ArticleG3 (Bethesda, Md.)2014
A method for sporulating budding yeast cells that allows for unbiased identification of kinase substrates using stable isotope labeling by amino acids in cell culture.
Article in G3 (Bethesda, Md.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Multi-site phosphorylation of yeast Mif2/CENP-C promotes inner kinetochore assembly.Current biology : CB · 2023Article
- The Proteomic Landscape of Centromeric Chromatin Reveals an Essential Role for the Ctf19Current biology : CB · 2021Article
- Mek1 coordinates meiotic progression with DNA break repair by directly phosphorylating and inhibiting the yeast pachytene exit regulator Ndt80.PLoS genetics · 2018Article
- Mek1 Down Regulates Rad51 Activity during Yeast Meiosis by Phosphorylation of Hed1.PLoS genetics · 2016Article
- Identification of Putative Mek1 Substrates during Meiosis in Saccharomyces cerevisiae Using Quantitative Phosphoproteomics.PloS one · 2016Article
- Phosphorylation of the Synaptonemal Complex Protein Zip1 Regulates the Crossover/Noncrossover Decision during Yeast Meiosis.PLoS biology · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Quantitative proteomics has been widely used to elucidate many cellular processes. In particular, stable isotope labeling by amino acids in cell culture (SILAC) has been instrumental in improving the quality of data generated from quantitative high-throughput proteomic studies. SILAC uses the cell's natural metabolic pathways to label proteins with isotopically heavy amino acids. Incorporation of these heavy amino acids effectively labels a cell's proteome, allowing the comparison of cell cultures treated under different conditions. SILAC has been successfully applied to a variety of model organisms including yeast, fruit flies, plants, and mice to look for kinase substrates as well as protein-protein interactions. In budding yeast, several kinases are known to play critical roles in different aspects of meiosis. Therefore, the use of SILAC to identify potential kinase substrates would be helpful in the understanding the specific mechanisms by which these kinases act. Previously, it has not been possible to use SILAC to quantitatively study the phosphoproteome of meiotic Saccharomyces cerevisiae cells, because yeast cells sporulate inefficiently after pregrowth in standard synthetic medium. In this study we report the development of a synthetic, SILAC-compatible, pre-sporulation medium (RPS) that allows for efficient sporulation of S. cerevisiae SK1 diploids. Pre-growth in RPS supplemented with heavy amino acids efficiently labels the proteome, after which cells proceed relatively synchronously through meiosis, producing highly viable spores. As proof of principle, SILAC experiments were able to identify known targets of the meiosis-specific kinase Mek1.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.