Characterizing Human-Disease Mutations in the Essential RNA Exosome with the Budding Yeast Model System Restricted; Files Only
Sterrett, Maria (Spring 2023)
Abstract
Differential genetic expression allows for cellular diversity and specialized tissues composing our bodies. Key to this specialization are post-transcriptional events that regulate RNA(7). The RNA exosome is critical for many post-transcriptional events, required for 3’ to 5’ processing and degradation of a vast amount of RNA. This molecular machine is highly conserved, both in function and in structure, consisting of a 3-subunit cap, a 6-subunit core ring and a catalytic 3’-5’ exo/endoribonuclease. Recently, missense mutations have been identified in the structural cap and core subunit genes that cause distinct disease pathologies, including neurological and developmental disorders. The identification of these distinct diseases raises the question of how single amino acid substitutions in conserved, structural subunits of this complex affect RNA exosome function and consequently underlie diverse pathologies.
To explore the functional consequences of disease-linked amino acid substitutions in RNA exosome structural subunits, we generated Saccharomyces cerevisiae modeling disease mutations in corresponding budding yeast genes. In Chapter II, I present a systematic characterization of a single S. cerevisiae RNA exosome mutant model, rrp4-G226D. The rrp4-G226D cells model a mutation found in the cap subunit gene EXOSC2 that is linked to a novel syndrome. I uncover that the modeled pathogenic amino acid substitution impacts the function of the RNA exosome through disruptions of a key interaction with an RNA helicase known as Mtr4. In Chapter III, I take similar methods as in Chapter II and characterize a the rrp4-M68T mutant model. The rrp4-M68T cells model a mutation in EXOSC2 that is linked to multiple-myeloma. I find that rrp4-M68T also destabilizes interactions between the RNA exosome and Mtr4, however rrp4-M68T cells have functional consequences that differ from those of the rrp4-G226D model. In Chapter IV, I present a comparative RNA-Seq analysis of several S. cerevisiae models of disease-linked mutations in RNA exosome structural genes. I identify broad transcriptomic changes and uncover a shared link between RNA exosome disease mutations and translational defects. Overall, these studies provide evidence that disease-linked amino acid substitutions in structural subunits of the RNA exosome impair the function of the essential complex through differential in vivo consequences.
Table of Contents
Table of Contents
Chapter I: Introduction. 1
1.1 Post-Transcriptional Regulation of Gene Expression. 2
1.2 RNA Turnover and Decay. 5
1.3 The RNA Exosome: An Essential Molecular Machine. 7
1.4 Function of the Eukaryotic RNA Exosome. 9
1.5 Interacting Cofactors Expand the Function of the RNA Exosome. 10
1.6 RNA Exosome and Human Disease: RNA Exosomopathies. 11
1.7 RNA Exosomopathy-linked Amino Acid Substitutions and Differential Effects on RNA exosome Function in vivo. 13
1.8 Doctoral Research Aims. 15
1.9 Chapter I Figures. 17
Figure 1. Schematic representation of mRNA post-transcriptional regulation and gene expression. 17
Figure 2. Conservation of the core RNA exosome structure in eukarya and archaea. 20
Figure 3. Overview of pathogenic RNA exosomopathy amino acid substitutions in the human RNA exosome. 23
Figure 4. Proposed model of how RNA exosomopathy amino acid substitutions may result in distinct disease pathologies. 25
1.10 References. 27
Chapter II: A Budding Yeast Model for Human Disease Mutations in the EXOSC2 Cap Subunit of the RNA Exosome Complex. 35
2.1 Abstract 36
2.2 Introduction. 37
2.3 Materials and Methods. 41
2.4 Results. 51
2.5 Discussion. 61
2.6 Chapter II Acknowledgements. 67
2.7 Chapter II Figures. 68
Figure 1. Overview of pathogenic amino acid substitutions in the human cap subunit EXOSC2 of the RNA exosome. 68
Figure 2. Modeling pathogenic amino acid substitutions in Human EXOSC2 and S. cerevisiae Rrp4. 70
Figure 3. S. cerevisiae Rrp4 variants that model EXOSC2 variants identified in patients show impaired function. 72
Figure 4. The Rrp4 G58V and Rrp4 G226D variants do not associate with the RNA exosome complex in the presence of wild-type Rrp4, but the Rrp4 G226D variant can associate with the RNA exosome complex. 74
Figure 5. The rrp4-G226D variant cells show elevated levels of some but not all RNA exosome target transcripts. 76
Figure 6. RNA-Seq analysis of rrp4-G226D cells reveal distinct transcriptomic changes compared to RRP4 cells. 79
Figure 7. Validation of the differentially expressed transcripts identified in the RNA-Seq confirms that the levels of key mRNAs and CUTs are significantly altered in rrp4-G226D cells and reveals that some of these transcripts are not changed in rrp40-W195R cells. 81
Figure 8. The rrp4-G226D mutant exhibits distinct negative genetic interactions with RNA exosome cofactor mutants that are not shared by the rrp40-W195R mutant. 82
Figure 9. The rrp4-G226D mutant shows genetic interaction with an mtr4 mutant that is impaired for interaction with Rrp6/Rrp47 and Rrp4 G226D impairs interaction with Mtr4. 84
2.8 Chapter II Supplementary Materials. 86
Supplementary Figure S1. Protein sequence alignment of human EXOSC2 and EXOSC3. 86
Supplementary Figure S2. Modeling of the human EXOSC2-EXOSC4 and yeast Rrp4-Rrp41 interface show structural conservation. 88
Supplementary Figure S3. Increased input signal levels for rRNA northern blot in Figure 5A emphasize previously observed accumulation of 5.8S precursors in rrp40-W195R cells. 89
Supplementary Figure S4. Volcano plot of autophagy transcripts differentially expressed in the rrp4-G226D RNA-Seq. 90
Table S1. S. cerevisiae Strains and Plasmids used in this study. 91
Table S2. DNA Oligonucleotides employed for RT-qPCR.. 92
Table S3. Summary of in silico predictions for pathogenic amino acid substitutions in EXOSC2 and Rrp4. 93
2.9 References. 94
Chapter III: In vivo Characterization of the Critical Interaction between the RNA Exosome and the Essential RNA Helicase Mtr4 in Saccharomyces cerevisiae. 100
3.1 Abstract 101
3.2 Introduction. 102
3.3 Materials and Methods. 107
3.4 Results. 117
3.5 Discussion. 130
3.6 Chapter III Acknowledgements. 136
3.7 Chapter III Figures. 136
Figure 1. Overview of multiple myeloma linked amino acid substitutions in the human cap subunit EXOSC2 of the RNA exosome. 137
Figure 2. Modeling the multiple myeloma EXOSC2 M40T amino acid substitution in the human EXOSC2 cap subunit and the S. cerevisiae ortholog Rrp4. 139
Figure 3. S. cerevisiae rrp4-M68T mutant cells that model the EXOSC2 M40T variant identified in multiple myeloma patients show impaired function on drugs that impact RNA processing. 142
Figure 4. The rrp4-M68T mutant cells show elevated levels of specific RNA exosome target transcripts that depend on the Mtr4-RNA exosome interaction in vivo. 144
Figure 5. The modeled multiple myeloma amino acid substitution in Rrp4 does not impact Rrp4 protein level or association of the cap subunit with the RNA exosome complex. 146
Figure 6. The rrp4-M68T mutant cells show specific negative genetic interactions with mtr4 mutants that are predicted to impair the Trf4/5-Air1/2-Mtr4 (TRAMP) complex. 148
Figure 7. The rrp4-M68T mpp6Δ double mutant cells exhibits impaired growth that is exacerbated on drugs that impact RNA processing. 151
Figure 8. Rrp4 M68T shows decreased association with Mtr4 compared to wild-type Rrp4. 153
3.8 Chapter III Supplementary Materials. 154
Supplementary Figure S1. A collection of mutations in RNA exosome subunit genes were identified in newly diagnosed multiple myeloma patients in the CoMMpass study. 154
Supplementary Figure S2. ConSurf analysis of EXOSC2 and Rrp4 reveals conservation at interface with MTR4/Mtr4. 156
Supplementary Figure S3. The steady-state level of mature and precursor 5.8S rRNA in rrp4-M68T cells is similar to wild-type, control cells. 158
Supplementary Figure S4. Synthetical lethality of either rrp4-M68T mtr4-R349E-N352E and rrp4-M68T mtr4-R1030A double mutant cells is rescued by wild-type plasmid. 160
Supplementary Figure S5. Extended liquid growth curve of rrp4-M68T mpp6Δ and rrp4-M68T rrp47Δ cells. 161
Supplementary Figure S6. Chr9- NC_000009.12 (130,693,760…130,704,894) schematic with multiple myeloma patient EXOSC2 mutations. 162
Table S1. S. cerevisiae Strains and Plasmids used in this study. 163
Table S2. DNA Oligonucleotides employed for RT-qPCR.. 165
3.9 References. 166
Chapter IV. Comparative analysis of disease-linked amino acid substitutions in the RNA exosome modeled in S. cerevisiae reveal functional consequences in translation. 173
4.1 Abstract 174
4.2 Introduction. 175
4.3 Materials and Methods. 181
4.4 Results & Discussion. 184
4.5 Conclusion. 199
4.6 Chapter IV Figures. 201
Figure 1. Overview of pathogenic amino acid substitutions in the human cap and core structural subunits of the RNA exosome. 201
Figure 2. S. cerevisiae Rrp4 variants that model EXOSC variants identified in patients show impaired function. 204
Figure 3. RNA-Seq analysis of rrp RNA exosomopathy mutant models reveal distinct transcriptomic changes in the rrp4-G226D, rrp40-W195R and rrp46-L191H cells. 207
Figure 4. UpSet Plots of differentially expressed transcripts in rrp4-G226D, rrp40-W195R and rrp46-L191H cells reveal shared targets involved in metabolism and rRNA processing. 210
Figure 5. UpSet Plots of differentially expressed transcripts in rrp4-G226D, rrp40-W195R and rrp46-L191H cells reveal targets shared differently between dual combinations of the three rrp mutants. 213
Figure 6. UpSet Plots of differentially expressed transcripts in rrp4-G226D, rrp40-W195R and rrp46-L191H cells reveal targets uniquely impacted in each of the three rrp mutants. 216
Figure 7. Heatmaps of rrp mutants reveal broad changes in ribosomal protein gene and CUTs/SUTs expression. 218
4.7 Chapter IV Supplementary Materials. 219
Figure S1. MA plots for differential expression analysis results and PCA plots of sample clustering in RNA-Seq experiment. 219
Figure S2. Volcano plots of differentially expressed transcripts identified in rrp40-S87A, rrp45-I15P, rrp46-Q86I and rrp46-L127T samples. 221
Figure S3. Heatmap of ribosomal protein genes with gene names. 224
Table S1. List of RNA exosomopathy mutations and associated pathologies. 225
Table S2. Saccharomyces cerevisiae strains and plasmids. 226
Supplemental Documentation S1. Full RNA-Seq Datasets. 227
Supplemental Documentation S2. Full lists of differentially expressed genes (≥+1.5 or ≤-1.5 Fold Change [FC], p<0.05) 227
Supplemental Documentation S3. Full Gene Ontology (GO) Analyses Terms Lists. 227
Supplemental Documentation S4. Full Gene Ontology (GO) Analyses on Human homologs. 249
4.8 References. 262
Chapter V: Discussion & Future Directions. 269
5.1 Summary of Presented Studies. 270
5.2 Conclusions from Presented Studies. 273
5.3 Future Directions. 275
5.4 Closing Remarks. 281
5.5 Chapter V Figures. 283
Figure 1. Proposed model of how RNA exosomopathy amino acid substitutions may result in distinct translational defects that could underlie patient pathology. 284
5.6 References. 285
Appendix I. Generating a CRISPR/Cas9 toolkit to introduce RNA exosomopathy-linked missense mutations in S. cerevisiae genes. 290
A1.1 Abstract 291
A1.2 Introduction. 292
A1.3 CRISPR/Cas9 Toolkit and Workflow.. 295
A1.4 Results: Generating and assessing rrp4-G226D and rrp40-W195R mutant cells. 306
A1.5 Discussion. 309
A1.6 References. 317
Appendix II. Experimental Design to assess the impacts of pathogenic amino acid substitutions on RNA exosome integrity. 319
A1.1 Introduction. 320
A1.2 Experimental Design. 322
A1.3 Step I: Generating Inducible Constructs Expressing wild-type Rrp variant with HA tag. 324
A1.4 Step II: Verifying expression of generated inducible construct 325
A1.5 Step II:: Timecourse assay to assess exchange rate between the Myc tagged versus the HA tagged Rrp variant. 327
A1.6 Future Directions. 331
A1.7 References. 336
Appendix III. Amplifying Growth Mindsets With PCR: Implementing growth mindset interventions in introductory biology lab to increase resiliency in undergraduate STEM students. 338
A3.1 Introduction. 339
A3.2 Defining “Mindset”. 341
A3.3 Rationale and Approach. 342
A3.4 Experimental Design. 344
A3.5 Results and Limitations of study. 350
A3.5 Discussion. 353
A3.6 Appendices. 355
A3.7 References. 367
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