Synergistic Regulation of Microglia Gene Expression by Natural Molecules in Herbal Medicine

The activated microglia contribute to stroke-induced neuroinflammation by upregulating the expression of a pleura of genes that are characterized as either proinflammatory or anti-inflammatory. The natural products alantolactone (Ala) and dehydrodiisoeugenol (Deh) found in Inula helenium L. and Myristica fragrans Houtt., respectively, are regularly used in traditional herb medicine, which play anti-inflammatory and antioxidant roles via regulation of canonical pathways such as nuclear factor kappa B (NF-κB) in microglia and microphages. To illustrate the full spectra of gene expression alteration in microglia treated with Ala, Deh, and the mixture of Ala and Deh (denoted as Mix), we performed RNA-seq analysis of total RNA extracted from lipopolysaccharide- (LPS-) treated microglia subsequently exposed to Ala, Deh, and Mix. While both chemicals regulated the gene expression that facilitates an anti-inflammatory polarization, the mixture exerted some distinctive synergic regulatory effect, which differed from either of the chemicals alone. Our data provide important evidence for further research on the therapeutic mechanism of traditional medicine including Eerdun Wurile (EW).

A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations

Background Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the intrinsic difficulty in dealing with the scarcity of data leads to the necessity to further improve the algorithms. In this work, we propose a novel method, employing a semi-supervised deep-learning model with pseudo labels, which takes advantage of learning from both experimentally annotated and unannotated data. Results We prepared known functional non-coding variants with histone marks, DNA accessibility, and sequence context in GM12878, HepG2, and K562 cell lines. Applying our method to the dataset demonstrated its outstanding performance, compared with that of existing tools. Our results also indicated that the semi-supervised model with pseudo labels achieves higher predictive performance than the supervised model without pseudo labels. Interestingly, a model trained with the data in a certain cell line is unlikely to succeed in other cell lines, which implies the cell-type-specific nature of the non-coding variants. Remarkably, we found that DNA accessibility significantly contributes to the functional consequence of variants, which suggests the importance of open chromatin conformation prior to establishing the interaction of non-coding variants with gene regulation. Conclusions The semi-supervised deep learning model coupled with pseudo labeling has advantages in studying with limited datasets, which is not unusual in biology. Our study provides an effective approach in finding non-coding mutations potentially associated with various biological phenomena, including human diseases.

Aging-dependent downregulation of SUV39H1 histone methyltransferase increases susceptibility to stress-induced depressive behavior

Aging induces cellular and molecular changes including gene expression alteration in the brain, which might be associated with aging-dependent increase in vulnerability to stress-induced depression. However, the underlying mechanism is not clearly understood. In the present study, we investigate how aging changes the ability to cope with stress and increases sensitivity to stress. Aged mice have decreased expression of SUV39H1 histone methyltransferase and increased expression of Mkp-1 in the hippocampus. The siRNA-mediated knockdown of SUV39H1 increases Mkp-1 expression and suppresses p-CREB and Bdnf expression in HT22 cells and in the hippocampus of mice. Chromatin immunoprecipitation assays indicate that the levels of SUV39H1 and methylated histone-H3 bound to the promoter of the Mkp-1 in the hippocampus are reduced in aged mice. Aged mice exhibit depression-like behavior following weak stress that does not induce depressive behavior in young mice. Rosmarinic acid, a phenolic compound that increases SUV39H1 expression, reverses stress-induced changes of SUV39H1, Mkp-1, and Bdnf expression in the hippocampus via an overlapping but distinct mechanism from those of fluoxetine and imipramine and produces anti-depressive effects. These results suggest that aging increases susceptibility to stress via downregulation of SUV39H1 and changes in SUV39H1-regulated signaling pathways in the hippocampus.

Hippocampal toxicity of metal base nanoparticles. Is there a relationship between nanoparticles and psychiatric disorders?

Metal base nanoparticles are widely produced all over the world and used in many fields and products such as medicine, electronics, cosmetics, paints, ceramics, toys, kitchen utensils and toothpastes. They are able to enter the body through digestive, respiratory, and alimentary systems. These nanoparticles can also cross the blood brain barrier, enter the brain and aggregate in the hippocampus. After entering the hippocampus, they induce oxidative stress, neuro-inflammation, mitochondrial dysfunction, and gene expression alteration in hippocampal cells, which finally lead to neuronal apoptosis. Metal base nanoparticles can also affect hippocampal neurogenesis and synaptic plasticity that both of them play crucial role in memory and learning. On the one hand, hippocampal cells are severely vulnerable due to their high metabolic activity, and on the other hand, metal base nanoparticles have high potential to damage hippocampus through variety of mechanisms and affect its functions. This review discusses, in detail, nanoparticles’ detrimental effects on the hippocampus in cellular, molecular and functional levels to reveal that according to the present information, which types of nanoparticles have more potential to induce hippocampal toxicity and psychiatric disorders and which types should be more evaluated in the future studies.

Correction to: New insights in gene expression alteration as effect of doxorubicin drug resistance in triple negative breast cancer cells

An amendment to this paper has been published and can be accessed via the original article.

Investigation of RNA metabolism through large-scale genetic interaction profiling in yeast

Gene deletion and gene expression alteration can lead to growth defects that are amplified or reduced when a second mutation is present in the same cells. We performed 154 genetic interaction mapping (GIM) screens with mutants related with RNA metabolism and measured growth rates of about 700 000 Saccharomyces cerevisiae double mutant strains. The screens used the gene deletion collection in addition to a set of 900 strains in which essential genes were affected by mRNA destabilization (DAmP). To analyze the results we developed RECAP, a strategy that validates genetic interaction profiles by comparison with gene co-citation frequency, and identified links between 1 471 genes and 117 biological processes. To validate specific results, we tested and confirmed a link between an inositol polyphosphate hydrolase complex and mRNA translation initiation. Altogether, the results and the newly developed analysis strategy should represent a useful resource for discovery of gene function in yeast.

GENES and In-Stent Restenosis: Review

The initiation of coronary stents is a vast landmark in the practice of interventional cardiology. The vascular injury sustained during the percutaneous coronary intervention (PCI) leads to a complicated inflammatory and repairing process. Therefore, stent restenosis arises. Diabetes mellitus is the highest-risk clinical predictor of ISR. Genetics has an important role in the development of ISR. There is a suggested association between the appearance of stent restenosis and certain genetic polymorphisms. Examples of these single nucleotide polymorphisms are endothelial nitric oxide synthase gene (eNOS), the angiotensin converting enzyme gene (ACE), the angiotensin II type 1 receptor gene (AT1R), TGF-β, and VEGF. CYP2C19 variants can help change the medical strategy to a more individualized therapeutic regimen either by altering the therapeutic dose depending on the genotype or using an alternative drug that does not worsen the patient’s case. However, eNOS polymorphism produces gene expression alteration leading to ISR following stent placement. In addition, the deletion-allele of the ACE genotype increases the risk of ISR; however, the I allele decreases the risk. Moreover, the D/I polymorphism is not an independent factor of ISR in patients administering ACE inhibitors or angiotensin receptor antagonists. Furthermore, studies on large sample sizes are required to decrease the harmful adverse effects of stent restenosis by detecting these allele gene polymorphisms.