A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels.
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ABSTRACT:
SUBMITTER: Urbonaite G
PROVIDER: S-EPMC8245502 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The ability to measure the number of gene-specific mRNA molecules in individual mammalian cells has transformed the transcriptomics field. Among the key technologies enabling single-cell mRNA sequencing has been Droplet Sequencing (Drop-Seq). While this method works efficiently for mammalian cells, its direct application to yeast cells has been problematic due to cell-type specific differences such as size, doublet formation rate, and cell wall. Here we introduce YeastDropSeq, a single-cell RNA sequencing method for the study of transcriptomics in yeast. We modified and optimized the original Drop-Seq method to address the issues that emerged from smaller cell sizes and the presence of a cell wall in yeast. As proof-of-principle application of the YeastDropSeq, we investigated the transcriptomic effects of mycophenolic acid (MPA), a lifespan-extending compound that decreases de novo GMP synthesis. We compared transcript levels between cells treated with MPA and cells treated with DMSO and/or guanine, MPA’s epistatic agent. We discovered that isogenic populations of yeast cells contain transcriptionally distinct subpopulations and that the subpopulation structures were maintained despite the different treatment conditions. We found that cells treated with MPA experience an upregulation of genes coding for proteins involved in DNA replication stress-response, antioxidation, pre-RNA processing, and translation initiation. Conversely, a downregulation of mRNA expression was observed for genes encoding translation initiation and elongation factors, the 40S and 60S ribosomal subunits, and for genes involved in metal transport and mitochondrial function. YeastDropSeq will accelerate biological discovery by facilitating droplet-based transcriptomics of yeast cells.
2021-01-29 | GSE165686 | GEO
Project description:The ability to measure the number of gene-specific mRNA molecules in individual mammalian cells has transformed the transcriptomics field. Among the key technologies enabling single-cell mRNA sequencing has been Droplet Sequencing (Drop-Seq). While this method works efficiently for mammalian cells, its direct application to yeast cells has been problematic due to cell-type specific differences such as size, doublet formation rate, and cell wall. Here we introduce YeastDropSeq, a single-cell RNA sequencing method for the study of transcriptomics in yeast. We modified and optimized the original Drop-Seq method to address the issues that emerged from smaller cell sizes and the presence of a cell wall in yeast. We also quantified the rate of doublet formation through a species-mixing experiment. As proof-of-principle application of the YeastDropSeq, we investigated the transcriptomic effects of mycophenolic acid (MPA), a lifespan-extending compound that decreases de novo GMP synthesis. We compared transcript levels between cells treated with MPA and cells treated with DMSO and/or guanine, MPA’s epistatic agent. We discovered that isogenic populations of yeast cells contain transcriptionally distinct subpopulations and that the subpopulation structures were maintained despite the different treatment conditions. We found that cells treated with MPA experience an upregulation of genes coding for proteins involved in DNA replication stress-response, antioxidation, pre-RNA processing, and translation initiation. Conversely, a downregulation of mRNA expression was observed for genes encoding translation initiation and elongation factors, the 40S and 60S ribosomal subunits, and for genes involved in metal transport and mitochondrial function. Additionally, we elucidated that expression levels of several genes of unknown function were affected by the MPA treatment. YeastDropSeq will accelerate biological discovery by facilitating droplet-based transcriptomics of yeast cells.
2020-06-26 | GSE144636 | GEO
Project description:A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
| PRJNA695455 | ENA
Project description:A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
| PRJNA604244 | ENA
Project description:Correlations between gene transcription and the abundance of high-energy purine nucleotides in Saccharomyces cerevisiae have often been noted. However, there has been no systematic investigation of this phenomenon in the absence of confounding factors such as nutrient status and growth rate, and there is little hard evidence for a causal relationship. Whether transcription is fundamentally responsive to prevailing cellular energetic conditions via sensing of intracellular purine nucleotides, independently of specific nutrition, remains an important question. The controlled nutritional environment of chemostat culture revealed a strong correlation between ATP and GTP abundance and the transcription of genes required for growth. Short pathways for the inducible and futile consumption of ATP or GTP were engineered into S. cerevisiae, permitting analysis of the transcriptional effect of an increased demand for these nucleotides. During steady-state growth using the fermentable carbon source glucose, the futile consumption of ATP led to a decrease in intracellular ATP concentration but an increase in GTP and the guanylate energy charge (GEC). Expression of transcripts encoding proteins involved in ribosome biogenesis, and those controlled by promoters subject to SWI/SNF-dependent chromatin remodelling, was correlated with these nucleotide pool changes. Similar nucleotide abundance changes were observed using a nonfermentable carbon source, but an effect on the growth-associated transcriptional programme was absent. Induction of the GTP-cycling pathway had only marginal effects on nucleotide abundance and gene transcription. The transcriptional response of respiring cells to glucose was dampened in chemostats induced for ATP cycling, but not GTP cycling, and this was primarily associated with altered adenine nucleotide levels.IMPORTANCE This paper investigates whether, independently of the supply of any specific nutrient, gene transcription responds to the energy status of the cell by monitoring ATP and GTP levels. Short pathways for the inducible and futile consumption of ATP or GTP were engineered into the yeast Saccharomyces cerevisiae, and the effect of an increased demand for these purine nucleotides on gene transcription was analyzed. The resulting changes in transcription were most consistently associated with changes in GTP and GEC levels, although the reprogramming in gene expression during glucose repression is sensitive to adenine nucleotide levels. The results show that GTP levels play a central role in determining how genes act to respond to changes in energy supply and that any comprehensive understanding of the control of eukaryotic gene expression requires the elucidation of how changes in guanine nucleotide abundance are sensed and transduced to alter the global pattern of transcription.
| S-EPMC6343037 | biostudies-literature
Project description:Post-transcriptional gene regulation is mediated through complex networks of protein-RNA interactions. The targets of only a few RNA binding proteins (RBPs) are known, even in the well-characterized budding yeast. In silico prediction of protein-RNA interactions is therefore useful to guide experiments and to provide insight into regulatory networks. Computational approaches have identified RBP targets based on sequence binding preferences. We investigate here to what extent RBP-RNA interactions can be predicted based on RBP and mRNA features other than sequence motifs. We analyze global relationships between gene and protein properties in general and between selected RBPs and known mRNA targets in particular. Highly translated RBPs tend to bind to shorter transcripts, and transcripts bound by the same RBP show high expression correlation across different biological conditions. Surprisingly, a given RBP preferentially binds to mRNAs that encode interaction partners for this RBP, suggesting coordinated post-transcriptional auto-regulation of protein complexes. We apply a machine-learning approach to predict specific RBP targets in yeast. Although this approach performs well for RBPs with known targets, predictions for uncharacterized RBPs remain challenging due to limiting experimental data. We also predict targets of fission yeast RBPs, indicating that the suggested framework could be applied to other species once more experimental data are available.
| S-EPMC3152324 | biostudies-literature
Project description:Oxidation of guanine (Gua) to form 7,8-dihydro-8-oxoguanine (8oxoG) is a frequent mutagenic DNA lesion. DNA repair glycosylases such as the bacterial MutM can effciently recognize and eliminate the 8oxoG damage by base excision. The base excision requires a 8oxoG looping out (flipping) from an intrahelical base paired to an extrahelical state where the damaged base is in the enzyme active site. It is still unclear how the damage is identified and flipped from an energetically stable stacked and paired state without any external energy source. Free energy simulations have been employed to study the flipping process for globally deformed DNA conformational states. DNA deformations were generated by systematically untwisting the DNA to mimic its conformation in repair enzyme encounter complex. The simulations indicate that global DNA untwisting deformation toward the enzyme bound form alone (without protein) significantly reduces the penalty for damage flipping to about half of the penalty observed in regular DNA. The finding offers a mechanistic explanation how binding free energy that is transformed to binding induced DNA deformation facilitates flipping and helps to rapidly detect a damaged base. It is likely of general relevance since repair enzyme binding frequently results in significant deformation of the target DNA.
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Project description:The human placenta is a dynamic and heterogeneous organ critical in the establishment of the fetomaternal interface and the maintenance of gestational well-being. It is also the major source of cell-free fetal nucleic acids in the maternal circulation. Placental dysfunction contributes to significant complications, such as preeclampsia, a potentially lethal hypertensive disorder during pregnancy. Previous studies have identified significant changes in the expression profiles of preeclamptic placentas using whole-tissue analysis. Moreover, studies have shown increased levels of targeted RNA transcripts, overall and placental contributions in maternal cell-free nucleic acids during pregnancy progression and gestational complications, but it remains infeasible to noninvasively delineate placental cellular dynamics and dysfunction at the cellular level using maternal cell-free nucleic acid analysis. In this study, we addressed this issue by first dissecting the cellular heterogeneity of the human placenta and defined individual cell-type-specific gene signatures by analyzing more than 24,000 nonmarker selected cells from full-term and early preeclamptic placentas using large-scale microfluidic single-cell transcriptomic technology. Our dataset identified diverse cellular subtypes in the human placenta and enabled reconstruction of the trophoblast differentiation trajectory. Through integrative analysis with maternal plasma cell-free RNA, we resolved the longitudinal cellular dynamics of hematopoietic and placental cells in pregnancy progression. Furthermore, we were able to noninvasively uncover the cellular dysfunction of extravillous trophoblasts in early preeclamptic placentas. Our work showed the potential of integrating transcriptomic information derived from single cells into the interpretation of cell-free plasma RNA, enabling the noninvasive elucidation of cellular dynamics in complex pathological conditions.
| S-EPMC5604038 | biostudies-literature
Project description:We measured half-lives of 21,248 mRNA 3' isoforms in yeast by rapidly depleting RNA polymerase II from the nucleus and performing direct RNA sequencing throughout the decay process. Interestingly, half-lives of mRNA isoforms from the same gene, including nearly identical isoforms, often vary widely. Based on clusters of isoforms with different half-lives, we identify hundreds of sequences conferring stabilization or destabilization upon mRNAs terminating downstream. One class of stabilizing element is a polyU sequence that can interact with poly(A) tails, inhibit the association of poly(A)-binding protein, and confer increased stability upon introduction into ectopic transcripts. More generally, destabilizing and stabilizing elements are linked to the propensity of the poly(A) tail to engage in double-stranded structures. Isoforms engineered to fold into 3' stem-loop structures not involving the poly(A) tail exhibit even longer half-lives. We suggest that double-stranded structures at 3' ends are a major determinant of mRNA stability.
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Project description:Nonsense-mediated mRNA decay (NMD) is a eukaryotic mechanism of RNA surveillance that selectively eliminates aberrant transcripts coding for potentially deleterious proteins. NMD also functions in the normal repertoire of gene expression. In Saccharomyces cerevisiae, hundreds of endogenous RNA Polymerase II transcripts achieve steady-state levels that depend on NMD. For some, the decay rate is directly influenced by NMD (direct targets). For others, abundance is NMD-sensitive but without any effect on the decay rate (indirect targets). To distinguish between direct and indirect targets, total RNA from wild-type (Nmd(+)) and mutant (Nmd(-)) strains was probed with high-density arrays across a 1-h time window following transcription inhibition. Statistical models were developed to describe the kinetics of RNA decay. 45% +/- 5% of RNAs targeted by NMD were predicted to be direct targets with altered decay rates in Nmd(-) strains. Parallel experiments using conventional methods were conducted to empirically test predictions from the global experiment. The results show that the global assay reliably distinguished direct versus indirect targets. Different types of targets were investigated, including transcripts containing adjacent, disabled open reading frames, upstream open reading frames, and those prone to out-of-frame initiation of translation. Known targeting mechanisms fail to account for all of the direct targets of NMD, suggesting that additional targeting mechanisms remain to be elucidated. 30% of the protein-coding targets of NMD fell into two broadly defined functional themes: those affecting chromosome structure and behavior and those affecting cell surface dynamics. Overall, the results provide a preview for how expression profiles in multi-cellular eukaryotes might be impacted by NMD. Furthermore, the methods for analyzing decay rates on a global scale offer a blueprint for new ways to study mRNA decay pathways in any organism where cultured cell lines are available.
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