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A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

ABSTRACT: 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.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE165686 | GEO | 2021/01/29

REPOSITORIES: GEO

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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. 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.

Project description:Mycophenolic acid (MPA), an immunosuppressive drug widely used in kidney transplantation, has been suggested to have anti-fibrotic effects. To analyze at a genomic level these effects, we prospectively studied a group of stable kidney transplant recipients (n=35) on cyclosporine (CyA) and azathioprine treatment. Twenty patients were converted from azathioprine to MPA (MPA group) and 15 patients continued on azathioprine (AZA group). RNA was extracted by peripheral blood mononuclear cells at baseline and 3 months thereafter. Genomic analysis, performed on 5 randomly-selected MPA patients, revealed that 17 genes discriminated the transcriptomic profile after conversion. Neutral endopeptidase (NEP), an enzyme degrading angiotensin-II, was the most significant up-regulated gene. NEP expression level was inversely correlated to proteinuria at baseline and after conversion. Immunohistochemistry on graft biopsy of 33 independent patients demonstrated higher glomerular and tubular NEP protein expression in CyA+MPA (n=13) compared to CyA+AZA (n=12) and CyA alone (n=8). Glomerular NEP levels were inversely correlated to proteinuria and glomerulosclerosis. Tubular NEP expression was inversely correlated to interstitial fibrosis. Incubation of proximal tubular cells with MPA led to a dose- and time-dependent increase of NEP gene expression. The direct influence of MPA on NEP expression may suggest a novel therapeutic effect of this drug. For microarray analysis, we studied 5 randomly selected patients included in the training group. Patients included in this group were, at the time of enrollment (T0), on standard maintenance immunosuppression with Cyclosporine (Neoral, Novartis, Basel, mean±SD of daily dose: 160.1±37.1mg), prednisone (5 mg daily) and Azathioprine (50 mg daily). Twenty patients, at T0, were switched from Azathioprine to EC-MPS (Myfortic, Novartis, Basel, 720 mg bid) for their need of allopurinol therapy (EC-MPS group). However, to avoid confounding factors, allopurinol treatment did not start until the end of our study (3 months). For the microarray analysis, we randomly selected 5 patients from the EC-MPS group. PBMC both at T0 and at T1 (3 months after the switching of the therapy) were immediately isolated from 20 ml of whole blood by Ficoll–Hypaque (Flow Laboratories, Irvine, UK) density gradient centrifugation. Total RNA was extracted by RNeasy mini kit (QIAGEN Inc., Valencia, CA) according the manufacturer’s instructions. Total RNA was processed and hybridized to the Affymetrix GeneChips Human Genome U133 Array Set HG-U133A (Affymetrix)(Affymetrix, Santa Clara, CA)

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A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

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