Short-lived long non-coding RNAs as surrogate indicators for chemical exposure and LINC00152 and MALAT1 modulate their neighboring genes

<div><p>Whole transcriptome analyses have revealed a large number of novel long non-coding RNAs (lncRNAs). Although accumulating evidence demonstrates that lncRNAs play important roles in regulating gene expression, the detailed mechanisms of action of most lncRNAs remain unclear. We previously reported that a novel class of lncRNAs with a short half-life (<i>t</i>_1/2 < 4 h) in HeLa cells, termed short-lived non-coding transcripts (SLiTs), are closely associated with physiological and pathological functions. In this study, we focused on 26 SLiTs and nuclear-enriched abundant lncRNA, MALAT1(<i>t</i>_1/2 of 7.6 h in HeLa cells) in neural stem cells (NSCs) derived from human induced pluripotent stem cells, and identified four SLiTs (TUG1, GAS5, FAM222-AS1, and SNHG15) that were affected by the following typical chemical stresses (oxidative stress, heavy metal stress and protein synthesis stress). We also found the expression levels of LINC00152 (<i>t</i>_1/2 of 2.1 h in NSCs), MALAT1 (<i>t</i>_1/2 of 1.8 h in NSCs), and their neighboring genes were elevated proportionally to the chemical doses. Moreover, we confirmed that the overexpression of LINC00152 or MALAT1 upregulated the expressions of their neighboring genes even in the absence of chemical stress. These results reveal that LINC00152 and MALAT1 modulate their neighboring genes, and thus provide a deeper understanding of the functions of lncRNAs.</p></div

Alterations in LINC00152- and MALAT1-neighboring genes.

<p>Expression levels of LINC00152 (A) and MALAT1 (B) were determined by RT-qPCR. GAPDH, ACTB, HPRT1, and PGK1 were used for normalization. Values represent mean ± SD obtained from three independent experiments (*P < 0.05, Student’s t test).</p

Chemical stresses prolonged the decay rates of LINC00152 and MALAT1, but did not affect transcription rates.

<p>The transcription rates of (A) LINC00152 and (B) MALAT1 were determined in control cells (black bar) and chemical-stressed cells (gray bar). Nascent LINC00152 and MALAT1 were transcribed with the incorporation of EU. Relative EU-RNA quantity indicated the total amount of EU-labeled RNA captured was divided by the input RNA amount, and indicated the transcription rate. The decay rates of (A) LINC00152 and (B) MALAT1 were determined in control cells (solid circle and black bar) and in chemical-stressed cells (open circle and gray bar). Values represent mean ± SD obtained from three independent experiments (*P < 0.05, Student’s t test).</p

Alterations in mRNA and lncRNA expression levels in NSCs in response to four chemical stressors.

<p>NSCs were treated with (A) 100 μM hydrogen peroxide, (B) 100 μM mercury II chloride, (C) 100 μM cycloheximide, or (D) 100 μM zinc chloride for 24 h. Expression levels of the indicated RNAs were determined by RT-qPCR. GAPDH, ACTB, HPRT1, and PGK1 were used for normalization. Values represent mean ± SD obtained from four independent experiments. Y-axis indicated that the expression levels of treated-cells was divided by the those of untreated-cells. Thus, zero indicated the RNA not detectable and one indicated the there was no change in expression levels comparing the untreated-cells. Gray dotted lines indicated cut-off values. Values represent mean ± SD obtained from four independent experiments (*P < 0.05, Student’s t test) over cut-off values. (E) Venn diagram of up-regulated genes by four chemical stressors.</p

Immunostaining and RT-qPCR of neural stem cell (NSC) markers.

<p>(A) Fluorescence images were obtained using a human NSC immunocytochemistry kit (Life Technologies). Cells were immunostained for NESTIN (green; left) and SOX1 (green; right). BF indicated bright field and IF indicated immunofluorescence. (B) Expression levels of SOX1, POU5F1, and HPRT1 in iPSCs (black bar) and in NSCs (gray bar) were determined by RT-qPCR. GAPDH, ACTB, HPRT1, and PGK1 were used for normalization. Values represent mean ± SD obtained from three independent experiments (*P < 0.05, Student’s t test).</p

Identification of RNA biomarkers for chemical safety screening in mouse embryonic stem cells using RNA deep sequencing analysis

<div><p>Although it is not yet possible to replace in vivo animal testing completely, the need for a more efficient method for toxicity testing, such as an in vitro cell-based assay, has been widely acknowledged. Previous studies have focused on mRNAs as biomarkers; however, recent studies have revealed that non-coding RNAs (ncRNAs) are also efficient novel biomarkers for toxicity testing. Here, we used deep sequencing analysis (RNA-seq) to identify novel RNA biomarkers, including ncRNAs, that exhibited a substantial response to general chemical toxicity from nine chemicals, and to benzene toxicity specifically. The nine chemicals are listed in the Japan Pollutant Release and Transfer Register as class I designated chemical substances. We used undifferentiated mouse embryonic stem cells (mESCs) as a simplified cell-based toxicity assay. RNA-seq revealed that many mRNAs and ncRNAs responded substantially to the chemical compounds in mESCs. This finding indicates that ncRNAs can be used as novel RNA biomarkers for chemical safety screening.</p></div

Chemical structures used in the present study.

<p>Chemical structures used in the present study.</p

Genes downregulated in mouse embryonic stem cells exposed to benzene (Top 30).

<p>Genes downregulated in mouse embryonic stem cells exposed to benzene (Top 30).</p

Genes upregulated in mouse embryonic stem cells on general exposure to nine chemicals (Top 30).

<p>Genes upregulated in mouse embryonic stem cells on general exposure to nine chemicals (Top 30).</p

GO terms for genes upregulated in mouse embryonic stem cells exposed to benzene (Top 30).

<p>GO terms for genes upregulated in mouse embryonic stem cells exposed to benzene (Top 30).</p