| 1. |
- Kostallas, George
(författare)
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Intracellular systems for characterization and engineering of proteases and their substrates
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Over the years, the view on proteases as relatively non-specific protein degradation enzymes, mainly involved in food digestion and intracellular protein turnover, has shifted and they are now recognized as key regulators of many biological processes that determine the fate of a cell. Besides their biological role, proteases have emerged as important tools in various biotechnical, industrial and medical applications. At present, there are worldwide efforts made that aim at deciphering the biological role of proteases and understanding their mechanism of action in greater detail. In addition, with the growing demand of novel protease variants adapted to specific applications, protease engineering is attracting a lot of attention. With the vision of contributing to the field of protein science, we have developed a platform for the identification of site-specific proteolysis, consisting of two intracellular genetic assays; one fluorescence-based (Paper I) and one antibiotic resistance-based (Paper IV). More specifically, the assays take advantage of genetically encoded short-lived reporter substrates that upon cleavage by a coexpressed protease confer either increased whole-cell fluorescence or antibiotic resistance to the cells in proportion to the efficiency with which the substrates are processed. Thus, the fluorescence-based assay is highly suitable for high-throughput analysis of substrate processing efficiency by flow cytometry analysis and cell sorting, while the antibiotic resistance assay can be used to monitor and identify proteolysis through (competitive) growth in selective media. By using the highly sequence specific tobacco etch virus protease (TEVp) as a model in our systems, we could show that both allowed for (i) discrimination among closely related substrate peptides (Paper I & IV) and (ii) enrichment and identification of the best performing substrate-protease combination from a background of suboptimal variants (Paper I & IV). In addition, the fluorescence-based assay was used successfully to determine the substrate specificity of TEVp by flow cytometric screening of large combinatorial substrate libraries (Paper II), and in a separate study also used as one of several methods for the characterization of different TEVp mutants engineered for improved solubility (Paper III). We believe that our assays present a new and promising path forward for high-throughput substrate profiling of proteases, directed evolution of proteases and identification of protease inhibitors, which all are areas of great biological, biotechnical and medical interest.
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| 2. |
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| 3. |
- Asp, Michaela, et al.
(författare)
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A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart
- 2019
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Ingår i: Cell. - : CELL PRESS. - 0092-8674 .- 1097-4172. ; 179:7, s. 1647-
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Tidskriftsartikel (refereegranskat)abstract
- The process of cardiac morphogenesis in humans is incompletely understood. Its full characterization requires a deep exploration of the organ-wide orchestration of gene expression with a single-cell spatial resolution. Here, we present a molecular approach that reveals the comprehensive transcriptional landscape of cell types populating the embryonic heart at three developmental stages and that maps cell-type-specific gene expression to specific anatomical domains. Spatial transcriptomics identified unique gene profiles that correspond to distinct anatomical regions in each developmental stage. Human embryonic cardiac cell types identified by single-cell RNA sequencing confirmed and enriched the spatial annotation of embryonic cardiac gene expression. In situ sequencing was then used to refine these results and create a spatial subcellular map for the three developmental phases. Finally, we generated a publicly available web resource of the human developing heart to facilitate future studies on human cardiogenesis.
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| 4. |
- Asp, Michaela, et al.
(författare)
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An organ‐wide gene expression atlas of the developing human heart
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The human developing heart holds a greater proportion of stem-cell-like cells than the adult heart. However, it is not completely understood how these stem cells differentiate into various cardiac cell types. We have performed an organ-wide transcriptional landscape analysis of the developing heart to advance our understanding of cardiac morphogenesis in humans. Comprehensive spatial gene expression analyses identified distinct profiles that correspond not only to individual chamber compartments, but also distinctive regions within the outflow tract. Furthermore, the generated spatial expression reference maps facilitated the assignment of 3,787 human embryonic cardiac cells obtained from single-cell RNA-sequencing to an in situlocation. Through this approach we reveal that the outflow tract contains a wider range of cell types than the chambers, and that the epicardium expression profile can be traced to several cell types that are activated at different stages of development. We also provide a 3D spatial model of human embryonic cardiac cells to enable further studies of the developing human heart.
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| 5. |
- Baeckdahl, Jesper, et al.
(författare)
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Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin
- 2021
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 33:9, s. 1869-
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Tidskriftsartikel (refereegranskat)abstract
- The contribution of cellular heterogeneity and architecture to white adipose tissue (WAT) function is poorly understood. Herein, we combined spatially resolved transcriptional profiling with single-cell RNA sequencing and image analyses to map human WAT composition and structure. This identified 18 cell classes with unique propensities to form spatially organized homo-and heterotypic clusters. Of these, three constituted mature adipocytes that were similar in size, but distinct in their spatial arrangements and transcriptional profiles. Based on marker genes, we termed these Adipo(LEP), Adipo(PLIN), and Adipo(SAA). We confirmed, in independent datasets, that their respective gene profiles associated differently with both adipocyte and whole-body insulin sensitivity. Corroborating our observations, insulin stimulation in vivo by hyperinsulinemic-euglycemic clamp showed that only Adipo(PLIN) displayed a transcriptional response to insulin. Altogether, by mining this multimodal resource we identify that human WAT is composed of three classes of mature adipocytes, only one of which is insulin responsive.
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| 6. |
- Berglund, Emelie, et al.
(författare)
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Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.
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| 7. |
- Bhalla, Nayanika, et al.
(författare)
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Spatial transcriptomics of human placentas reveal distinct RNA patterns associated with morphology and preeclampsia
- 2023
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Ingår i: Placenta. - : Elsevier BV. - 0143-4004 .- 1532-3102. ; 139, s. 213-216
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Tidskriftsartikel (refereegranskat)abstract
- Spatial transcriptomics (ST) maps RNA level patterns within a tissue. This technology has not been previously applied to human placental tissue. We demonstrate analysis of human placental samples with ST. Unsupervised clustering revealed that distinct RNA patterns were found corresponding to different morphological structures. Additionally, when focusing upon terminal villi and hemoglobin associated structures, RNA levels differed between placentas from full term healthy pregnancies and those complicated by preeclampsia. The results from this study can provide a benchmark for future ST studies in placenta.
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| 8. |
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| 9. |
- Carlberg, Konstantin, et al.
(författare)
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Exploring inflammatory signatures in arthritic joint biopsies with Spatial Transcriptomics
- 2019
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Ingår i: Scientific Reports. - : NATURE PUBLISHING GROUP. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Lately it has become possible to analyze transcriptomic profiles in tissue sections with retained cellular context. We aimed to explore synovial biopsies from rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients, using Spatial Transcriptomics (ST) as a proof of principle approach for unbiased mRNA studies at the site of inflammation in these chronic inflammatory diseases. Synovial tissue biopsies from affected joints were studied with ST. The transcriptome data was subjected to differential gene expression analysis (DEA), pathway analysis, immune cell type identification using Xcell analysis and validation with immunohistochemistry (IHC). The ST technology allows selective analyses on areas of interest, thus we analyzed morphologically distinct areas of mononuclear cell infiltrates. The top differentially expressed genes revealed an adaptive immune response profile and T-B cell interactions in RA, while in SpA, the profiles implicate functions associated with tissue repair. With spatially resolved gene expression data, overlaid on high-resolution histological images, we digitally portrayed pre-selected cell types in silico. The RA displayed an overrepresentation of central memory T cells, while in SpA effector memory T cells were most prominent. Consequently, ST allows for deeper understanding of cellular mechanisms and diversity in tissues from chronic inflammatory diseases.
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| 10. |
- Carlberg, Konstantin, et al.
(författare)
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Integrated Single Cell and Spatial Transcriptomics Reveal Autoreactive Differentiated B Cells in Joints of Early Rheumatoid Arthritis
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Rheumatoid Arthritis (RA) is a prevalent autoimmune disease characterized by inflammation of peripheral joints. Patients can be subdivided by the presence or absence of Rheumatoid Factor and anti-citrullinated protein antibodies (ACPA) in their circulation. Inflammation of the joint tissue is associated with infiltration of leukocytes from the blood, which can result in generation of lymphoid structures composed of B and T cells. Previous studies have shown that both memory B cells and antibody-secreting plasma cells populate the rheumatic joint tissue when captured from established and often long-standing disease. However, it has remained unclear, whether these cells are autoreactive and whether the associated lymphoid structures are present at the site of inflammation already at the time of diagnosis. Here, we used an integrated single cell and spatial transcriptomic approach to study B and plasma cells in synovial tissue of ACPA- and ACPA+ RA patients at this early time point. We found evidence for T cell help to B cells and presence of memory B and plasma cell pools in ACPA- as well as in ACPA+ RA. Our results demonstrated common supportive microenvironments in both patient subgroups, clonal relationships between the memory B and plasma cell pools and autoreactivity within the plasma cell compartment. These findings challenge our understanding of the dynamics of local adaptive immune responses in the RA joint of ACPA- and ACPA+ patients at the time of diagnosis, with direct implications for B and T cell targeting therapies for both patient subgroups.
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| 11. |
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| 12. |
- Franzén, Lovisa, et al.
(författare)
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Spatially resolved transcriptomics of human and mouse fibrotic lung
- 2022
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Ingår i: European Respiratory Journal. - : European Respiratory Society (ERS). - 0903-1936 .- 1399-3003. ; 60
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by progressive and irreversible scarring of the lung tissue. Development of new efficacious and safe treatments is hampered by limited understanding of disease pathogenesis, lack of predictive preclinical models, and narrow therapeutic index of candidate drugs targeting complex biologies. Here, we tackle these aspects by generating spatially resolved transcriptomic maps of fibrotic lungs from clinical samples and a preclinical mouse model. We utilized the Visium platform to study parenchyma biopsies from four healthy lungs and regions of varying fibrotic severity from four IPF patient lungs. By mapping single cell RNA-seq data spatially, we were able to detect distinct fibroblast populations in different regions of the lesioned IPF lung, as well as the presence of various immune cell populations. To study lung fibrosis preclinically in vivo, the bleomycin mouse model is the most widely used alternative, although its translatability to human disease is disputed. Visium data from mouse lungs collected at two time points following bleomycin administration were generated, which allowed us to characterize the fibrotic lesions and inflammatory areas in their spatiotemporal context. In addition, mass spectrometry imaging was performed on adjacent tissue sections to provide paired spatial metabolomics. Herein, we have generated spatial maps of the lung fibrosis transcriptome from IPF lung biopsies and bleomycin-injured mouse lungs, providing an extensive resource to probe disease pathogenesis and animal model translatability.
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| 13. |
- Hardt, Uta, et al.
(författare)
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Integrated single cell and spatial transcriptomics reveal autoreactive differentiated B cells in joints of early rheumatoid arthritis
- 2022
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- B cells play a significant role in established Rheumatoid Arthritis (RA). However, it is unclear to what extent differentiated B cells are present in joint tissue already at the onset of disease. Here, we studied synovial biopsies (n = 8) captured from untreated patients at time of diagnosis. 3414 index-sorted B cells underwent RNA sequencing and paired tissue pieces were subjected to spatial transcriptomics (n = 4). We performed extensive bioinformatics analyses to dissect the local B cell composition. Select plasma cell immunoglobulin sequences were expressed as monoclonal antibodies and tested by ELISA. Memory and plasma cells were found irrespective of autoantibody status of the patients. Double negative memory B cells were prominent, but did not display a distinct transcriptional profile. The tissue architecture implicate both local B cell maturation via T cell help and plasma cell survival niches with a strong CXCL12-CXCR4 axis. The immunoglobulin sequence analyses revealed clonality between the memory B and plasma cell pools further supporting local maturation. One of the plasma cell-derived antibodies displayed citrulline autoreactivity, demonstrating local autoreactive plasma cell differentiation in joint biopsies captured from untreated early RA. Hence, plasma cell niches are not a consequence of chronic inflammation, but are already present at the time of diagnosis.
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| 14. |
- Larsson, Ludvig, et al.
(författare)
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Semla : a versatile toolkit for spatially resolved transcriptomics analysis and visualization
- 2023
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 39:10
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Tidskriftsartikel (refereegranskat)abstract
- SUMMARY: Spatially resolved transcriptomics technologies generate gene expression data with retained positional information from a tissue section, often accompanied by a corresponding histological image. Computational tools should make it effortless to incorporate spatial information into data analyses and present analysis results in their histological context. Here, we present semla, an R package for processing, analysis, and visualization of spatially resolved transcriptomics data generated by the Visium platform, that includes interactive web applications for data exploration and tissue annotation. AVAILABILITY AND IMPLEMENTATION: The R package semla is available on GitHub (https://github.com/ludvigla/semla), under the MIT License, and deposited on Zenodo (https://doi.org/10.5281/zenodo.8321645). Documentation and tutorials with detailed descriptions of usage can be found at https://ludvigla.github.io/semla/.
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| 15. |
- Llorens-Bobadilla, Enric, et al.
(författare)
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Solid-phase capture and profiling of open chromatin by spatial ATAC
- 2023
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Ingår i: Nature Biotechnology. - : Nature Research. - 1087-0156 .- 1546-1696. ; 41:8, s. 1085-1088
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Tidskriftsartikel (refereegranskat)abstract
- Current methods for epigenomic profiling are limited in their ability to obtain genome-wide information with spatial resolution. We introduce spatial ATAC, a method that integrates transposase-accessible chromatin profiling in tissue sections with barcoded solid-phase capture to perform spatially resolved epigenomics. We show that spatial ATAC enables the discovery of the regulatory programs underlying spatial gene expression during mouse organogenesis, lineage differentiation and in human pathology.
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| 16. |
- Massier, Lucas, et al.
(författare)
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An integrated single cell and spatial transcriptomic map of human white adipose tissue
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Single-cell studies of human white adipose tissue (WAT) provide insights into the specialized cell types in the tissue. Here the authors combine publicly available and newly generated high-resolution and bulk transcriptomic results from multiple human datasets to provide a comprehensive cellular map of white adipose tissue. To date, single-cell studies of human white adipose tissue (WAT) have been based on small cohort sizes and no cellular consensus nomenclature exists. Herein, we performed a comprehensive meta-analysis of publicly available and newly generated single-cell, single-nucleus, and spatial transcriptomic results from human subcutaneous, omental, and perivascular WAT. Our high-resolution map is built on data from ten studies and allowed us to robustly identify >60 subpopulations of adipocytes, fibroblast and adipogenic progenitors, vascular, and immune cells. Using these results, we deconvolved spatial and bulk transcriptomic data from nine additional cohorts to provide spatial and clinical dimensions to the map. This identified cell-cell interactions as well as relationships between specific cell subtypes and insulin resistance, dyslipidemia, adipocyte volume, and lipolysis upon long-term weight changes. Altogether, our meta-map provides a rich resource defining the cellular and microarchitectural landscape of human WAT and describes the associations between specific cell types and metabolic states.
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| 17. |
- Salmén, Fredrik, et al.
(författare)
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Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections
- 2018
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Ingår i: Nature Protocols. - : Nature Publishing Group. - 1754-2189 .- 1750-2799. ; 13:11, s. 2501-2534
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Tidskriftsartikel (refereegranskat)abstract
- Spatial resolution of gene expression enables gene expression events to be pinpointed to a specific location in biological tissue. Spatially resolved gene expression in tissue sections is traditionally analyzed using immunohistochemistry (IHC) or in situ hybridization (ISH). These technologies are invaluable tools for pathologists and molecular biologists; however, their throughput is limited to the analysis of only a few genes at a time. Recent advances in RNA sequencing (RNA-seq) have made it possible to obtain unbiased high-throughput gene expression data in bulk. Spatial Transcriptomics combines the benefits of traditional spatially resolved technologies with the massive throughput of RNA-seq. Here, we present a protocol describing how to apply the Spatial Transcriptomics technology to mammalian tissue. This protocol combines histological staining and spatially resolved RNA-seq data from intact tissue sections. Once suitable tissue-specific conditions have been established, library construction and sequencing can be completed in similar to 5-6 d. Data processing takes a few hours, with the exact timing dependent on the sequencing depth. Our method requires no special instruments and can be performed in any laboratory with access to a cryostat, microscope and next-generation sequencing.
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| 18. |
- Salmén, Fredrik, 1984-
(författare)
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Spatially resolved and single cell transcriptomics
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, massive parallel sequencing has revolutionized the field of biology and has provided us with a vast number of new discoveries in fields such as neurology, developmental biology and cancer research. A significant area is deciphering gene expression patterns, as well as other aspects of transcriptome information, such as the impact of splice variants and mutations on biological functions and disease development. By applying RNA-sequencing, one can extract this type of information in a large-scale manner. The most recent approaches include high-resolution techniques such as single cell sequencing and in situ methods in order to circumvent the problems with gene expression averaging in homogenized samples, and loss of spatial information.The research in this thesis is focused on the development of a novel genome-wide spatial transcriptomics method. The technique is used for analysis of intact tissue sections as well as single cells from solution, with the aim to combine gene expression and morphological information. In Paper I, the method is described in detail, and it is shown that the method is able to generate spatial high quality data from mouse olfactory bulb tissue sections (a part of the forebrain) as well as from tissue sections from breast cancer samples. In Paper III, we adapt the library preparation method in order to be able to execute it on a robotic workstation, thus increasing the reproducibility and the throughput, and decreasing the hands-on time. In Paper IV, we generate 3D-data from breast cancer samples by serial sectioning. We show that the gene expression can be highly variable along all three axes of a tumor, and we track pathways with specific spatial activity, as well as perform subtype classification with three-dimensional resolution. In Paper II, we present a high-throughput method for single cell transcriptomics of cells in solution. The method is based on the same type of solid surface capture as the tissue protocol described in Papers I, III and IV. Again, we show that we can generate high-quality gene expression data, and connect this to morphological characteristics of the analyzed single cells; both using cultured cells and samples from patients with leukemia.
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| 19. |
- Ståhl, Patrik, Dr.
(författare)
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Gene expression of single cells mapped in tissue sections
- 2024
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 625:7993, s. 38-39
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- A tool that tags individual cells in a tissue with a unique barcode means that the gene-expression profile of each cell can be plotted in its original location. This allows spatial information to be captured at single-cell resolution.
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| 20. |
- Ståhl, Patrik L., 1981-
(författare)
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Methods for Analyzing Genomes
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The human genome reference sequence has given us a two‐dimensional blueprint of our inherited code of life, but we need to employ modern‐day technology to expand our knowledge into a third dimension. Inter‐individual and intra‐individual variation has been shown to be larger than anticipated, and the mode of genetic regulation more complex. Therefore, the methods that were once used to explain our fundamental constitution are now used to decipher our differences. Over the past four years, throughput from DNA‐sequencing platforms has increased a thousand‐fold, bearing evidence of a rapid development in the field of methods used to study DNA and the genomes it constitutes. The work presented in this thesis has been carried out as an integrated part of this technological evolution, contributing to it, and applying the resulting solutions to answer difficult biological questions. Papers I and II describe a novel approach for microarray readout based on immobilization of magnetic particles, applicable to diagnostics. As benchmarked on canine mitochondrial DNA, and human genomic DNA from individuals with cystic fibrosis, it allows for visual interpretation of genotyping results without the use of machines or expensive equipment. Paper III outlines an automated and cost‐efficient method for enrichment and titration of clonally amplified DNA‐libraries on beads. The method uses fluorescent labeling and a flow‐cytometer to separate DNA‐beads from empty ones. At the same time the fraction of either bead type is recorded, and a titration curve can be generated. In paper IV we combined the highly discriminating multiplex genotyping of trinucleotide threading with the digital readout made possible by massively parallel sequencing. From this we were able to characterize the allelic distribution of 88 obesity related SNPs in a population of 462 individuals enrolled at a childhood obesity center. Paper V employs the throughput of present day DNA sequencingas it investigates deep into sun‐exposed skin to find clues on the effects of sunlight during the course of a summer holiday. The tumor suppressor p53 gene was targeted, only to find that despite its well‐documented involvement in the disease progression of cancers, an estimated 35,000 novel sun‐induced persistent p53 mutations are added and phenotypically tolerated in the skin of every individual every year. The last paper, VI, describes a novel approach for finding breast cancer biomarkers. In this translational study we used differential protein expression profiles and sequence capture to select and enrich for 52 candidate genes in DNA extracted from ten tumors. Two of the genes turned out to harbor protein‐altering mutations in multiple individuals.
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| 21. |
- Ståhl, Patrik, Dr., et al.
(författare)
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Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
- 2016
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Ingår i: Science. - : AMER ASSOC ADVANCEMENT SCIENCE. - 0036-8075 .- 1095-9203. ; 353:6294, s. 78-82
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of the pattern of proteins or messenger RNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call "spatial transcriptomics," that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.
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| 22. |
- 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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| 23. |
- Vickovic, Sanja, et al.
(författare)
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Three-dimensional spatial transcriptomics uncovers cell type dynamics in the rheumatoid arthritis synovium
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics to study local cellular interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-seq data coupled to quantitative and cell type-specific chemokine-driven dynamics at and around organized structures of infiltrating leukocyte cells in the synovium.
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| 24. |
- Vickovic, Sanja, et al.
(författare)
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Three-dimensional spatial transcriptomics uncovers cell type localizations in the human rheumatoid arthritis synovium
- 2022
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Ingår i: Communications Biology. - : Springer Nature. - 2399-3642. ; 5:1
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Tidskriftsartikel (refereegranskat)abstract
- The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis. Sanja Vickovic et al. use spatial transcriptomics to probe the local synovial tissue interactions in rheumatoid arthritis (RA) patients. Their results provide a valuable resource to understand the spatial organisation of cell populations in the synovium in the context of RA-associated inflammation.
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| 25. |
- Xu, Xuechun, et al.
(författare)
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Lokatt : a hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network
- 2023
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Ingår i: BMC Bioinformatics. - : Springer Nature. - 1471-2105. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundBasecalling long DNA sequences is a crucial step in nanopore-based DNA sequencing protocols. In recent years, the CTC-RNN model has become the leading basecalling model, supplanting preceding hidden Markov models (HMMs) that relied on pre-segmenting ion current measurements. However, the CTC-RNN model operates independently of prior biological and physical insights.ResultsWe present a novel basecaller named Lokatt: explicit duration Markov model and residual-LSTM network. It leverages an explicit duration HMM (EDHMM) designed to model the nanopore sequencing processes. Trained on a newly generated library with methylation-free Ecoli samples and MinION R9.4.1 chemistry, the Lokatt basecaller achieves basecalling performances with a median single read identity score of 0.930, a genome coverage ratio of 99.750%, on par with existing state-of-the-art structure when trained on the same datasets.ConclusionOur research underlines the potential of incorporating prior knowledge into the basecalling processes, particularly through integrating HMMs and recurrent neural networks. The Lokatt basecaller showcases the efficacy of a hybrid approach, emphasizing its capacity to achieve high-quality basecalling performance while accommodating the nuances of nanopore sequencing. These outcomes pave the way for advanced basecalling methodologies, with potential implications for enhancing the accuracy and efficiency of nanopore-based DNA sequencing protocols.
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| 26. |
- Yoosuf, Niyaz, et al.
(författare)
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Identification and transfer of spatial transcriptomics signatures for cancer diagnosis
- 2020
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Ingår i: Breast Cancer Research. - : BioMed Central. - 1465-5411 .- 1465-542X. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Distinguishing ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC) regions in clinical biopsies constitutes a diagnostic challenge. Spatial transcriptomics (ST) is an in situ capturing method, which allows quantification and visualization of transcriptomes in individual tissue sections. In the past, studies have shown that breast cancer samples can be used to study their transcriptomes with spatial resolution in individual tissue sections. Previously, supervised machine learning methods were used in clinical studies to predict the clinical outcomes for cancer types. Methods: We used four publicly available ST breast cancer datasets from breast tissue sections annotated by pathologists as non-malignant, DCIS, or IDC. We trained and tested a machine learning method (support vector machine) based on the expert annotation as well as based on automatic selection of cell types by their transcriptome profiles. Results: We identified expression signatures for expert annotated regions (non-malignant, DCIS, and IDC) and build machine learning models. Classification results for 798 expression signature transcripts showed high coincidence with the expert pathologist annotation for DCIS (100%) and IDC (96%). Extending our analysis to include all 25,179 expressed transcripts resulted in an accuracy of 99% for DCIS and 98% for IDC. Further, classification based on an automatically identified expression signature covering all ST spots of tissue sections resulted in prediction accuracy of 95% for DCIS and 91% for IDC. Conclusions: This concept study suggest that the ST signatures learned from expert selected breast cancer tissue sections can be used to identify breast cancer regions in whole tissue sections including regions not trained on. Furthermore, the identified expression signatures can classify cancer regions in tissue sections not used for training with high accuracy. Expert-generated but even automatically generated cancer signatures from ST data might be able to classify breast cancer regions and provide clinical decision support for pathologists in the future.
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