Skip to main content
Premium Trial:

Request an Annual Quote

PNAS Papers on Transcription Factor Prediction, Yeast Metabolic Analysis, Insect Arousal

A team from Korea, the US, and Denmark describes a deep learning transcription factor prediction method called DeepTFactor. The strategy relies on "a convolutional neural network to extract features of a protein," the researchers write, adding that it uses deep learning to find eukaryotic or prokaryotic proteins with transcription factor activity. When they applied DeepTFactor to Escherichia coli, for example, they uncovered more than 300 candidate transcription factors, including dozens of candidate transcription factors encoded by E. coli genes without known functions and three potential transcription factors followed up on experimentally. "We provide DeepTFactor as a stand-alone program for researchers to analyze their own protein sequences of interest," the authors write. "It will serve as a useful tool for understanding the regulatory systems of organisms."

Yale University researchers report on findings from a simulation study of the phenotypic, genotypic, and gene expression contributors to the so-called Crabtree effect — a metabolic shift that maintains homeostasis in yeast cells moved from low-glucose environments to environments that are rich in glucose. "Overall, we conclude that, for the short-term adaptation over the lifetime of an organism and the long-term selection of adaptations over many generations, the metabolic phenotype plays a key role in early adaptation and in guiding subsequent short-term changes in gene expression and long-term genomic adaptations," they report. "Although our findings are specific to the Crabtree effect, they likely hold broadly because of the well-recognized similarities in glucose metabolism between different pathways and across kingdoms and phyla from yeast to humans."

Investigators at the University of Florida and Ohio State University describe roles for reactive oxygen species (ROS) and hypoxia signaling in periodic arousal regulations in an insect model, focusing on pupae from the flesh fly species Sarcophaga crassipalpis in diapause, a months-long process marked by metabolic suppression. Based on findings from their metabolite analyses, protein interaction experiments, and other assays, the authors speculate that "as metabolism falls from early to late depression ROS levels eventually reach a lower threshold that ultimately precipitates metabolic arousal." They note that "more work is needed to test the extent to which regulatory mechanisms for these characteristic shifts in substrate use are shared between diapausing insects and hibernating mammals."