ABSTRACT
Understanding the transcriptional changes that are engaged in stress resilience may reveal novel antidepressant targets. Here we use gene co-expression analysis of RNA-sequencing data from brains of resilient mice to identify a gene network that is unique to resilience. Zfp189, which encodes a previously unstudied zinc finger protein, is the highest-ranked key driver gene in the network, and overexpression of Zfp189 in prefrontal cortical neurons preferentially activates this network and promotes behavioral resilience. The transcription factor CREB is a predicted upstream regulator of this network and binds to the Zfp189 promoter. To probe CREB-Zfp189 interactions, we employ CRISPR-mediated locus-specific transcriptional reprogramming to direct CREB or G9a (a repressive histone methyltransferase) to the Zfp189 promoter in prefrontal cortex neurons. Induction of Zfp189 with site-specific CREB is pro-resilient, whereas suppressing Zfp189 expression with G9a increases susceptibility. These findings reveal an essential role for Zfp189 and CREB-Zfp189 interactions in mediating a central transcriptional network of resilience.
Subject(s)
Adaptation, Psychological/physiology , Stress, Psychological/genetics , Zinc Fingers/genetics , Animals , Gene Regulatory Networks/genetics , Mice , Mice, Inbred C57BL , Prefrontal Cortex/metabolism , Transcription, GeneticABSTRACT
A rotating machinery test rig was instrumented with fiber Fabry-Perot interferometer strain sensors for condition monitoring of rolling element bearings. Strain variations produced by ball passes were observed and analyzed in the time and frequency domain. Wavelength division multiplexing was utilized to simultaneously monitor the sensors with analog and digital readout systems--analog for high bandwidth and digital for high dynamic range and the monitoring of multiple sensors. The effects of imbalance on the shaft, changes in rotational speed, effects on the rotor system, and detection of bearing defects were investigated. Frequency peaks observed in the bearing sensor spectra closely matched predicted values. Imbalance and rotational speed tests showed good agreement with expected trends, and bearing defects were successfully detected.
