We describe a rapid, sensitive process for comprehensively identifying proteins in macromolecular complexes that uses multidimensional liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to separate and fragment peptides. The SEQUEST algorithm, relying upon translated genomic sequences, infers amino acid sequences from the fragment ions. The method was applied to the Saccharomyces cerevisiae ribosome leading to the identification of a novel protein component of the yeast and human 40S subunit. By offering the ability to identify >100 proteins in a single run, this process enables components in even the largest macromolecular complexes to be analyzed comprehensively.
Gene profiling techniques allow the assay of transcripts from organs, tissues, and cells with an unprecedented level of coverage. However, most of these approaches are still limited by the fact that organs and tissues are composed of multiple cell types that are each unique in their patterns of gene expression. To identify the transcriptome from a single cell type in a complex tissue, investigators have relied upon physical methods to separate cell types or in situ hybridization and immunohistochemistry. Here, we describe a strategy to rapidly and efficiently isolate ribosome-associated mRNA transcripts from any cell type in vivo. We have created a mouse line, called RiboTag, which carries an Rpl22 allele with a floxed wild-type C-terminal exon followed by an identical Cterminal exon that has three copies of the hemagglutinin (HA) epitope inserted before the stop codon. When the RiboTag mouse is crossed to a cell-type-specific Cre recombinase-expressing mouse, Cre recombinase activates the expression of epitopetagged ribosomal protein RPL22 HA , which is incorporated into actively translating polyribosomes. Immunoprecipitation of polysomes with a monoclonal antibody against HA yields ribosomeassociated mRNA transcripts from specific cell types. We demonstrate the application of this technique in brain using neuronspecific Cre recombinase-expressing mice and in testis using a Sertoli cell Cre recombinase-expressing mouse.gene profiling ͉ immunopreciptation ͉ mouse genetics
The density and dimensional changes of Nafion 117 H have been measured as a function of the water content. Swelling of Nafion commences at N (= mol ratio water to hydrogen ion) -1.9. Some anisotropy of dimensional changes was observed. Water-sorption isotherms obey Henry's Law with a nonzero intercept indicating some water retention. The diffusion coefficient of water in Nafion and the electrical conductivity of Nafion are strong functions of the water content. The latter is exploited for the development of a humidity sensor.
The ability to predict the impact of cis-regulatory sequence on gene expression would facilitate discovery in fundamental and applied biology. Here, we combine polysome profiling of a library of 280,000 randomized 5′ UTRs with deep learning to build a predictive model that relates human 5′ UTR sequence to translation. Together with a genetic algorithm, we use the model to engineer new 5′ UTRs that accurately direct specified levels of ribosome loading, providing the ability to tune sequences for optimal protein expression. We show that the same approach can be extended to chemically modified RNA, an important feature for applications in mRNA therapeutics and synthetic biology. We test 35,000 truncated human 5′ UTRs and 3,577 naturally occurring variants and show that the model predicts ribosome loading of these sequences. Finally, we provide evidence of 45 SNVs associated with human diseases that substantially change ribosome loading and thus may represent a molecular basis for disease. The sequence of the 5′ untranslated region (5′ UTR) is a primary determinant of translation efficiency 1,2. While many cis-regulatory elements within human 5′ UTRs have been characterized individually, the field still lacks a means to accurately predict protein expression from 5′ UTR sequence alone, limiting the ability to estimate the effects of genome-encoded variants and the ability to engineer 5′ UTRs for precise translation control. Massively parallel reporter assays (MPRAs)-methods that assess thousands to millions of sequence variants in a single experiment-coupled with machine learning have proven † Corresponding author. gseelig@uw.edu. Author contributions P.J.S and B.W. designed and performed experiments, performed data analysis and modeling, and wrote the manuscript. D.R. performed fluorescence validation experiments. V.P. and I.M. wrote the manuscript. D.R.M. helped design polysome profiling. G.S. designed experiments and wrote the manuscript.
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