Murine Falcor/LL35 lncRNA Contributes to Glucose and Lipid Metabolism In Vitro and In Vivo.

Glucose and lipid metabolism are crucial functional systems in eukaryotes. A large number of experimental studies both in animal models and humans have shown that long non-coding RNAs (lncRNAs) play an important role in glucose and lipid metabolism. Previously, human lncRNA DEANR1/linc00261 was described as a tumor suppressor that regulates a variety of biological processes such as cell proliferation, apoptosis, glucose metabolism and tumorigenesis. Here we report that murine lncRNA Falcor/LL35, a proposed functional analog of human DEANR1/linc00261, is predominantly expressed in murine normal hepatocytes and downregulated in HCC and after partial hepatectomy. The application of high-throughput approaches such as RNA-seq, LC-MS proteomics, lipidomics and metabolomics analysis allowed changes to be found in the transcriptome, proteome, lipidome and metabolome of hepatocytes after LL35 depletion. We revealed that LL35 is involved in the regulation of glycolysis and lipid biosynthesis in vitro and in vivo. Moreover, LL35 affects Notch and NF-κB signaling pathways in normal hepatocytes. All observed changes result in the decrease in the proliferation and migration of hepatocytes. We demonstrated similar phenotype changes between murine LL35 and human linc00261 depletion in vitro and in vivo that opens the opportunity to translate results for LL35 from a liver murine model to possible functions of human lncRNA linc00261.

Long-Term Fluoxetine Administration Causes Substantial Lipidome Alteration of the Juvenile Macaque Brain.

Fluoxetine is an antidepressant commonly prescribed not only to adults but also to children for the treatment of depression, obsessive-compulsive disorder, and neurodevelopmental disorders. The adverse effects of the long-term treatment reported in some patients, especially in younger individuals, call for a detailed investigation of molecular alterations induced by fluoxetine treatment. Two-year fluoxetine administration to juvenile macaques revealed effects on impulsivity, sleep, social interaction, and peripheral metabolites. Here, we built upon this work by assessing residual effects of fluoxetine administration on the expression of genes and abundance of lipids and polar metabolites in the prelimbic cortex of 10 treated and 11 control macaques representing two monoamine oxidase A (MAOA) genotypes. Analysis of 8871 mRNA transcripts, 3608 lipids, and 1829 polar metabolites revealed substantial alterations of the brain lipid content, including significant abundance changes of 106 lipid features, accompanied by subtle changes in gene expression. Lipid alterations in the drug-treated animals were most evident for polyunsaturated fatty acids (PUFAs). A decrease in PUFAs levels was observed in all quantified lipid classes excluding sphingolipids, which do not usually contain PUFAs, suggesting systemic changes in fatty acid metabolism. Furthermore, the residual effect of the drug on lipid abundances was more pronounced in macaques carrying the MAOA-L genotype, mirroring reported behavioral effects of the treatment. We speculate that a decrease in PUFAs may be associated with adverse effects in depressive patients and could potentially account for the variation in individual response to fluoxetine in young people.

HypercubeME: two hundred million combinatorially complete datasets from a single experiment.

MOTIVATION: Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a "combinatorially complete dataset". So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. RESULTS: We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199,847,053 unique combinatorially complete genotype combinations of dimensionality ranging from two to twelve. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data. AVAILABILITY: https://github.com/ivankovlab/HypercubeME.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.