NHR-49 Helps Germline-Less Worms Chew the Fat

In C. elegans, removal of the germline extends lifespan significantly. We demonstrate that the nuclear hormone receptor, NHR-49, enables the response to this physiological change by increasing the expression of genes involved in mitochondrial β-oxidation and fatty-acid desaturation. The coordinated augmentation of these processes is critical for germline-less animals to maintain their lipid stores and to sustain de novo fat synthesis during adulthood. Following germline ablation, NHR-49 is up-regulated in somatic cells by the conserved longevity determinants DAF-16/FOXO and TCER-1/TCERG1. Accordingly, NHR-49 overexpression in fertile animals extends their lifespan modestly. In fertile adults, nhr-49 expression is DAF-16/FOXO and TCER-1/TCERG1 independent although its depletion causes age-related lipid abnormalities. Our data provide molecular insights into how reproductive stimuli are integrated into global metabolic changes to alter the lifespan of the animal. They suggest that NHR-49 may facilitate the adaptation to loss of reproductive potential through synchronized enhancement of fatty-acid oxidation and desaturation, thus breaking down some fats ordained for reproduction and orchestrating a lipid profile conducive for somatic maintenance and longevity

Structure-oriented prediction in complex networks

Complex systems are extremely hard to predict due to its highly nonlinear interactions and rich emergent properties. Thanks to the rapid development of network science, our understanding of the structure of real complex systems and the dynamics on them has been remarkably deepened, which meanwhile largely stimulates the growth of effective prediction approaches on these systems. In this article, we aim to review different network-related prediction problems, summarize and classify relevant prediction methods, analyze their advantages and disadvantages, and point out the forefront as well as critical challenges of the field

A benchmarked protein microarray-based platform for the identification of novel low-affinity extracellular protein interactions

Low-affinity extracellular protein interactions are critical for cellular recognition processes, but existing methods to detect them are limited in scale, making genome-wide interaction screens technically challenging. To address this, we report here the miniaturization of the AVEXIS (avidity-based extracellular interaction screen) assay by using protein microarray technology. To achieve this, we have developed protein tags and sample preparation methods that enable the parallel purification of hundreds of recombinant proteins expressed in mammalian cells. We benchmarked the protein microarray-based assay against a set of known quantified receptor–ligand pairs and show that it is sensitive enough to detect even very weak interactions that are typical of this class of interactions. The increase in scale enables interaction screening against a dilution series of immobilized proteins on the microarray enabling the observation of saturation binding behaviors to show interaction specificity and also the estimation of interaction affinities directly from the primary screen. These methodological improvements now permit screening for novel extracellular receptor–ligand interactions on a genome-wide scale