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- Baeza-Delgado, Carlos, et al.
(författare)
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Biological insertion of computationally designed short transmembrane segments
- 2016
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- The great majority of helical membrane proteins are inserted co-translationally into the ER membrane through a continuous ribosome-translocon channel. The efficiency of membrane insertion depends on transmembrane (TM) helix amino acid composition, the helix length and the position of the amino acids within the helix. In this work, we conducted a computational analysis of the composition and location of amino acids in transmembrane helices found in membrane proteins of known structure to obtain an extensive set of designed polypeptide segments with naturally occurring amino acid distributions. Then, using an in vitro translation system in the presence of biological membranes, we experimentally validated our predictions by analyzing its membrane integration capacity. Coupled with known strategies to control membrane protein topology, these findings may pave the way to de novo membrane protein design.
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2. |
- Miguel-Escalada, Irene, et al.
(författare)
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Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes
- 2019
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 51:7, s. 1137-1148
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Tidskriftsartikel (refereegranskat)abstract
- Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.
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3. |
- Wernersson, Erik, et al.
(författare)
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Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images
- 2024
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Ingår i: Nature Methods. - 1548-7091 .- 1548-7105.
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Tidskriftsartikel (refereegranskat)abstract
- Microscopy-based spatially resolved omic methods are transforming the life sciences. However, these methods rely on high numerical aperture objectives and cannot resolve crowded molecular targets, limiting the amount of extractable biological information. To overcome these limitations, here we develop Deconwolf, an open-source, user-friendly software for high-performance deconvolution of widefield fluorescence microscopy images, which efficiently runs on laptop computers. Deconwolf enables accurate quantification of crowded diffraction limited fluorescence dots in DNA and RNA fluorescence in situ hybridization images and allows robust detection of individual transcripts in tissue sections imaged with x20 air objectives. Deconvolution of in situ spatial transcriptomics images with Deconwolf increased the number of transcripts identified more than threefold, while the application of Deconwolf to images obtained by fluorescence in situ sequencing of barcoded Oligopaint probes drastically improved chromosome tracing. Deconwolf greatly facilitates the use of deconvolution in many bioimaging applications. Deconwolf is a computationally efficient and user-friendly software tool for fluorescence microscopy image deconvolution that improves the analysis of diverse fluorescence in situ hybridization methods and can handle large datasets.
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