Non-Coding RNA

28 pages, 2482 KiB

Open AccessFeature PaperReview

Understanding Long Noncoding RNA and Chromatin Interactions: What We Know So Far

by Kankadeb Mishra and Chandrasekhar Kanduri

Non-Coding RNA 2019, 5(4), 54; https://doi.org/10.3390/ncrna5040054 - 3 Dec 2019

Cited by 79 | Viewed by 9039

With the evolution of technologies that deal with global detection of RNAs to probing of lncRNA-chromatin interactions and lncRNA-chromatin structure regulation, we have been updated with a comprehensive repertoire of chromatin interacting lncRNAs, their genome-wide chromatin binding regions and mode of action. Evidence [...] Read more.

With the evolution of technologies that deal with global detection of RNAs to probing of lncRNA-chromatin interactions and lncRNA-chromatin structure regulation, we have been updated with a comprehensive repertoire of chromatin interacting lncRNAs, their genome-wide chromatin binding regions and mode of action. Evidence from these new technologies emphasize that chromatin targeting of lncRNAs is a prominent mechanism and that these chromatin targeted lncRNAs exert their functionality by fine tuning chromatin architecture resulting in an altered transcriptional readout. Currently, there are no unifying principles that define chromatin association of lncRNAs, however, evidence from a few chromatin-associated lncRNAs show presence of a short common sequence for chromatin targeting. In this article, we review how technological advancements contributed in characterizing chromatin associated lncRNAs, and discuss the potential mechanisms by which chromatin associated lncRNAs execute their functions. Full article

(This article belongs to the Special Issue Non-Coding RNA and Intracellular Structures)

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Figure 1

Figure 1
Timeline of technological advances to study RNA-Protein and RNA-Chromatin interactions. Upper panel (light sea-green box) depicts in chronological order the prominent methods (in blue) to detect RNA interactions with chromatin. Examples of some of the functionally validated lncRNAs from each of these studies are shown (in black) below the corresponding method. Middle panel depicts the year in which these methodologies were published. Lower panel (light pink box) likewise shows in chronological order methods (in green) to identify RNA interactions with proteins. Full article ">Figure 2
Mechanisms of chromatin targeting of lncRNAs.Three broad mechanisms that explain both cis and trans acting lncRNAs targeting to the chromatin. (A–E) depicts possible mechanisms by which lncRNAs associate with chromatin through interacting with chromatin modifiers, chromatin readers and/or RNA binding proteins. LncRNAs that interact with proteins with dual RNA-DNA binding properties can bind to chromatin enriched with active (A) or inactive histone modifications (E), or interacts with RNA binding subunit of a heterocomplex chromatin modifiers (B), or lncRNAs can directly be targeted (triplex or R-loop) to chromatin as a complex with any RBP (C) or histone modification readers can recruit RBP bound lncRNAs that can subsequently interact with chromatin via histone modifications (D). Inactive chromatin associated lncRNAs (iCARs) can be recruited to chromatin by a single (E) or heterocomplex chromatin modifiers (not shown) with histone reading as well as modifying functions and such recruitments leads to spreading of inactive chromatin through repressive histone marks. (F–G) Triplex and R-loop forming lncRNAs can target chromatin in cis vs. trans (F–I). There might be a same (F) or different (G) group of protein complexes that might play a role in either stabilizing triplex formation by cis (F) or trans-acting (G) lncRNAs via binding to triplex forming oligos (TFOs). Similarly, R-loop formation might be coordinated by different protein complexes in cis (H) as compared to (if any) in-trans targeting (I). Full article ">Figure 3
Mechanism of in-cis chromatin targeting. Proposed model elucidating three different mechanisms of in-cis chromatin targeting of some of the well characterized lncRNAs. (A) Xist lncRNA upon transcription from the X-chromosome (red bar depicts the promoter) that is due to be inactivated, interacts with YY1 protein. YY1, being bifunctional RNA-DNA interacting protein, binds to YY1 binding sites (green bar) downstream of Xist promoter thereby retaining the newly transcribed Xist in cis. hnRNPU is another bifunctional protein, which can interact with both chromatin and RNA, binds at the 5′ end of Xist and targets it to chromatin. Nucleated Xist lncRNA then spreads along the entire X-chromosome using the three-dimensional folding of the chromatin with the aid of other transcriptional repressor complexes such as SHARP and PRC2. (B) Kcnq1ot1 lncRNA is exclusively transcribed (arrows depicting transcription) from an unmethylated paternal ICR (imprinted control region) (sky blue box), located within the intron 10 of its sense partner gene Kcnq1 gene. It functions in-cis to repress (blunted arrows represent transcriptional repression) lineage specific imprinted genes. Kcnq1ot1 (light green) interacts with and recruits G9a-PRC1-PRC2 complex to the promoters of placental linage genes (Blue boxes), while it additionally interacts with DNMT1 and targets G9a-PRC1-PRC2/DNMT1 complex to the promoters of genes that are silenced in all tissues in lineage independent fashion (Red boxes). The targeting and spreading to specific promoters across 1 mega-base region, unlike the whole X-chromosome spreading by Xist, is mediated by the three-dimensional folding of the chromatin. (C) Active XH lncCARs exemplify the case of in-cis targeting of lncRNAs to specific promoter regions of neighbouring protein coding genes to maintain their transcriptional activation. In the model, either the XH lncCARs first binds to WDR5-methyl transferase complex through the RNA binding pocket of WDR5 and then targeted (dashed black arrows) to chromatin at H3K4me2 (WDR5 reads H3K4me2), or they can directly bind H3K4me2 enriched chromatin (dashed red arrows) and act as a scaffold for the efficient docking of WDR5-methyl transferase complex which is necessary to maintain H3K4me2 levels and catalyse the conversion of H3K4me2 to H3K4me3. The maintenance of H3K4me2 marks is possibly mediated by a different WDR5- methyl transferase complex that is independent of the role of XH lncCARs. Full article ">

17 pages, 1898 KiB

Open AccessReview

MiR-205 Dysregulations in Breast Cancer: The Complexity and Opportunities

by Yajuan Xiao, Brock Humphries, Chengfeng Yang and Zhishan Wang

Non-Coding RNA 2019, 5(4), 53; https://doi.org/10.3390/ncrna5040053 - 19 Nov 2019

Cited by 64 | Viewed by 5854

Abstract

MicroRNAs (miRNAs) are endogenous non-coding small RNAs that downregulate target gene expression by imperfect base-pairing with the 3′ untranslated regions (3′UTRs) of target gene mRNAs. MiRNAs play important roles in regulating cancer cell proliferation, stemness maintenance, tumorigenesis, cancer metastasis, and cancer therapeutic resistance. [...] Read more.

MicroRNAs (miRNAs) are endogenous non-coding small RNAs that downregulate target gene expression by imperfect base-pairing with the 3′ untranslated regions (3′UTRs) of target gene mRNAs. MiRNAs play important roles in regulating cancer cell proliferation, stemness maintenance, tumorigenesis, cancer metastasis, and cancer therapeutic resistance. While studies have shown that dysregulation of miRNA-205-5p (miR-205) expression is controversial in different types of human cancers, it is generally observed that miR-205-5p expression level is downregulated in breast cancer and that miR-205-5p exhibits a tumor suppressive function in breast cancer. This review focuses on the role of miR-205-5p dysregulation in different subtypes of breast cancer, with discussions on the effects of miR-205-5p on breast cancer cell proliferation, epithelial–mesenchymal transition (EMT), metastasis, stemness and therapy-resistance, as well as genetic and epigenetic mechanisms that regulate miR-205-5p expression in breast cancer. In addition, the potential diagnostic and therapeutic value of miR-205-5p in breast cancer is also discussed. A comprehensive list of validated miR-205-5p direct targets is presented. It is concluded that miR-205-5p is an important tumor suppressive miRNA capable of inhibiting the growth and metastasis of human breast cancer, especially triple negative breast cancer. MiR-205-5p might be both a potential diagnostic biomarker and a therapeutic target for metastatic breast cancer. Full article

(This article belongs to the Special Issue Non-Coding RNAs as Therapeutic Targets)

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Figure 1
The miR-205 location on chromosome and sequence. MiR-205 locates on human chromosome 1q32.2. The seed sequences of miR-205-5p and miR-205-3p are underlined. The miR-205 discussed in this review refers to miR-205-5p. Full article ">Figure 2
The distinct roles of miR-205-5p in different types of cancers. Red arrows represent the facilitating effects of miR-205-5p and blue arrows represent the suppressive effects of miR-205-5p. The graph shows opposite roles of miR-205-5p in tumor proliferation, epithelial–mesenchymal transition (EMT), and metastasis among different types of cancers. MiR-205-5p exerts promoting effects in cancers listed in red boxes and exerts suppressive effects in cancers listed in blue boxes. Full article ">Figure 3
Differential expression levels of miR-205 among breast cancer subtypes. The expression of miR-205-5p is lower in HER2+ than luminal A/B, and triple negative breast cancer (TNBC) has the lowest miR-205-5p level compared with the other subtypes. Decreasing miR-205-5p expression level is associated with enhanced metastatic capability and worsening of patient survival. Full article ">Figure 4
A summary of miR-205-5p expression regulation and direct targets of miR-205-5p and their biological effects. Overexpression of ERBB2 promotes methylation of the miR-205-5p promoter via the Ras/Raf/MEK/ERK pathway which upregulates DNMTs, which finally results in miR-205-5p downregulation. TP53 and HES also inhibit miR-205-5p expression. MiR-205-5p targets different genes directly to regulate cell proliferation, tumor metastasis, stemness, and therapeutic resistance. Full article ">

15 pages, 1666 KiB

Open AccessFeature PaperReview

Assembly and Function of Gonad-Specific Non-Membranous Organelles in Drosophila piRNA Biogenesis

by Shigeki Hirakata and Mikiko C. Siomi

Non-Coding RNA 2019, 5(4), 52; https://doi.org/10.3390/ncrna5040052 - 6 Nov 2019

Cited by 9 | Viewed by 7233

Abstract

PIWI-interacting RNAs (piRNAs) are small non-coding RNAs that repress transposons in animal germlines. This protects the genome from the invasive DNA elements. piRNA pathway failures lead to DNA damage, gonadal development defects, and infertility. Thus, the piRNA pathway is indispensable for the continuation [...] Read more.

PIWI-interacting RNAs (piRNAs) are small non-coding RNAs that repress transposons in animal germlines. This protects the genome from the invasive DNA elements. piRNA pathway failures lead to DNA damage, gonadal development defects, and infertility. Thus, the piRNA pathway is indispensable for the continuation of animal life. piRNA-mediated transposon silencing occurs in both the nucleus and cytoplasm while piRNA biogenesis is a solely cytoplasmic event. piRNA production requires a number of proteins, the majority of which localize to non-membranous organelles that specifically appear in the gonads. Other piRNA factors are localized on outer mitochondrial membranes. In situ RNA hybridization experiments show that piRNA precursors are compartmentalized into other non-membranous organelles. In this review, we summarize recent findings about the function of these organelles in the Drosophila piRNA pathway by focusing on their assembly and function. Full article

(This article belongs to the Special Issue Non-Coding RNA and Intracellular Structures)

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Figure 1
Comparison of Drosophila ovarian piRNA pathways in somatic cells and germ cells. (a) Comparison of PIWI proteins, silencing mechanisms, and piRNA clusters. Sole PIWI protein expressed in somatic cells, Piwi, is imported to nuclei once loaded with piRNA and represses transposon co-transcriptionally. In somatic cells, piRNA precursors are transcribed from uni-strand clusters, which are transcribed uni-directionally and produce transcripts harboring fragments of transposons in reverse orientation. In germ cells, Aub and Ago3 are expressed in addition to Piwi. Aub and Ago3 stay in the cytoplasm and cleave target transcripts using Slicer activities. piRNAs in germ cells are derived from both uni-strand and dual-strand clusters. Dual-strand clusters are transcribed from both strands of DNA, and transposon fragments are inserted in random orientations. (b) Comparison of piRNA biogenesis pathways. In somatic cells, dominant piRNA precursors, flamenco/COM (flam) transcripts, are selected and initially cleaved in Yb bodies, soma-specific perinuclear granules surrounded by mitochondria. Continuous cleavages of intermediate RNA on the outer membrane of mitochondria produce mature ‘phased’ piRNAs. In germ cells, reciprocal cleavage of target transcripts by Aub and Ago3 produce Ago3-bound and Aub-bound piRNAs, respectively. This cycle is called the ping-pong cycle. Through the ping-pong cycle, transposon transcripts (light blue) are cleaved and piRNAs are amplified. Cleavage of targets and loading of cleaved fragments onto PIWI proteins during the cycle occurs in germ-specific perinuclear granules called nuage. Maturation of Ago3-loaded piRNAs through trimming presumably occurs on the outer membrane of mitochondria. Loading of antisense RNA (magenta) on Aub triggers phased piRNA biogenesis on the mitochondrial outer membrane. Full article ">Figure 2
piRNA biogenesis pathway in Drosophila ovarian somatic cells. Transcripts of flam (magenta) generate Dot COM in the nucleus and are translocated to nuclear periphery in a manner dependent on Exon Junction Complex (EJC) and UAP56. Dot COM is exported to the cytoplasm by the Nxf1-Nxt1/p15 complex. In the cytoplasm, flam transcripts are processed into piRNA intermediates in Yb bodies. Yb and flam require each other for granularization in the cytoplasm. The Armi-Piwi-piRNA intermediate complex moves to the surface of the mitochondrial outer membrane, where phased piRNAs are produced in mature lengths by endoribonuclease Zuc. After Hen1-mediated 2′-O-methylations at the piRNA 3′ ends, piRISCs are imported into the nucleus, where they co-transcriptionally repress their targets. Some mRNAs (violet) are also processed into piRNA intermediates in the cytosol at low efficiency and generate genic piRNAs through phasing on mitochondria. The targets and functions of genic piRNAs are vague. Full article ">

12 pages, 5664 KiB

Open AccessFeature PaperArticle

Small RNA Species and microRNA Profiles are Altered in Severe Asthma Nanovesicles from Broncho Alveolar Lavage and Associate with Impaired Lung Function and Inflammation

by Ana S. Francisco-Garcia, Eva M. Garrido-Martín, Hitasha Rupani, Laurie C. K. Lau, Rocio T. Martinez-Nunez, Peter H. Howarth and Tilman Sanchez-Elsner

Non-Coding RNA 2019, 5(4), 51; https://doi.org/10.3390/ncrna5040051 - 2 Nov 2019

Cited by 25 | Viewed by 4788

Abstract

MicroRNAs are known to regulate important pathways in asthma pathology including the IL-6 and IFN pathways. MicroRNAs have been found not only within cells but also within extracellular vesicles such as exosomes. In this study, we particularly focused on microRNA cargo of nanovesicles [...] Read more.

MicroRNAs are known to regulate important pathways in asthma pathology including the IL-6 and IFN pathways. MicroRNAs have been found not only within cells but also within extracellular vesicles such as exosomes. In this study, we particularly focused on microRNA cargo of nanovesicles in bronchoalveolar lavage of severe asthmatic patients. We extracted nanovesicle RNA using a serial filtration method. RNA content was analyzed with small RNA sequencing and mapped to pathways affected using WebGestalt 2017 Software. We report that severe asthma patients have deficient loading of microRNAs into their airway luminal nanovesicles and an altered profile of small RNA nanovesicle content (i.e., ribosomal RNA and broken transcripts, etc.). This decrease in microRNA cargo is predicted to increase the expression of genes by promoting inflammation and remodeling. Consistently, a network of microRNAs was associated with decreased FEV₁ and increased eosinophilic and neutrophilic inflammation in severe asthma. MicroRNAs in airway nanovesicles may, thus, be valid biomarkers to define abnormal biological disease processes in severe asthma and monitor the impact of interventional therapies. Full article

(This article belongs to the Special Issue Non-Coding RNA and the Immune System)

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Figure 1
Small RNA species other than microRNA are increased in SA nanovesicles. (A). Proportion of RNA species present in BALF nanovesicles of SA and HC. (B). Ratio of microRNA cargo in nanovesicles compared to total RNA cargo (* p < 0.05). Statistics (p value and FDR) according to NIA Array analysis software (p ≤ 0.05). Full article ">Figure 2
MicroRNA cargo reduced in nanovesicles from severe asthma BALF. (A). Heatmap showing unsupervised clustering of SA (n = 12) and HC (n = 8) (B). Comparative levels of microRNAs in nanovesicles according to fold expression (SA/HC). Statistics (p value and FDR) according to NIA Array analysis software (p ≤ 0.05). SA: Severe asthma. HC: Healthy control. BALF: Bronchoalveolar lavage fluid. FDR: False discovery rate. Full article ">Figure 2 Cont.
MicroRNA cargo reduced in nanovesicles from severe asthma BALF. (A). Heatmap showing unsupervised clustering of SA (n = 12) and HC (n = 8) (B). Comparative levels of microRNAs in nanovesicles according to fold expression (SA/HC). Statistics (p value and FDR) according to NIA Array analysis software (p ≤ 0.05). SA: Severe asthma. HC: Healthy control. BALF: Bronchoalveolar lavage fluid. FDR: False discovery rate. Full article ">Figure 3
MicroRNAs downregulated in severe asthma correlate to FEV1 and immune inflammation. MicroRNAs with SA/HC ratio < 0.33 (p ≤ 0.01, FDR ≤ 0.15) in nanovesicles from SA were correlated (Spearman’s rank) with FEV1 (green), eosinophilic inflammation (orange), or neutrophilic inflammation (blue). Influence of atopy (yellow) on microRNAs significantly correlated to FEV1, eosinophilic inflammation, or neutrophilic inflammation, which were calculated using the Mann-Whitney test (p ≤ 0.05). Full article ">Figure 4
Networks of miRNA target key molecular and cellular pathways related to asthma pathology. Biological pathways were predicted by Ingenuity Pathway Analysis (raw p value less than 0.010) to be affected by microRNAs associated with FEV1 ((A), hsa-mir-151a-5p, hsa-mir-202-3p, hsa-mir-202-5p, hsa-mir-568, hsa-mir-625-3p), neutrophilic inflammation ((B), hsa-mir-224-5p, hsa-mir-151a-5p, hsa-mir-581), and eosinophilic inflammation ((C), hsa-mir-10b-5p, hsa-mir-151a-3p, and hsa-mir-615-3p). Full article ">

14 pages, 1191 KiB

Open AccessFeature PaperReview

Evidence for and against Liquid-Liquid Phase Separation in the Nucleus

by Peng A and Stephanie C. Weber

Non-Coding RNA 2019, 5(4), 50; https://doi.org/10.3390/ncrna5040050 - 1 Nov 2019

Cited by 119 | Viewed by 14646

Abstract

Enclosed by two membranes, the nucleus itself is comprised of various membraneless compartments, including nuclear bodies and chromatin domains. These compartments play an important though still poorly understood role in gene regulation. Significant progress has been made in characterizing the dynamic behavior of [...] Read more.

Enclosed by two membranes, the nucleus itself is comprised of various membraneless compartments, including nuclear bodies and chromatin domains. These compartments play an important though still poorly understood role in gene regulation. Significant progress has been made in characterizing the dynamic behavior of nuclear compartments and liquid-liquid phase separation (LLPS) has emerged as a prominent mechanism governing their assembly. However, recent work reveals that certain nuclear structures violate key predictions of LLPS, suggesting that alternative mechanisms likely contribute to nuclear organization. Here, we review the evidence for and against LLPS for several nuclear compartments and discuss experimental strategies to identify the mechanism(s) underlying their assembly. We propose that LLPS, together with multiple modes of protein-nucleic acid binding, drive spatiotemporal organization of the nucleus and facilitate functional diversity among nuclear compartments. Full article

(This article belongs to the Special Issue Non-Coding RNA and Intracellular Structures)

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Figure 1
Membraneless compartments can form through at least three distinct mechanisms: (A) binding, (B) bridging, or (C) liquid-liquid phase separation. Full article ">Figure 2
The nucleus contains many different membraneless structures, including the nucleolus (orange), constitutive heterochromatin compartments (yellow), paraspeckles (green) and transcriptional condensates (blue), which have all been proposed to assemble through liquid-liquid phase separation (LLPS). Replication compartments (purple) form following infection by herpes simplex virus. Full article ">Figure 3
Concentration dependence and diffusion across boundary represent useful criteria for distinguishing among various mechanisms for nuclear compartmentalization. (A) Each model predicts a distinct relationship between compartment size and component concentration. (B) LLPS can buffer the nucleoplasmic concentration, while binding and bridging mechanisms cannot. (C) Inert probes freely diffuse through compartments formed by binding or bridging, but their mobility is hindered by the phase boundary. (D) Component molecules move similarly to inert probes except when bound to the polymer scaffold. (E) Despite their spherical shape and molecular dynamics, replication compartments and paraspeckles are not consistent with LLPS. Images are reprinted from refs. [<a href="#B33-ncrna-05-00050" class="html-bibr">33</a>,<a href="#B40-ncrna-05-00050" class="html-bibr">40</a>,<a href="#B61-ncrna-05-00050" class="html-bibr">61</a>] under the Creative Commons license: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>. Full article ">

6 pages, 557 KiB

Open AccessCommentary

Accurate Adapter Information Is Crucial for Reproducibility and Reusability in Small RNA Seq Studies

by Xiangfu Zhong, Fatima Heinicke, Benedicte A. Lie and Simon Rayner

Non-Coding RNA 2019, 5(4), 49; https://doi.org/10.3390/ncrna5040049 - 28 Oct 2019

Cited by 6 | Viewed by 5340

Abstract

A necessary pre-processing data analysis step is the removal of adapter sequences from the raw reads. While most adapter trimming tools require adapter sequence as an essential input, adapter information is often incomplete or missing. This can impact quantification of features, reproducibility of [...] Read more.

A necessary pre-processing data analysis step is the removal of adapter sequences from the raw reads. While most adapter trimming tools require adapter sequence as an essential input, adapter information is often incomplete or missing. This can impact quantification of features, reproducibility of the study and might even lead to erroneous conclusions. Here, we provide examples to highlight the importance of specifying the adapter sequence by demonstrating the effect of using similar but different adapter sequences and identify additional potential sources of errors in the adapter trimming step. Finally, we propose solutions by which users can ensure their small RNA-seq data is fully annotated with adapter information. Full article

(This article belongs to the Section Small Non-Coding RNA)

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Figure 1
Use of incorrect adapter sequence or trimming protocol can lead to incorrectly trimmed reads and miscounting of reads mapping to features. The selected datasets are originally from [<a href="#B15-ncrna-05-00049" class="html-bibr">15</a>], samples containing six synthetic small RNAs prepared by the NEBNext and CATS kits. After trimming, the Linux command grep -c was used for counting. (A) Top part of figure: Schematic of the different but highly similar adapter sequences used in (B–D). Bottom section of figure: Different versions of the CATS manual used for trimming protocol applied in (D). Legend under (A) Fill colour corresponds to the six synthetic RNAs in the dataset, line colour corresponds to the two replicates for each sample. Sequence for oligonucleotides are listed in <a href="#app1-ncrna-05-00049" class="html-app">Supplementary Table S5</a>. (B) Choice of adapter sequence can have a major impact on downstream analysis. Left: Use of the correct adapter sequence (NEBNext_trim01) identifies the presence of 5 out of 6 synthetic small RNAs present in the NGS dataset. Middle and right (NEBNext_trim02 and NEBNext_trim03): Using a highly similar adapter sequence that differs by one or two nucleotides has a drastic effect on mapped reads with less than 1% of reads identified. (C) In some case detailed trimming instructions are required in addition to the adapter sequence. The trimming sets CATS_trim01 and CATS_trim02 were trimmed by specifying the correct adapter sequence, but few perfectly trimmed reads were detected. (D) The problem extends to incorrect application of manufacturer’s protocol during read trimming. From left to right, trimming results after following trimming instructions specified in the January 2017, March 2017 and September 2017 releases of the manual. The instructions in the latest version are distinct from those provided in the previous two versions and this is reflected in the number of identified reads, with the latest protocol identifying notably fewer reads associated with the synthetic RNAs. CATS_trim01 was trimmed using the same adapter sequence as CATS_trim05, demonstrating that for some kits, specifying the adapter alone is not sufficient to achieve efficient read trimming. Full article ">

15 pages, 9755 KiB

Open AccessArticle

Expression of Long Non-Coding RNAs by Human Retinal Müller Glial Cells Infected with Clonal and Exotic Virulent Toxoplasma gondii

by Elise Rochet, Binoy Appukuttan, Yuefang Ma, Liam M. Ashander and Justine R. Smith

Non-Coding RNA 2019, 5(4), 48; https://doi.org/10.3390/ncrna5040048 - 20 Sep 2019

Cited by 22 | Viewed by 5091

Abstract

Retinal infection with Toxoplasma gondii—ocular toxoplasmosis—is a common cause of vision impairment worldwide. Pathology combines parasite-induced retinal cell death and reactive intraocular inflammation. Müller glial cells, which represent the supporting cell population of the retina, are relatively susceptible to infection with T. [...] Read more.

Retinal infection with Toxoplasma gondii—ocular toxoplasmosis—is a common cause of vision impairment worldwide. Pathology combines parasite-induced retinal cell death and reactive intraocular inflammation. Müller glial cells, which represent the supporting cell population of the retina, are relatively susceptible to infection with T. gondii. We investigated expression of long non-coding RNAs (lncRNAs) with immunologic regulatory activity in Müller cells infected with virulent T. gondii strains—GT1 (haplogroup 1, type I) and GPHT (haplogroup 6). We first confirmed expression of 33 lncRNA in primary cell isolates. MIO-M1 human retinal Müller cell monolayers were infected with T. gondii tachyzoites (multiplicity of infection = 5) and harvested at 4, 12, 24, and 36 h post-infection, with infection being tracked by the expression of parasite surface antigen 1 (SAG1). Significant fold-changes were observed for 31 lncRNAs at one or more time intervals. Similar changes between strains were measured for BANCR, CYTOR, FOXD3-AS1, GAS5, GSTT1-AS1, LINC-ROR, LUCAT1, MALAT1, MIR22HG, MIR143HG, PVT1, RMRP, SNHG15, and SOCS2-AS1. Changes differing between strains were measured for APTR, FIRRE, HOTAIR, HOXD-AS1, KCNQ1OT1, LINC00968, LINC01105, lnc-SGK1, MEG3, MHRT, MIAT, MIR17HG, MIR155HG, NEAT1, NeST, NRON, and PACER. Our findings suggest roles for lncRNAs in regulating retinal Müller cell immune responses to T. gondii, and encourage future studies on lncRNA as biomarkers and/or drug targets in ocular toxoplasmosis. Full article

(This article belongs to the Section Long Non-Coding RNA)

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Figure 1
Gel images showing Müller cell long non-coding RNAs and reference gene amplicons run on 2% or 3% agarose gel. L = DNA ladder, D1 = human donor cell isolate 1, D2 = human donor cell isolate 2, D3 = human donor cell isolate 3, M = MIO-M1 cell line. Expected product sizes: APTR = 300 bp, BANCR = 80 bp, CDKN2B-AS1 = 169 bp, CYTOR = 187 bp, FIRRE = 215 bp, FOXD3-AS1 = 118 bp, GAS5 = 127 bp, GSTT1-AS1 = 105 bp, HOTAIR = 168 bp, HOXD-AS1 = 149 bp, KCNQ1OT1 = 567 bp, LINC00968 = 126 bp, LINC01105 = 137 bp, LINC-ROR = 151 bp, Lnc-SGK1 = 131 bp, LUCAT1 = 114 bp, MALAT1 = 396 bp, MEG3 = 187 bp, MHRT = 73 bp, MIAT = 122 bp, MIR17HG = 221 bp, MIR22HG = 136/219 bp, MIR143HG = 128 bp, MIR155HG = 247 bp, NEAT1 = 137 bp, NeST = 94 bp, NRON = 133 bp, PACER = 90 bp, PURPL = 120 bp, PVT1 = 179 bp, RMRP = 67 bp, SNHG15 = 155 bp, SOCS2-AS1 = 83 bp, PPIA = 355 bp, RPLP0 = 235 bp. Multiple bands on same gel (FOXD3-AS1, GSTT1-AS1, MIR22HG, PVT1, and SNHG15) represent transcript variants, which were confirmed by sequencing. Bands at lower edge of gels represent primer dimer products. Controls prepared with no template did not amplify. Full article ">Figure 2
Expression of surface antigen 1 (SAG1) in human retinal Müller cells infected with T. gondii tachyzoites. Graph shows normalized SAG1 transcript expression in uninfected versus GT-1 and GPHT strain-infected MIO-M1 cells (multiplicity of infection = 5; evaluated time points post-infection = 4, 12, 24, and 36 h). Reference genes were ribosomal protein lateral stalk subunit P0 (RPLP0) and peptidylprolyl isomerase A (PPIA). n = 3 cultures/condition. Bars represent mean normalized expression, and error bars indicate standard deviation. Black columns represent GT1 strain-infected, and grey columns represent GPHT strain-infected. Full article ">Figure 3
Expression of long non-coding RNAs in human retinal Müller cells infected with T. gondii tachyzoites with similarity in response to parasite strains. Graphs show normalized lncRNA expression in uninfected versus GT-1 and GPHT strain-infected MIO-M1 cells (multiplicity of infection = 5; evaluated time points post-infection = 4, 12, 24, and 36 h). Reference genes were ribosomal protein lateral stalk subunit P0 (RPLP0) and peptidylprolyl isomerase A (PPIA). Data were analyzed by two-way ANOVA with Bonferroni post-test. n = 3 cultures/condition. Bars represent mean normalized expression, and error bars indicate standard deviation. White columns represent uninfected, black columns represent GT1 strain-infected, and grey columns represent GPHT strain-infected. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Full article ">Figure 4
Expression of long non-coding RNAs in human retinal Müller cells infected with T. gondii tachyzoites with differences in response to parasite strains. Graphs show normalized lncRNA expression in uninfected versus GT-1 and GPHT strain-infected MIO-M1 cells (multiplicity of infection = 5; evaluated time points post-infection = 4, 12, 24, and 36 h). Reference genes were ribosomal protein lateral stalk subunit P0 (RPLP0) and peptidylprolyl isomerase A (PPIA). Data were analyzed by two-way ANOVA with Bonferroni post-test. n = 3 cultures/condition. Bars represent mean normalized expression, and error bars indicate standard deviation. White columns represent uninfected, black columns represent GT1 strain-infected, and grey columns represent GPHT strain-infected. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Full article ">Figure 5
Photomicrographs of Müller cells isolated from human retinae and phenotyped by immunocytochemistry for cellular retinaldehyde binding protein (CRALBP), glutamine synthetase (GS), vimentin, and glial fibrillary acidic protein (GFAP), with negative control labelled with species-matched primary antibody (IgG). Cells stained positively for CRALBP, GS, vimentin, and GFAP; staining artefacts were visible in the negative control, but the labelling pattern was clearly different. Alexa Fluor 488 (green) or Alexa Fluor 594 (red) with DAPI nuclear counterstain (blue). Original magnification: 200×. Full article ">

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Non-Coding RNA, Volume 5, Issue 4 (December 2019) – 7 articles

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