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- Angles d'Ortoli, Thibault, et al.
(författare)
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Temperature Dependence of Hydroxymethyl Group Rotamer Populations in Cellooligomers
- 2015
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Ingår i: Journal of Physical Chemistry B. - : American Chemical Society (ACS). - 1520-6106 .- 1520-5207. ; 119:30, s. 9559-9570
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Tidskriftsartikel (refereegranskat)abstract
- Empirical force fields for computer simulations of carbohydrates are often implicitly assumed to be valid also at temperatures different from room temperature for which they were optimited: Herein, the temperature dependence of the hydroxymethyl group rotamer populations in short oligogaccharides is invegtigated using Molecular dynamics simulations and NMR spectroscopy. Two oligosaccharides, methyl beta-cellobioside and beta-cellotetraose were simulated using three different carbohydrate force fields (CHARMM C35, GLYCAM06, and GROMOS 56A(carbo)) in combination with different water models (SPC, SPC/E, and TIP3P) using replica exchange molecular dynamics simulations. For comparison, hydroxymethyl group rotamer populations were investigated for methyl beta-cellobioside and cellopentaose based- on measured NMR (3)J(H5,H6) coupling constants, in the latter case by using a chemical shift selective NMR-filter. Molecular dynamics simulations in combination with NMR spectroscopy show that the temperature dependence of the hydroxymethyl rotamer population in these short cellooligomers, in the range 263-344 K, generally becomes exaggerated in simulations when compared to experimental data, but also that it is dependent on simulation conditions, and most notably properties of the water model.
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| 4. |
- Bergenstråhle, Ludvig, et al.
(författare)
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Super-resolved spatial transcriptomics by deep data fusion
- 2022
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Ingår i: Nature Biotechnology. - : Nature Research. - 1087-0156 .- 1546-1696. ; 40:4, s. 476-479
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Tidskriftsartikel (refereegranskat)abstract
- Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.
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| 5. |
- Erickson, A, et al.
(författare)
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Spatially resolved clonal copy number alterations in benign and malignant tissue
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 608:7922, s. 360-
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Tidskriftsartikel (refereegranskat)abstract
- Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.
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- He, B., et al.
(författare)
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Integrating spatial gene expression and breast tumour morphology via deep learning
- 2020
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Ingår i: Nature Biomedical Engineering. - : Nature Research. - 2157-846X. ; 4:8, s. 827-834
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Tidskriftsartikel (refereegranskat)abstract
- Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the development of a deep learning algorithm for the prediction of local gene expression from haematoxylin-and-eosin-stained histopathology images using a new dataset of 30,612 spatially resolved gene expression data matched to histopathology images from 23 patients with breast cancer. We identified over 100 genes, including known breast cancer biomarkers of intratumoral heterogeneity and the co-localization of tumour growth and immune activation, the expression of which can be predicted from the histopathology images at a resolution of 100 µm. We also show that the algorithm generalizes well to The Cancer Genome Atlas and to other breast cancer gene expression datasets without the need for re-training. Predicting the spatially resolved transcriptome of a tissue directly from tissue images may enable image-based screening for molecular biomarkers with spatial variation.
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| 8. |
- Muus, Christoph, et al.
(författare)
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Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics
- 2021
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 27:3, s. 546-559
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Tidskriftsartikel (refereegranskat)abstract
- Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2(+)TMPRSS2(+) cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention. An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.
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- Vickovic, Sanja, et al.
(författare)
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High-definition spatial transcriptomics for in situ tissue profiling
- 2019
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Ingår i: Nature Methods. - : NATURE PUBLISHING GROUP. - 1548-7091 .- 1548-7105. ; 16:10, s. 987-
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Tidskriftsartikel (refereegranskat)abstract
- Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here, we developed high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. Each experiment recovers several hundred thousand transcriptcoupled spatial barcodes at 2-mu m resolution, as demonstrated in mouse brain and primary breast cancer. This opens the way to high-resolution spatial analysis of cells and tissues.
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