Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.
Project description:The conceptual picture of an extratropical cyclone typically includes a cold front and a dry intrusion (DI) behind it. By objectively identifying fronts and DIs in ECMWF ERA-Interim data for 1979-2014, Part I quantified the climatological relationship between cold fronts and DIs. Driven by the finding that front intensity and frontal precipitation are enhanced in the presence of DIs, here we employ a front-centred perspective to focus on the dynamical and thermodynamical environment of cold fronts with and without DIs in the Northern Hemisphere winter. Distinguishing between trailing fronts (that connect to a parent cyclone) and isolated fronts, examples of DIs behind each type illustrate the baroclinic environment of the trailing front, and the lack of strong temperature gradients across the isolated front. Composite analyses of North Atlantic and North Pacific fronts outline the major differences in the presence of DIs, compared to similar fronts but without DIs in their vicinity. The magnitude and spatial structure of the modification by DIs depends on the front intensity. Yet, generally with DIs, trailing fronts occur with stronger SLP dipole, deeper upper-tropospheric trough, stronger 10-m wind gusts, enhanced ocean sensible and latent heat fluxes in the cyclone cold sector and heavier precipitation. Isolated weak fronts exhibit similar behaviour, with different spatial structure. This study highlights the central role of DIs for shaping the variability of fronts and their associated environment and impact.
Project description:Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.
Project description:Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.
Project description:A defining characteristic of quiescent cells is their low level of gene activity compared to growing cells. Using a yeast model for cellular quiescence, we compared the genome-wide profiles of multiple histone modifications between growing and quiescent cells, and correlated these profiles with the presence of RNA polymerase II and its transcripts. Quiescent cells retained several forms of histone methylation normally associated with transcriptionally active chromatin and had many transcripts in common with growing cells. Quiescent cells also contained high levels of RNA polymerase II, but only low levels of the canonical initiating and elongating forms of the polymerase. The data suggest that the transcript and histone methylation marks in quiescent cells were either inherited from growing cells or established early during the development of quiescence and then retained in this non-growing cell population. This might ensure that quiescent cells can rapidly adapt to a changing environment to resume growth. RNA-seq analysis was performed in yeast Log-phase cells and purified Quiescent yeast cells and the transcriptomes in each were compared. The RNA data was correlated with genomic RNA polymerase II and histone H3 methylation occupancy profiles in the log and quiescent cells.
Project description:Through high throughput compound screening, we've identified compounds that induce the expression of fetal hemoglobin. This study contains CUT&RUN data of a novel target, WIZ.