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Diminished nuclear RNA decay upon Salmonella infection upregulates antibacterial noncoding RNA s

2018; Springer Nature; Volume: 37; Issue: 13 Linguagem: Inglês

10.15252/embj.201797723

1460-2075

Katsutoshi Imamura, Akiko Takaya, Yoichi Ishida, Yayoi Fukuoka, Toshiki Taya, Ryo Nakaki, Miho Kakeda, Naoto Imamachi, Aiko Sato, Toshimichi Yamada, Rena Onoguchi‐Mizutani, Gen Akizuki, Tanzina Tanu, Kazuyuki Tao, Sotaro Miyao, Yutaka Suzuki, Masami Nagahama, Tomoko Yamamoto, Torben Heick Jensen, Nobuyoshi Akimitsu,

RNA Research and Splicing

Article7 June 2018free access Source DataTransparent process Diminished nuclear RNA decay upon Salmonella infection upregulates antibacterial noncoding RNAs Katsutoshi Imamura Department of Microbiology and Molecular Genetics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark Search for more papers by this author Akiko Takaya Department of Microbiology and Molecular Genetics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan Search for more papers by this author Yo-ichi Ishida Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Yayoi Fukuoka Agilent Technologies Japan, Ltd., Tokyo, Japan Search for more papers by this author Toshiki Taya Agilent Technologies Japan, Ltd., Tokyo, Japan Search for more papers by this author Ryo Nakaki Rhelixa, Inc., Tokyo, Japan Search for more papers by this author Miho Kakeda Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Naoto Imamachi Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Aiko Sato Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Toshimichi Yamada Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Rena Onoguchi-Mizutani Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Gen Akizuki Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Tanzina Tanu Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Kazuyuki Tao Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Sotaro Miyao Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Yutaka Suzuki Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan Search for more papers by this author Masami Nagahama Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Tomoko Yamamoto Medical Mycology Research Center, Chiba University, Chiba, Japan Search for more papers by this author Torben Heick Jensen Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark Search for more papers by this author Nobuyoshi Akimitsu Corresponding Author [email protected] orcid.org/0000-0002-3190-2942 Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Katsutoshi Imamura Department of Microbiology and Molecular Genetics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark Search for more papers by this author Akiko Takaya Department of Microbiology and Molecular Genetics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan Search for more papers by this author Yo-ichi Ishida Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Yayoi Fukuoka Agilent Technologies Japan, Ltd., Tokyo, Japan Search for more papers by this author Toshiki Taya Agilent Technologies Japan, Ltd., Tokyo, Japan Search for more papers by this author Ryo Nakaki Rhelixa, Inc., Tokyo, Japan Search for more papers by this author Miho Kakeda Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Naoto Imamachi Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Aiko Sato Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Toshimichi Yamada Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Rena Onoguchi-Mizutani Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Gen Akizuki Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Tanzina Tanu Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Kazuyuki Tao Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Sotaro Miyao Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Yutaka Suzuki Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan Search for more papers by this author Masami Nagahama Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan Search for more papers by this author Tomoko Yamamoto Medical Mycology Research Center, Chiba University, Chiba, Japan Search for more papers by this author Torben Heick Jensen Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark Search for more papers by this author Nobuyoshi Akimitsu Corresponding Author [email protected] orcid.org/0000-0002-3190-2942 Isotope Science Center, The University of Tokyo, Tokyo, Japan Search for more papers by this author Author Information Katsutoshi Imamura1,2, Akiko Takaya1, Yo-ichi Ishida3, Yayoi Fukuoka4, Toshiki Taya4, Ryo Nakaki5, Miho Kakeda6, Naoto Imamachi6, Aiko Sato6, Toshimichi Yamada3,6, Rena Onoguchi-Mizutani6, Gen Akizuki6, Tanzina Tanu6, Kazuyuki Tao6, Sotaro Miyao3, Yutaka Suzuki7, Masami Nagahama3, Tomoko Yamamoto8, Torben Heick Jensen2 and Nobuyoshi Akimitsu *,6 1Department of Microbiology and Molecular Genetics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan 2Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark 3Laboratory of Molecular and Cellular Biochemistry, Meiji Pharmaceutical University, Tokyo, Japan 4Agilent Technologies Japan, Ltd., Tokyo, Japan 5Rhelixa, Inc., Tokyo, Japan 6Isotope Science Center, The University of Tokyo, Tokyo, Japan 7Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan 8Medical Mycology Research Center, Chiba University, Chiba, Japan *Corresponding author. Tel: +81 3 5841 2877; E-mail: [email protected] EMBO J (2018)37:e97723https://doi.org/10.15252/embj.201797723 See also: M Munschauer & J Vogel (July 2018) PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Cytoplasmic mRNA degradation controls gene expression to help eliminate pathogens during infection. However, it has remained unclear whether such regulation also extends to nuclear RNA decay. Here, we show that 145 unstable nuclear RNAs, including enhancer RNAs (eRNAs) and long noncoding RNAs (lncRNAs) such as NEAT1v2, are stabilized upon Salmonella infection in HeLa cells. In uninfected cells, the RNA exosome, aided by the Nuclear EXosome Targeting (NEXT) complex, degrades these labile transcripts. Upon infection, the levels of the exosome/NEXT components, RRP6 and MTR4, dramatically decrease, resulting in transcript stabilization. Depletion of lncRNAs, NEAT1v2, or eRNA07573 in HeLa cells triggers increased susceptibility to Salmonella infection concomitant with the deregulated expression of a distinct class of immunity-related genes, indicating that the accumulation of unstable nuclear RNAs contributes to antibacterial defense. Our results highlight a fundamental role for regulated degradation of nuclear RNA in the response to pathogenic infection. Synopsis Nuclear RNA degradation is repressed by Salmonella infection, resulting in the accumulation of unstable noncoding RNAs (ncRNAs) in the nucleus and the activation of immune-related genes. Nuclear long noncoding RNAs (lncRNAs) are degraded by exosome-dependent RNA degradation in mammalian cells. Salmonella infection induces loss of RRP6 and MTR4, components of nuclear RNA degradation pathway. Unstable nuclear lncRNAs are stabilized upon Salmonella infection. Accumulated lncRNAs control immune-related genes. Introduction Numerous studies have revealed that dynamic changes in cytoplasmic mRNA abundance, through tightly regulated degradation, are crucial in the control of various biological processes (Keene, 2010; Schott & Stoecklin, 2010; Alonso, 2012). For instance, mRNAs encoding cytokines are stabilized upon the occurrence of immune stimuli through regulated binding of specialized RNA-binding proteins (RBPs) to specific sequences, such as adenylate-/uridylate-rich elements (AREs), embedded in 3′ untranslated regions (3′UTRs) of these transcripts. This results in an increase in RNA abundance and the immediate production of proteins needed to fight pathogenic infection (Schott & Stoecklin, 2010). Cytoplasmic mRNA degradation is also involved in the quality control of mRNA (Lykke-Andersen & Jensen, 2015) and therefore is at the heart of post-transcriptional regulation of gene expression. In addition to the pool of cytoplasmic mRNAs, eukaryotic genomes produce a large variety of long noncoding RNAs (lncRNAs), some of which reside in cell nuclei and regulate gene expression (Imamura & Akimitsu, 2014; Quinn & Chang, 2016). We previously identified a class of human unstable nuclear lncRNAs implicated in cell proliferation (Tani et al, 2012). Other studies have identified additional unstable nuclear RNAs produced from enhancer regions, so-called enhancer RNAs (eRNAs) (Maekawa et al, 2015), which may mediate the transcriptional activation of nearby genes (Tani et al, 2015; Li et al, 2016). Although the biological roles of the vast majority of unstable nuclear lncRNAs remain undetermined, they constitute interesting model transcripts for studying the possible impact of regulated RNA turnover on nuclear lncRNA function. RNA degradation is primarily executed by 5′-3′ and 3′-5′ exonucleases. 3′-5′ exonucleolytic activity in mammalian nuclei depends mainly on the multisubunit RNA exosome complex composed of nine core subunits, such as RRP46 (EXOSC5), and two catalytic subunits, RRP44 (DIS3) and RRP6 (EXOSC10) (Schneider & Tollervey, 2013; Januszyk & Lima, 2014). The nuclear RNA exosome degrades a range of unstable transcripts, among which are included several lncRNAs and eRNAs (Maekawa et al, 2015). In addition, the RNA exosome plays a central role in the 3′-5′ processing of rRNAs and 3′-extended products of snoRNAs by collaborating with the TRf4p/Air2p/Mtr4p Polyadenylation (TRAMP) complex, which resides in the nucleolus in mammals (Allmang et al, 1999; Fasken et al, 2011; Lubas et al, 2015; Thoms et al, 2015; Sudo et al, 2016). RNA exosome is generally guided to its substrates by RNA-binding adaptor complexes (Kilchert et al, 2016). Indeed, the Nuclear EXosome Targeting (NEXT) complex, consisting of the RNA helicase MTR4, the Zn-finger protein ZCCHC8, and the RNA-binding protein RBM7, is involved in the exosomal targeting of PROMoter uPstream Transcripts (PROMPTs) (Lubas et al, 2011), eRNAs (Meola et al, 2016), and the 3′-extended products from snRNAs (Lubas et al, 2015). In this regard, the NEXT complex contributes to the elimination of transcripts pervasively produced throughout the genome (Jensen et al, 2013). More recently, a nuclear RNA decay pathway, coined the Poly(A) tail eXosome Targeting (PAXT) connection, consisting of MTR4, the Zn-finger protein ZFC3H1, and the nuclear polyA binding protein PABPN1, was identified to target polyadenylated nuclear transcripts (Meola et al, 2016). Here, we focus on infection by Salmonella enterica serovar Typhimurium (Salmonella), a frequently used model for investigating the mechanisms of host–bacterium interaction (Keestra-Gounder et al, 2015). Salmonella is a facultative intracellular pathogen that resides within a unique membrane-bound component following host cell invasion. Its infection mechanism depends on two type III secretion systems encoded by the Salmonella pathogenicity islands, SPI-1 and SPI-2, which are necessary for invasion and intracellular replication, respectively (Brawn et al, 2007). To limit bacterial infection, many proteins act inside host cells. However, a limited number of noncoding RNAs, including microRNAs and lncRNAs, have also been implicated in the regulation of Salmonella infection (Schulte et al, 2011; Gomez et al, 2013; Maudet et al, 2014). Here, we report on the upregulation of a subset of unstable nuclear noncoding RNAs in response to Salmonella infection. We find that these labile RNAs accumulate as a result of loss of nuclear exosome/NEXT components and that this accumulation contributes positively to the expression of cellular immunity-related genes and hence acts in the defense against Salmonella infection. Results Accumulation of unstable nuclear RNAs upon bacterial infection To identify genes that are upregulated in response to bacterial infection, we conducted whole-transcriptome analysis by RNA sequencing (RNA-seq) of HeLa cells at 2, 6, and 18 h postinfection (p.i.) with Salmonella. This revealed that 1,210 protein-coding transcripts were upregulated with fold changes > 2 over the time course (Table EV1, Figs EV1A and EV2A). Gene Ontology (GO) terms related to immune responses were significantly enriched for these genes (Table EV2). Moreover, our data confirmed the upregulation of several mRNAs previously reported to be transiently induced upon Salmonella infection, such as NFKB1, NFKB2, and RELB (Fig EV1B) (Afonso-Grunz et al, 2015). Finally, of the 26,858 unstable nuclear ncRNA candidates detected in HeLa cells (Fig EV2B), 145 were upregulated with fold changes > 2 upon Salmonella infection with diverse induction kinetics (Fig 1A and B, Table EV3). To determine whether the upregulation of these ncRNAs could also be independently detected, we analyzed publicly available RNA-seq data from different Salmonella-infected cell lines (Afonso-Grunz et al, 2015; Westermann et al, 2016). We found that 15–60% of the unstable nuclear ncRNAs upregulated in Salmonella-infected human cells were also upregulated in different cells under different conditions (Table EV4). Human unstable nuclear ncRNAs upregulated upon Salmonella infection can be annotated in mouse (47 ncRNAs) and pig (34 ncRNAs) cells (Westermann et al, 2016). Depending on cell lines and experimental conditions, we found that 27–45% of mouse unstable nuclear ncRNAs were upregulated in response to Salmonella infection (Table EV4), while 15–50% of pig unstable nuclear ncRNAs were also upregulated upon Salmonella infection (Table EV4). This variation may reflect differences in infection conditions (e.g., time course and multiplicity of infection) or the variable cellular context (different cell types and species). Click here to expand this figure. Figure EV1. Identification of genes with upregulated expression in HeLa cells upon Salmonella infection Volcano plots of expression of the indicated RNAs in HeLa cells at the indicated times post-Salmonella infection (p.i.). The volcano plots of log2 of the fold changes (FC) versus the P-value obtained from edgeR. Induction kinetics of genes typically induced upon Salmonella infection. Relative mRNA expression levels were calculated from RPKM values obtained by RNA-seq analysis of total RNA isolated from infected cells at the indicated times. Download figure Download PowerPoint Click here to expand this figure. Figure EV2. Bioinformatic analysis of genes with induced expression upon Salmonella infection Heat maps showing the kinetics of changes in expression of the indicated mRNAs at 2, 6, and 18 h postinfection. Red and blue indicate higher and lower expression levels of the RNAs, respectively, in infected cells compared with those in uninfected cells at the same time point. The represented RNAs showed altered expression with fold change > 2 or < 0.5 at any time point upon Salmonella infection. Flow chart for the selection of unstable nuclear ncRNAs from lncRNAs. Expression levels of protein-coding genes in relation to their genomic distances from eRNAs that are upregulated (red dots) and not upregulated (blue dots) in response to MTR4 depletion. Expression levels of protein-coding genes in relation to their genomic distances from eRNAs, which are upregulated in both Salmonella-infected cells and MTR4-depleted cells. Download figure Download PowerPoint Figure 1. Identification and analysis of unstable nuclear ncRNAs upregulated in response to Salmonella infection Heat map depicting the relative expression of unstable nuclear ncRNAs (fold change > 2 comparing to noninfected condition) in HeLa cells at 2, 6 and 18 h after Salmonella infection (m.o.i. of 75). UCSC genome browser examples of NEAT1v2 from intergenic region (upper) and eRNA from enhancer region (lower) with chromatin signatures obtained from ENCODE data (https://www.encodeproject.org/). Induction of the expression of neighboring protein-coding genes of upregulated and non-upregulated eRNAs at 18 h p.i. Red and blue circles indicate induction rate of the neighboring protein-coding genes of 26 upregulated eRNAs and 100 non-upregulated eRNAs, respectively. The x-axis indicates 200-kb genomic regions (200 kb downstream and 200 kb upstream from each eRNA genes) divided into 16 bins (12.5-kb DNA region per bin). The y-axis indicates the ratio of the number of induced protein-coding genes to the number of total protein-coding genes located within each 12.5-kb DNA region, plotted as “induced genes/total genes”. Analysis of expression of eRNAs and the neighboring genes by ChIP-RNAPII to estimate transcriptional activation (middle panels) and by RT–qPCR analysis to estimate RNA amount (lower panels). Relative genomic positions of the analyzed genes are schematically shown in the upper panels. Arrows indicate the direction of the genes. Error bars indicate the absolute errors of two replicates. Download figure Download PowerPoint Previous studies suggested that ncRNAs can be classified into canonical lncRNAs and eRNAs (Ne et al, 2014). Enhancer regions may be distinguished from promoter regions by their high level of monomethylated lysine 4 residues on histone 3 (H3K4me1) and high acetylation of H3K27 (H3K27Ac) (Ernst et al, 2011; Dorighi et al, 2017). Using publicly available chromatin immunoprecipitation (ChIP)-seq data for histone modifications (ENCODE consortium), 26 of the 145 upregulated unstable nuclear ncRNAs were mapped to enhancer regions (Fig 1B lower panel, Table EV3). As eRNAs have been reported to coordinate the regulation of neighboring protein-coding genes through a locus control process (Lam et al, 2013; Li et al, 2013; Melo et al, 2013), we investigated whether these eRNAs may be involved in the transcriptional regulation of genes in their vicinity. To this end, we examined whether there was any correlation between the upregulation of eRNAs and their adjacently transcribed mRNAs by comparing expression changes with the distance between eRNA- and mRNA-expressing loci. This metagene analysis revealed increased expression of 70% (9/13) of protein-coding genes within a 12.5 kb genomic distance of upregulated eRNAs (Fig 1C, red line), whereas protein-coding genes adjacent to eRNAs, which were not upregulated by infection, were unaffected (Fig 1C, blue line). Interestingly, GO analysis revealed that immune-related terms were significantly enriched among the upregulated protein-coding genes (21/99) within ± 100 kb of upregulated eRNAs (Table EV5). Such eRNA–mRNA distance-dependent co-upregulation could also be detected in MTR4-depleted HeLa cells, further suggesting that the correlation indeed arose via a decrease in nuclear RNA turnover (Fig EV2C and D). Finally, we demonstrated for a subset of these cases that increased mRNA levels were in part derived from increased transcription, as determined by RNA polymerase II (RNAPII)-ChIP PCR, whereas the eRNA upregulations were not transcription-based (Fig 1D, Table EV6). Altered half-lives underlie unstable nuclear lncRNA and eRNA upregulation To examine the molecular basis for unstable nuclear lncRNA and eRNA upregulation, we selected four ncRNAs as model RNAs: NEAT1v2, LINC00173, eRNA07573, and eRNA10281. Of these, NEAT1v2 is a known lncRNA, which forms nuclear paraspeckles by gathering transcriptional regulators such as SFPQ and NONO (Hirose et al, 2014; Imamura et al, 2014). NEAT1v2 also participates in the transcriptional regulation of immunity-related genes in response to viral infection (Imamura et al, 2014). Living Salmonella, but neither heat-killed Salmonella, lipopolysaccharide (LPS), nor flagellin, induced the upregulation of unstable nuclear lncRNAs (Fig 2A). To analyze this further, we conducted real-time quantitative reverse-transcription PCR (RT–qPCR) assays of total RNA from cells infected with Salmonella mutants: SPI-1 mt (invasion) or SPI-2 mt (intercellular replication). Neither of these infections induced these unstable nuclear lncRNAs (Fig 2B). This suggests that bacterial intracellular replication triggers the increase in the tested ncRNAs. Figure 2. Analysis of unstable nuclear ncRNA that accumulates upon Salmonella infection Expression levels of unstable nuclear ncRNAs in HeLa cells infected with Salmonella (m.o.i. of 75, 18 h p.i.), treated with heat-killed Salmonella (m.o.i. of 75), 1 μg/ml LPS, or flagella stimuli were quantified by RT–qPCR at 18 h post-treatment. GAPDH mRNA levels were used for normalization. The dashed x-axis represents a twofold line. Expression levels of unstable nuclear ncRNAs in HeLa cells infected with Salmonella wild type or mutants defective in SPI-1 (CS4022; prgI-depleted mutant) and SPI-2 (CS4019; ssaG-depleted mutant) were quantified by RT–qPCR 18 h postinfection. GAPDH mRNA levels were used for normalization. Degradations of unstable nuclear ncRNAs were determined by BRIC (NEAT1v2) or actinomycin D chase (LINC00173, eRNA07573, and eRNA10281) followed by RT–qPCR. Colored and white circles indicate RNA levels in cells with or without Salmonella infection, respectively. Relative quantitative values at time 0 h were set to 100%. HeLa cells with (color bars) and without (white bars) Salmonella infection at 18 h p.i. were subjected to ChIP-RNAPII of the promoter region of the indicated gene loci. The dashed x-axis represents a twofold line. Data information: Values represent the mean ± SD (n = 3, *P < 0.01, Student's t-test). Download figure Download PowerPoint To determine whether altered RNA stability might underlie the observed increases in ncRNA levels upon infection, we measured turnover rates of unstable nuclear ncRNAs upon Salmonella infection and compared these to any altered transcriptional activity. This demonstrated that infection led to the stabilization of unstable nuclear ncRNAs (Fig 2C) without any increase in RNAPII occupancy on the promoter regions of these unstable nuclear ncRNA genes (Fig 2D). In contrast, RNAPII was recruited to the promoters of the IL8 and SOCS3 genes, which are known to be transcriptionally activated by Salmonella infection (St John & Abraham, 2009; Bhavsar et al, 2013). We conclude that unstable nuclear RNAs are accumulated due to stabilization upon Salmonella infection. Factors involved in the degradation of unstable nuclear ncRNAs in uninfected cells Several labile nuclear RNAs are degraded by the 3′-5′ exonucleolytic RNA exosome (Schneider & Tollervey, 2013; Januszyk & Lima, 2014). We therefore examined whether this is also the case for unstable nuclear ncRNAs in uninfected cells. Indeed, knockdown of the exosome core subunit RRP46 increased the abundance of unstable nuclear ncRNAs, whereas depletion of XRN2, a major nuclear 5′-3′ exonuclease, had only a marginal effect (Fig 3A and B). The nucleoplasm of HeLa cells contains at least two targeting complexes associated with the nuclear RNA exosome: the NEXT complex and the PAXT connection. Moreover, the exosome co-factor hTRAMP is primarily localized to the nucleolus. Knockdown of hTRAMP components and PAXT components did not significantly affect the levels of unstable nuclear ncRNAs (Fig 3C and D). In contrast, the levels of unstable nuclear ncRNAs were increased by depletion of both the MTR4 and the ZCCHC8, components of the NEXT complex (Fig 3E). Some unstable nuclear ncRNAs were also affected by the depletion of RBM7, a component of the NEXT complex. Our data thus suggest that unstable nuclear ncRNAs are targeted for exosomal degradation mainly by the NEXT complex. Figure 3. Involvement of the NEXT complex in the degradation of unstable nuclear ncRNAs A–E. Level changes of the indicated unstable nuclear ncRNAs in HeLa cells transfected with the indicated siRNAs, RRP46 (A), XRN2 (B), TRAMP complex components (C), PAXT connection component (D), and NEXT complex components (E). Two independent siRNAs were examined for each target. Values represent the mean ± SD (n = 3, Student's t-test, *P < 0.01). Dashed lines indicate the values of twofold upregulation. Download figure Download PowerPoint MTR4 and RRP6 are lost upon Salmonella infection To search for a potential mechanism by which Salmonella infection might stabilize unstable nuclear ncRNAs, we used Western blotting analysis to monitor levels of different nuclear RNA degradation factors in infected cells. Interestingly, we observed that MTR4 and RRP6 were specifically lost upon infection (Fig 4A). MTR4 levels began to decrease 6 h p.i. and were almost undetectable at 18 h p.i., at which point RRP6 protein was also undetectable. To understand whether the loss of MTR4 and RRP6 could also be detected in other cell types, we analyzed several human and mouse cell lines infected with Salmonella. This revealed the loss of MTR4 and RRP6 in examined cell lines upon Salmonella infection (Fig EV3A). Consistent with this probably being causal of the upregulation of unstable nuclear ncRNAs, levels of these transcripts increased dramatically at 18 h p.i. (Figs 1A and 4B). To confirm the loss of exosome defect, we detected the upregulation of unstable nuclear ncRNAs in MTR4-depleted cells (Table EV7). To further confirm MTR4-mediated degradation of unstable nuclear ncRNAs, we determined the degradation kinetics of NEAT1v2 in MTR4-depleted or control cells. This confirmed that MTR4 depletion stabilizes unstable nuclear ncRNAs (Fig EV4A). Knockdown of MTR4 did not affect the expression level of RRP6, and vice versa (Fig EV4B), suggesting that the loss of these factors is independently executed. Figure 4. Loss of MTR4 and RRP6 in response to Salmonella infection Levels of indicated proteins analyzed by Western blotting at the indicated time points after Salmonella infection. Induction kinetics of NEAT1v2 and eRNA07573 upregulation in response to Salmonella infection (m.o.i. of 75). Values represent the mean ± SD (n = 3, Student's t-test, *P < 0.01). Western blotting analysis of 5–30% glycerol gradient fractions of HeLa cell extract with or without Salmonella infection (m.o.i. of 75, 18 h p.i.) using the indicated antibodies. Western blotting analysis in HeLa cells treated with cycloheximide (CHX). Source data are available online for this figure. Source Data for Figure 4 [embj201797723-sup-0017-SDataFig4.pdf] Download figure Download PowerPoint Click here to expand this figure. Figure EV3. Loss of MTR4 and RRP6 in several cell lines upon Salmonella infectionLevels of MTR4 and RRP6 proteins analyzed by Western blotting in the indicated cell lines upon Salmonella infection. The anti-MTR4 antibody from the Nagahama laboratory was used to detect the human cell lysate, and the anti-MTR4 antibody (ab70551, Abcam) was used to detect the mouse cell lysate. Source data are available online for this figure. Download figure Download PowerPoint Click here to expand this figure. Figure EV4. Analysis of nuclear RNA decay factors involved in the expression of unstable nuclear ncRNAs Stabilization of NEAT1v2 degradation in MTR4-depleted HeLa cells. The kinetics of RNA degradation was determined by the BRIC method followed by RT–qPCR analysis normalized to GAPDH mRNA levels. RRP6 and MTR4 expression levels in HeLa cells transfected with the indicated siRNAs. Diagram of the human pre-rRNA processing pathway. The red bars indicate ITS1 and ITS2 probes used for northern blotting. The blue arrows indicate MTR4-dependent pathways. The membrane stained with methylene blue. Northern blotting analysis of MTR4-depleted HEK293 cells or Salmonella-infected cells by using ITS1 probe. The lower table indicates each band intensity as determined using ImageJ. 47S/45S rRNA band intensity was adjusted to 1.00. Northern blot analysis of the MTR4-depleted HEK293 cells or Salmonella-infected cells by using ITS2 probe. The lower table indicates each band intensity as determined using ImageJ. 47S/45S rRNA band intensity was adjusted to 1.00. Source data are available online for this figure. Download figure Download PowerPoint