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The transcriptional and splicing landscape of intestinal organoids undergoing nutrient starvation or endoplasmic reticulum stress - PubMed

  • ️Fri Jan 01 2016

The transcriptional and splicing landscape of intestinal organoids undergoing nutrient starvation or endoplasmic reticulum stress

Jessica Tsalikis et al. BMC Genomics. 2016.

Abstract

Background: The intestinal epithelium plays a critical role in nutrient absorption and innate immune defense. Recent studies showed that metabolic stress pathways, in particular the integrated stress response (ISR), control intestinal epithelial cell fate and function. Here, we used RNA-seq to analyze the global transcript level and alternative splicing responses of primary murine enteroids undergoing two distinct ISR-triggering stresses, endoplasmic reticulum (ER) stress and nutrient starvation.

Results: Our results reveal the core transcript level response to ISR-associated stress in murine enteroids, which includes induction of stress transcription factors, as well as genes associated with chemotaxis and inflammation. We also identified the transcript expression signatures that are unique to each ISR stress. Among these, we observed that ER stress and nutrient starvation had opposite effects on intestinal stem cell (ISC) transcriptional reprogramming. In agreement, ER stress decreased EdU incorporation, a marker of cell proliferation, in primary murine enteroids, while nutrient starvation had an opposite effect. We also analyzed the impact of these cellular stresses on mRNA splicing regulation. Splicing events commonly regulated by both stresses affected genes regulating splicing and were associated with nonsense-mediated decay (NMD), suggesting that splicing is modulated by an auto-regulatory feedback loop during stress. In addition, we also identified a number of genes displaying stress-specific splicing regulation. We suggest that functional gene expression diversity may arise during stress by the coordination of alternative splicing and alternative translation, and that this diversity might contribute to the cellular response to stress.

Conclusions: Together, these results provide novel understanding of the importance of metabolic stress pathways in the intestinal epithelium. Specifically, the importance of cellular stresses in the regulation of immune and defense function, metabolism, proliferation and ISC activity in the intestinal epithelium is highlighted. Furthermore, this work highlights an under-appreciated role played by alternative splicing in shaping the response to stress and reveals a potential mechanism for gene regulation involving coupling of AS and alternative translation start sites.

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Figures

Fig. 1
Fig. 1

RNA-seq analysis of transcript levels in thapsigargin-stimulated and nutrient-starved murine enteroids. a Experimental design of samples submitted for RNA-seq. Intestinal organoid cultures were derived from three separate mice per condition. RNA was purified from organoids stimulated with either thapsigargin or nutrient-starved for 4 h and sent for RNA-seq. b Overview of the total number of genes analyzed (average over three replicates), including the adjusted total number of genes excluding those which had RPKM values >0. c, d Scatterplot analysis of the log10 changes in expression of the total (adjusted for RPKM values >0) number of genes in thapsigargin versus control enteroids (c) and nutrient starved versus control enteroids (d). e Violin scatter boxplot analysis of the genes induced and repressed more than 2.5 fold upon thapsigargin treatment and nutrient starvation. f Average fold change overall in the genes analyzed upon thapsigargin and nutrient starvation

Fig. 2
Fig. 2

Induction of an ER stress transcriptional program in thapsigargin-stimulated enteroids. a Scatterplot of the expression of ER stress response classified genes. Genes above the top red line represent a 2.5-fold increase in expression, while genes below the bottom red line represent genes down-regulated 2.5-fold. b Alternative splicing of transcription factor gene Xbp1 upon thapsigargin treatment, visualized via integrated genome browser (IGV). c Venn diagram analysis of 651 genes upregulated more than 2.5 fold upon 4 h of thapsigargin treatment, categorized by gene function. d Gene list manually curated based on gene function from the group of 651 upregulated genes. e Venn diagram analysis of 245 genes down-regulated more than 2.5 fold upon 4 h of thapsigargin treatment, categorized by gene function. f Gene list manually curated based on gene function from the group of 245 downregulated genes

Fig. 3
Fig. 3

Nutrient starvation and ER stress induce a common transcriptional landscape in murine enteroids. a Venn diagram comparison of the genes commonly upregulated more than 2.5 fold upon nutrient starvation and thapsigargin treatment. Hypergeometric tests were used to calculate the P values for significance of overlaps. Scatterplot analysis of the genes transcriptionally upregulated (cutoff >2.5 fold) upon thapsigargin and nutrient starvation. Plots are displayed analyzing of the total number of genes (801) (b) or categorized by gene function (c). d Analysis of the gene function of the 90 genes commonly upregulated upon thapsigargin and nutrient starvation. e Expression profiles of genes encoding transcription factors and genes involved in inflammation/chemotaxis, manually picked from the 90 genes upregulated more than 2.5 fold upon thapsigargin/nutrient starvation. Expression profiles of three biological replicates per stimulation are shown (lanes a, b and c)

Fig. 4
Fig. 4

Metabolic stress affects the expression profile of intestinal stem cell genes. a Scatterplot analysis of the fold expression profiles of 151 intestinal stem cell (ISC) genes upon thapsigargin and nutrient starvation. b Overall fold induction of ISC genes compared to the total gene induction upon thapsigargin treatment and nutrient starvation. c List of ISC genes upregulated and downregulation more than 2 fold upon stress. d Cell proliferation was analyzed by flow cytometry by monitoring EdU incorporation during the last 2 h of the 4 h treatment. Representative profiles of thapsigargin-treated (blue), nutrient-starved (green) and untreated control organoids (black) are shown. e Quantification of cell proliferation is presented as mean fluorescence intensity (MFI)

Fig. 5
Fig. 5

Analysis of the alternative splicing landscape in murine enteroids upon thapsigargin treatment. a Classification of AS events induced upon thapsigargin based on type of splicing event (skipping(S)/inclusion(I), complex 1 (C1), complex 3 (C3), alternative 3’ (Alt3), intron retention simple (IR-S), intron retention complex (IR-C), complex 2 (C2), alternative 5’ (Alt5)). Examples of both skipping and inclusion events are shown. b Scatterplot of the expression of the genes found to undergo AS upon thapsigargin treatment. Genes above the top red line represent a 2.5-fold increase in expression, while genes below the bottom red line represent genes down-regulated 2.5-fold. c Comparison of the proportion of frameshifting vs. non-frameshifting events within each category of AS type. d Examples of frameshifting AS events in Srsf7 (S) and Smndc1 (Alt3). Gene schematics showing the AS events in blue, as well as the Sashimi plots obtained by IGV showing the total read numbers for each junction. e GO analysis of the gene group enrichment among the genes that underwent AS during thapsigargin treatment

Fig. 6
Fig. 6

ER stress and amino acid starvation induce a common alternative splicing signature. a Venn diagrams demonstrating the overlap between the AS events occurring during thapsigargin treatment and nutrient starvation. The overlap p value was calculated using a hypergeometric test. b Validation of AS events for Hnrnpd, Ogt, Srsf7, Ivns1abp, Hnrpdl. Gene schematics highlighting the AS events along with approximate location of the premature termination codon (PTC), along with PSI value plots for each event. Semi-quantitative RT-PCR validations for each event are shown, with the spliced PCR product labeled by an arrow. IGV plots of RNA-seq read for each AS event and adjacent sequence reads, with AS events highlighted accordingly

Fig. 7
Fig. 7

Splicing of retained introns in CLK4/1 upon ER stress. a Gene schematic showing splicing of detained introns (introns 3 and 4) upon control conditions vs. stress conditions (red dotted line). b Plots of expression values for CLK1/4 upon thapsigargin treatment and nutrient starvation. c Western blot analysis of CLK4 protein upon thapsigargin and KRB stimulation for 6 or 20 h, as compared to tubulin loading control (d) PSI values for splicing of introns 3 and 4 of CLK1/4. e Sashimi plots representing the splicing of introns 3 and 4 of CLK1/4. Values in red represented the amount of DI splicing, calculated by taking the value of exon 4 skipped / (average of intron 3 retained, intron 4 retained), taken as an average of three biological replicates, with the standard deviation values. A higher value corresponds to more splicing of introns 3 and 4 and consequently, more retention of exon 4

Fig. 8
Fig. 8

Validation of various alternative splicing events and in silico prediction of alternative ATG usage in splice variants induced upon cellular stress. a-b Six selected AS events induced upon thapsigargin treatment (Casp4, Slc35b1, Ufdl1) (a) and nutrient starvation (Frrs, Nnt, Nt5c3) (b). The type of AS event is indicated beside the gene name in parenthesis (S – skipping, Alt3 – alternative 3’, Alt5 – alternative 5’, C3 – complex type 3). Plots depicting the percent spliced-in (PSI) values for the AS events are shown. c-d Gene structures of full-length Casp4, Slc35b1, Nt5c3, Tinag, and Ufd1l using the canonical translation start sites (cATG) and their predicted splice variants induced by cellular stress (AS event highlighted in red). The alternative ATG (aATG) utilized by these variants were previously annotated by Aceview. The different protein domains encoded by the full-length and splice variants were analyzed using Simple Modular Architecture Research Tool (SMART) (c) and changes in protein localization were analyzed using PSORT (d)

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References

    1. Donnelly N, Gorman AM, Gupta S, Samali A. The eIF2alpha kinases: their structures and functions. Cell Mol Life Sci. 2013;70(19):3493–3511. doi: 10.1007/s00018-012-1252-6. - DOI - PMC - PubMed
    1. Cao SS, Wang M, Harrington JC, Chuang BM, Eckmann L, Kaufman RJ. Phosphorylation of eIF2alpha is dispensable for differentiation but required at a posttranscriptional level for paneth cell function and intestinal homeostasis in mice. Inflamm Bowel Dis. 2014;20(4):712–722. doi: 10.1097/MIB.0000000000000010. - DOI - PubMed
    1. Datta S, Barrera N, Pavicic PG, Jr, Zhao C, Freeman M, Min B, Hamilton T. cEBP Homologous protein expression in macrophages regulates the magnitude and duration of IL-6 expression and dextran sodium sulfate colitis. J Interferon Cytokine Res. 2015;35(10):785–794. doi: 10.1089/jir.2014.0204. - DOI - PMC - PubMed
    1. Kaser A, Lee AH, Franke A, Glickman JN, Zeissig S, Tilg H, Nieuwenhuis EE, Higgins DE, Schreiber S, Glimcher LH, et al. XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell. 2008;134(5):743–756. doi: 10.1016/j.cell.2008.07.021. - DOI - PMC - PubMed
    1. Sato T, Vries RG, Snippert HJ, van de Wetering M, Barker N, Stange DE, van Es JH, Abo A, Kujala P, Peters PJ, et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature. 2009;459(7244):262–265. doi: 10.1038/nature07935. - DOI - PubMed

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