Aging is a fundamental biological process. Characterization of genetic and environmental factors that influence lifespan is a crucial step toward understanding the mechanisms of aging at the organism level. To capture the different effects of genetic and environmental factors on lifespan, appropriate statistical analyses are needed. We developed an online application for survival analysis (OASIS) that helps conduct various novel statistical tasks involved in analyzing survival data in a user-friendly manner. OASIS provides standard survival analysis results including Kaplan-Meier estimates and mean/median survival time by taking censored survival data. OASIS also provides various statistical tests including comparison of mean survival time, overall survival curve, and survival rate at specific time point. To visualize survival data, OASIS generates survival and log cumulative hazard plots that enable researchers to easily interpret their experimental results. Furthermore, we provide statistical methods that can analyze variances among survival datasets. In addition, users can analyze proportional effects of risk factors on survival. OASIS provides a platform that is essential to facilitate efficient statistical analyses of survival data in the field of aging research. Web application and a detailed description of algorithms are accessible from http://sbi.postech.ac.kr/oasis.
Significance: Reactive oxygen species (ROS) have long been thought to cause aging and considered to be toxic byproducts generated during mitochondrial respiration. Surprisingly, recent studies show that modestly increased ROS levels lengthen lifespan, at least in the roundworm Caenorhabditis elegans . It was unclear how the levels of potentially toxic ROS are regulated and how ROS promote longevity. Here we demonstrate that ROS activate two proteins, AMP-activated kinase (AMPK) and hypoxia-inducible factor 1 (HIF-1), to promote longevity by increasing immunity. Further, we find that internal ROS levels are reduced by AMPK while being amplified by HIF-1 when animals are stimulated to have higher ROS levels. Thus, balancing ROS at optimal levels appears to be crucial for organismal health and longevity.
Control of enzyme allosteric regulation is required to drive metabolic flux toward desired levels. Although the three-dimensional (3D) structures of many enzyme-ligand complexes are available, it is still difficult to rationally engineer an allosterically regulatable enzyme without decreasing its catalytic activity. Here, we describe an effective strategy to deregulate the allosteric inhibition of enzymes based on the molecular evolution and physicochemical characteristics of allosteric ligand-binding sites. We found that allosteric sites are evolutionarily variable and comprised of more hydrophobic residues than catalytic sites. We applied our findings to design mutations in selected target residues that deregulate the allosteric activity of fructose-1,6-bisphosphatase (FBPase). Specifically, charged amino acids at less conserved positions were substituted with hydrophobic or neutral amino acids with similar sizes. The engineered proteins successfully diminished the allosteric inhibition of E. coli FBPase without affecting its catalytic efficiency. We expect that our method will aid the rational design of enzyme allosteric regulation strategies and facilitate the control of metabolic flux. Design of allosterically regulatable enzyme is essential to develop a highly efficient metabolite production. However, mutations on allosteric ligand binding sites often disrupt the catalytic activity of enzyme. To aid the design process of allosterically controllable enzymes, we develop an effective computational strategy to deregulate the allosteric inhibition of enzymes based on sequence evolution analysis of allosteric ligand-binding sites. We analyzed the molecular evolution and amino acid composition of catalytic and allosteric sites of enzymes, and discovered that allosteric sites are evolutionarily variable and comprised of more hydrophobic residues than catalytic sites. We then experimentally tested our strategy of enzyme allosteric regulation and found that the designed mutations effectively deregulated allosteric inhibition of FBPase. We believe that our method will aid the rational design of enzyme allosteric regulation and help to facilitate control of metabolic flux.