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Merkel cell carcinoma (MCC)-a neuroendocrine cancer of the skin-is caused by the integration of Merkel cell polyomavirus and persistent expression of large T antigen and small T antigen. We report that small T antigen in complex with MYCL and the EP400 complex activates the expression of LSD1 (KDM1A), RCOR2 and INSM1 to repress gene expression by the lineage transcription factor ATOH1. LSD1 inhibition reduces the growth of MCC in vitro and in vivo. Through a forward-genetics CRISPR-Cas9 screen, we identified an antagonistic relationship between LSD1 and the non-canonical BAF (ncBAF) chromatin remodelling complex. Changes in gene expression and chromatin accessibility caused by LSD1 inhibition were partially rescued by BRD9 inhibition, revealing that LSD1 and ncBAF antagonistically regulate an overlapping set of genes. Our work provides mechanistic insight into the dependence of MCC on LSD1 and a tumour suppressor role for ncBAF in cancer.
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Stochasticity between independent LC-MS/MS runs is a challenging problem in the field of proteomics, resulting in significant missing values (i.e., abundance measurements) among observed peptides. To address this issue, several approaches have been developed including computational methods such as MaxQuant's match-between-runs (MBR) algorithm. Often dozens of runs are all considered at once by MBR, transferring identifications from any one run to any of the others. To evaluate the error associated with these transfer events, we created a two-sample/two-proteome approach. In this way, samples containing no yeast lysate (n = 20) were assessed for false identification transfers from samples containing yeast (n = 20). While MBR increased the total number of spectral identifications by â¼40%, we also found that 44% of all identified yeast proteins had identifications transferred to at least one sample without yeast. However, of these only 2.7% remained in the final data set after applying the MaxQuant LFQ algorithm. We conclude that false transfers by MBR are plentiful, but few are retained in the final data set.
Assuntos
Algoritmos , Biologia Computacional/métodos , Proteoma/metabolismo , Proteômica/métodos , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/metabolismo , Sequência de Aminoácidos , Cromatografia Líquida/métodos , Células HCT116 , Humanos , Peptídeos/análise , Reprodutibilidade dos Testes , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética , Especificidade da Espécie , Espectrometria de Massas em Tandem/métodosRESUMO
Phosphorylation stoichiometry, or occupancy, is one element of phosphoproteomics that can add useful biological context (Gerber et al. Proc. Natl. Acad. Sci. U. S. A. 2003, 100, 6940-5). We previously developed a method to assess phosphorylation stoichiometry on a proteome-wide scale (Wu et al. Nat. Methods 2011, 8, 677-83). The stoichiometry calculation relies on identifying and measuring the levels of each nonphosphorylated counterpart peptide with and without phosphatase treatment. The method, however, is problematic in that low stoichiometry phosphopeptides can return negative stoichiometry values if measurement error is larger than the percent stoichiometry. Here, we have improved the stoichiometry method through the use of isobaric labeling with 10-plex TMT reagents. In this way, five phosphatase treated and five untreated samples are compared simultaneously so that each stoichiometry is represented by five ratio measurements with no missing values. We applied the method to determine basal stoichiometries of HCT116 cells growing in culture. With this method, we analyzed five biological replicates simultaneously with no need for phosphopeptide enrichment. Additionally, we developed a Bayesian model to estimate phosphorylation stoichiometry as a parameter confined to an interval between 0 and 1 implemented as an R/Stan script. Consequently, both point and interval estimates are consistent with the plausible range of values for stoichiometry. Finally, we report absolute stoichiometry measurements with credible intervals for 6772 phosphopeptides containing at least a single phosphorylation site.