Changing gears in Nrf1 research, from mechanisms of regulation to its role in disease and prevention.

The "cap'n'collar" bZIP transcription factor Nrf1 heterodimerizes with small Maf proteins to bind to the Antioxidant Response Element/Electrophile Response Element to transactivate antioxidant enzyme, phase 2 detoxification enzyme and proteasome subunit gene expression. Nrf1 specifically regulates pathways in lipid metabolism, amino acid metabolism, proteasomal degradation, the citric acid cycle, and the mitochondrial respiratory chain. Nrf1 is maintained in the endoplasmic reticulum (ER) in an inactive glycosylated state. Activation involves retrotranslocation from the ER lumen to the cytoplasm, deglycosylation and partial proteolytic processing to generate the active forms of Nrf1. Recent evidence has revealed how this factor is regulated and its involvement in various metabolic diseases. This review outlines Nrf1 structure, function, regulation and its links to insulin resistance, diabetes and inflammation. The glycosylation/deglycosylation of Nrf1 is controlled by glucose levels. Nrf1 glycosylation affects its control of glucose transport, glycolysis, gluconeogenesis and lipid metabolism.

Trimethylation Enhancement Using (13)C-Diazomethane ((13)C-TrEnDi): Increased Sensitivity and Selectivity of Phosphatidylethanolamine, Phosphatidylcholine, and Phosphatidylserine Lipids Derived from Complex Biological Samples.

Significant sensitivity enhancements in the tandem mass spectrometry-based analysis of complex mixtures of several phospholipid classes has been achieved via (13)C-TrEnDi. (13)C-TrEnDi-modified phosphatidylethanolamine (PE), phosphatidylserine (PS), and phosphatidylcholine (PC) lipids extracted from HeLa cells demonstrated greater sensitivity via precursor ion scans (PISs) than their unmodified counterparts. Sphingomyelin (SM) species exhibited neither an increased nor decreased sensitivity following modification. The use of isotopically labeled diazomethane enabled the distinction of modified PE and modified PC species that would yield isobaric species with unlabeled diazomethane. (13)C-TrEnDi created a PE-exclusive PIS of m/z 202.1, two PS-exclusive PISs of m/z 148.1 and m/z 261.1, and a PIS of m/z 199.1 for PC species (observed at odd m/z values) and SM species (observed at even m/z values). The standardized average area increase after TrEnDi modification was 10.72-fold for PE species, 2.36-fold for PC, and 1.05-fold for SM species. The sensitivity increase of PS species was not quantifiable, as there were no unmodified PS species identified prior to derivatization. (13)C-TrEnDi allowed for the identification of 4 PE and 7 PS species as well as the identification and quantitation of an additional 4 PE and 4 PS species that were below the limit of detection (LoD) prior to modification. (13)C-TrEnDi also pushed 24 PE and 6 PC lipids over the limit of quantitation (LoQ) that prior to modification were above the LoD only.

Transcriptome-Wide Off-Target Effects of Steric-Blocking Oligonucleotides.

Steric-blocking oligonucleotides (SBOs) are short, single-stranded nucleic acids designed to modulate gene expression by binding to RNA transcripts and blocking access from cellular machinery such as splicing factors. SBOs have the potential to bind to near-complementary sites in the transcriptome, causing off-target effects. In this study, we used RNA-seq to evaluate the off-target differential splicing events of 81 SBOs and differential expression events of 46 SBOs. Our results suggest that differential splicing events are predominantly hybridization driven, whereas differential expression events are more common and driven by other mechanisms (including spurious experimental variation). We further evaluated the performance of in silico screens for off-target splicing events, and found an edit distance cutoff of three to result in a sensitivity of 14% and false discovery rate (FDR) of 99%. A machine learning model incorporating splicing predictions substantially improved the ability to prioritize low edit distance hits, increasing sensitivity from 4% to 26% at a fixed FDR of 90%. Despite these large improvements in performance, this approach does not detect the majority of events at an FDR <99%. Our results suggest that in silico methods are currently of limited use for predicting the off-target effects of SBOs, and experimental screening by RNA-seq should be the preferred approach.

Large-scale investigation of oxygen response mutants in Saccharomyces cerevisiae.

A genome-wide screen of a yeast non-essential gene-deletion library was used to identify sick phenotypes due to oxygen deprivation. The screen provided a manageable list of 384 potentially novel as well as known oxygen responding (anoxia-survival) genes. The gene-deletion mutants were further assayed for sensitivity to ferrozine and cobalt to obtain a subset of 34 oxygen-responsive candidate genes including the known hypoxic gene activator, MGA2. With each mutant in this subset a plasmid based ß-galactosidase assay was performed using the anoxic-inducible promoter from OLE1 gene, and 17 gene deletions were identified that inhibit induction under anaerobic conditions. Genetic interaction analysis for one of these mutants, the RNase-encoding POP2 gene, revealed synthetic sick interactions with a number of genes involved in oxygen sensing and response. Knockdown experiments for CNOT8, human homolog of POP2, reduced cell survival under low oxygen condition suggesting a similar function in human cells.