microtubules, we disassembled microtubules with low temperature and then carefully analyzed the patterns of microtubules that formed upon the addition of heat (22°C) or heat and D2O. Although most of the initial clusters of microtubules that formed could not be interpreted as part of an axoneme, the spacings between these microtubules were the same as that in the axoneme, 70 and 300 A. By model building we were able to show that all clusters that form, including stages in the formation of the axoneme and its 12-fold symmetry, could be explained by links of two sizes (70 and 300 A) and the substructure of the microtubule. We could demonstrate these links with improved staining methods. We suggest that nonaxonemal assemblies of microtubules may be eliminated by the natural selection of the most energetically stable configuration of microtubules, all others undergoing disassembly under equilibrium conditions. Model building further supports this suggestion since the model axoneme possesses more links per tubule than any other cluster found.

The Natural Selection of Minds

1998 ◽  
Vol 43 (4) ◽  
pp. 263-264
Author(s):  
Joseph F. Rychlak
Keyword(s):  
Natural Selection ◽  
Selection Of

Bioluminescent proteins prediction with voting strategy.

2020 ◽  
Vol 15 ◽  
Author(s):  
Shulin Zhao ◽  
Ying Ju ◽  
Xiucai Ye ◽  
Jun Zhang ◽  
Shuguang Han
Keyword(s):  
Amino Acid ◽  
Model Building ◽  
Prediction Method ◽  
Pair Composition ◽  
Proposed Model ◽  
Counting Rules ◽  
Significant Phenomenon ◽  
Voting Strategy ◽  
Improved Accuracy ◽  
Selection Of

Background: Bioluminescence is a unique and significant phenomenon in nature. Bioluminescence is important for the lifecycle of some organisms and is valuable in biomedical research, including for gene expression analysis and bioluminescence imaging technology.In recent years, researchers have identified a number of methods for predicting bioluminescent proteins (BLPs), which have increased in accuracy, but could be further improved. Method: In this paper, we propose a new bioluminescent proteins prediction method based on a voting algorithm. We used four methods of feature extraction based on the amino acid sequence. We extracted 314 dimensional features in total from amino acid composition, physicochemical properties and k-spacer amino acid pair composition. In order to obtain the highest MCC value to establish the optimal prediction model, then used a voting algorithm to build the model.To create the best performing model, we discuss the selection of base classifiers and vote counting rules. Results: Our proposed model achieved 93.4% accuracy, 93.4% sensitivity and 91.7% specificity in the test set, which was better than any other method. We also improved a previous prediction of bioluminescent proteins in three lineages using our model building method, resulting in greatly improved accuracy.

scholarly journals Genetic diversity and natural selection on the thrombospondin-related adhesive protein (TRAP) gene of Plasmodium falciparum on Bioko Island, Equatorial Guinea and global comparative analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Li-Yun Lin ◽  
Hui-Ying Huang ◽  
Xue-Yan Liang ◽  
Dong-De Xie ◽  
Jiang-Tao Chen ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Plasmodium Falciparum ◽  
Natural Selection ◽  
Protein Structure ◽  
Transmembrane Protein ◽  
Fixation Index ◽  
Bioko Island ◽  
Adhesive Protein ◽  
Trap Gene ◽  
Selection Of

Abstract Background Thrombospondin-related adhesive protein (TRAP) is a transmembrane protein that plays a crucial role during the invasion of Plasmodium falciparum into liver cells. As a potential malaria vaccine candidate, the genetic diversity and natural selection of PfTRAP was assessed and the global PfTRAP polymorphism pattern was described. Methods 153 blood spot samples from Bioko malaria patients were collected during 2016–2018 and the target TRAP gene was amplified. Together with the sequences from database, nucleotide diversity and natural selection analysis, and the structural prediction were preformed using bioinformatical tools. Results A total of 119 Bioko PfTRAP sequences were amplified successfully. On Bioko Island, PfTRAP shows its high degree of genetic diversity and heterogeneity, with π value for 0.01046 and Hd for 0.99. The value of dN–dS (6.2231, p < 0.05) hinted at natural selection of PfTRAP on Bioko Island. Globally, the African PfTRAPs showed more diverse than the Asian ones, and significant genetic differentiation was discovered by the fixation index between African and Asian countries (Fst > 0.15, p < 0.05). 667 Asian isolates clustered in 136 haplotypes and 739 African isolates clustered in 528 haplotypes by network analysis. The mutations I116T, L221I, Y128F, G228V and P299S were predicted as probably damaging by PolyPhen online service, while mutations L49V, R285G, R285S, P299S and K421N would lead to a significant increase of free energy difference (ΔΔG > 1) indicated a destabilization of protein structure. Conclusions Evidences in the present investigation supported that PfTRAP gene from Bioko Island and other malaria endemic countries is highly polymorphic (especially at T cell epitopes), which provided the genetic information background for developing an PfTRAP-based universal effective vaccine. Moreover, some mutations have been shown to be detrimental to the protein structure or function and deserve further study and continuous monitoring.

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