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Abstract As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses, for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses. 

Abstract BackgroundAt the molecular level, nonlinear networks of heterogeneous molecules control many biological processes, so that systems biology provides a valuable approach in this field, building on the integration of experimental biology with mathematical modeling. One of the biggest challenges to making this integration a reality is that many life scientists do not possess the mathematical expertise needed to build and manipulate mathematical models well enough to use them as tools for hypothesis generation. Available modeling software packages often assume some modeling expertise. There is a need for software tools that are easy to use and intuitive for experimentalists. ResultsThis paper introduces PlantSimLab, a web-based application developed to allow plant biologists to construct dynamic mathematical models of molecular networks, interrogate them in a manner similar to what is done in the laboratory, and use them as a tool for biological hypothesis generation. It is designed to be used by experimentalists, without direct assistance from mathematical modelers. ConclusionsMathematical modeling techniques are a useful tool for analyzing complex biological systems, and there is a need for accessible, efficient analysis tools within the biological community. PlantSimLab enables users to build, validate, and use intuitive qualitative dynamic computer models, with a graphical user interface that does not require mathematical modeling expertise. It makes analysis of complex models accessible to a larger community, as it is platform-independent and does not require extensive mathematical expertise. 

Summary Components of the plant immune signaling network need mechanisms that confer resilience against fast‐evolving pathogen effectors that target them. Among eight Arabidopsis CaM‐Binding Protein (CBP) 60 family members, AtCBP60g and AtSARD1 are partially functionally redundant, major positive immune regulators, and AtCBP60a is a negative immune regulator. We investigated possible resilience‐conferring evolutionary mechanisms among the CBP60a, CBP60g and SARD1 immune regulatory subfamilies.Phylogenetic analysis was used to investigate the times of CBP60 subfamily neofunctionalization. Then, using the pairwise distance rank based on the newly developed analytical platform Protein Evolution Analysis in a Euclidean Space (PEAES), hypotheses of specific coevolutionary mechanisms that could confer resilience on the regulator module were tested.The immune regulator subfamilies diversified around the time of angiosperm divergence and have been evolving very quickly. We detected significant coevolutionary interactions across the immune regulator subfamilies in all of 12 diverse core eudicot species lineages tested. The coevolutionary interactions were consistent with the hypothesized coevolution mechanisms.Despite their unusually fast evolution, members across the CBP60 immune regulator subfamilies have influenced the evolution of each other long after their diversification in a way that could confer resilience on the immune regulator module against fast‐evolving pathogen effectors.