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Publications (10 of 20) Show all publications
Sonavane, S., Hassan, S., Chatterjee, U., Soler, L., Holm, L., Mollbrink, A., . . . Rising, A. (2024). Origin, structure, and composition of the spider major ampullate silk fiber revealed by genomics, proteomics, and single-cell and spatial transcriptomics. Science Advances, 10(33)
Open this publication in new window or tab >>Origin, structure, and composition of the spider major ampullate silk fiber revealed by genomics, proteomics, and single-cell and spatial transcriptomics
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2024 (English)In: Science Advances, E-ISSN 2375-2548, Vol. 10, no 33Article in journal (Refereed) Published
Abstract [en]

Spiders produce nature’s toughest fiber using renewable components at ambient temperatures and with water as solvent, making it highly interesting to replicate for the materials industry. Despite this, much remains to be understood about the bioprocessing and composition of spider silk fibers. Here, we identify 18 proteins that make up the spiders’ strongest silk type, the major ampullate fiber. Single-cell RNA sequencing and spatial transcriptomics revealed that the secretory epithelium of the gland harbors six cell types. These cell types are confined to three distinct glandular zones that produce specific combinations of silk proteins. Image analysis of histological sections showed that the secretions from the three zones do not mix, and proteomics analysis revealed that these secretions form layers in the final fiber. Using a multi-omics approach, we provide substantial advancements in the understanding of the structure and function of the major ampullate silk gland as well as of the architecture and composition of the fiber it produces.

Place, publisher, year, edition, pages
American Association for the Advancement of Science (AAAS), 2024
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-352769 (URN)10.1126/sciadv.adn0597 (DOI)001293053700005 ()39141739 (PubMedID)2-s2.0-85201353456 (Scopus ID)
Note

QC 20240905

Available from: 2024-09-05 Created: 2024-09-05 Last updated: 2024-09-05Bibliographically approved
Rájová, J., Davidsson, M., Avallone, M., Hartnor, M., Aldrin-Kirk, P., Cardoso, T., . . . Björklund, T. (2023). Deconvolution of spatial sequencing provides accurate characterization of hESC-derived DA transplants in vivo. Molecular therapy. Methods & clinical development, 29, 381-394
Open this publication in new window or tab >>Deconvolution of spatial sequencing provides accurate characterization of hESC-derived DA transplants in vivo
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2023 (English)In: Molecular therapy. Methods & clinical development, ISSN 2399-6951, E-ISSN 2329-0501, Vol. 29, p. 381-394Article in journal (Refereed) Published
Abstract [en]

Cell therapy for Parkinson's disease has experienced substantial growth in the past decades with several ongoing clinical trials. Despite increasing refinement of differentiation protocols and standardization of the transplanted neural precursors, the transcriptomic analysis of cells in the transplant after its full maturation in vivo has not been thoroughly investigated. Here, we present spatial transcriptomics analysis of fully differentiated grafts in their host tissue. Unlike earlier transcriptomics analyses using single-cell technologies, we observe that cells derived from human embryonic stem cells (hESCs) in the grafts adopt mature dopaminergic signatures. We show that the presence of phenotypic dopaminergic genes, which were found to be differentially expressed in the transplants, is concentrated toward the edges of the grafts, in agreement with the immunohistochemical analyses. Deconvolution shows dopamine neurons being the dominating cell type in many features beneath the graft area. These findings further support the preferred environmental niche of TH-positive cells and confirm their dopaminergic phenotype through the presence of multiple dopaminergic markers.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
deconvolution, differentiation, disease models, Parkinson's disease, single-cell sequencing, spatial transcriptomics, stem cells, transplantation
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-331560 (URN)10.1016/j.omtm.2023.04.008 (DOI)001042367600001 ()37251982 (PubMedID)2-s2.0-85159628613 (Scopus ID)
Note

QC 20230711

Available from: 2023-07-11 Created: 2023-07-11 Last updated: 2023-08-18Bibliographically approved
Lebrigand, K., Bergenstråhle, J., Thrane, K., Mollbrink, A., Meletis, K., Barbry, P., . . . Lundeberg, J. (2023). The spatial landscape of gene expression isoforms in tissue sections. Nucleic Acids Research, 51(8)
Open this publication in new window or tab >>The spatial landscape of gene expression isoforms in tissue sections
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2023 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 51, no 8Article in journal (Refereed) Published
Abstract [en]

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource, where isoform expression and RNA editing can be visualized in a spatial context.

Place, publisher, year, edition, pages
Oxford University Press (OUP), 2023
National Category
Genetics and Genomics
Identifiers
urn:nbn:se:kth:diva-328093 (URN)10.1093/nar/gkad169 (DOI)000952958700001 ()36928528 (PubMedID)2-s2.0-85204494245 (Scopus ID)
Note

QC 20230602

Available from: 2023-06-02 Created: 2023-06-02 Last updated: 2025-05-27Bibliographically approved
Kaufmann, M., Schaupp, A.-L. -., Sun, R., Coscia, F., Dendrou, C. A., Cortes, A., . . . Fugger, L. (2022). Identification of early neurodegenerative pathways in progressive multiple sclerosis. Nature Neuroscience, 25(7), 944-955
Open this publication in new window or tab >>Identification of early neurodegenerative pathways in progressive multiple sclerosis
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2022 (English)In: Nature Neuroscience, ISSN 1097-6256, E-ISSN 1546-1726, Vol. 25, no 7, p. 944-955Article in journal (Refereed) Published
Abstract [en]

Progressive multiple sclerosis (MS) is characterized by unrelenting neurodegeneration, which causes cumulative disability and is refractory to current treatments. Drug development to prevent disease progression is an urgent clinical need yet is constrained by an incomplete understanding of its complex pathogenesis. Using spatial transcriptomics and proteomics on fresh-frozen human MS brain tissue, we identified multicellular mechanisms of progressive MS pathogenesis and traced their origin in relation to spatially distributed stages of neurodegeneration. By resolving ligand–receptor interactions in local microenvironments, we discovered defunct trophic and anti-inflammatory intercellular communications within areas of early neuronal decline. Proteins associated with neuronal damage in patient samples showed mechanistic concordance with published in vivo knockdown and central nervous system (CNS) disease models, supporting their causal role and value as potential therapeutic targets in progressive MS. Our findings provide a new framework for drug development strategies, rooted in an understanding of the complex cellular and signaling dynamics in human diseased tissue that facilitate this debilitating disease. 

Place, publisher, year, edition, pages
Springer Nature, 2022
Keywords
proteome, transcriptome, animal experiment, animal model, antiinflammatory activity, Article, brain tissue, cell communication, cell interaction, central nervous system disease, cohort analysis, controlled study, degenerative disease, deterioration, disease course, disease model, drug targeting, female, gene knockdown, human, human tissue, in vivo study, male, microenvironment, mouse, multiple sclerosis, nerve cell, nerve degeneration, nonhuman, pathogenesis, protein interaction, proteomics, spatial analysis, transcriptomics, complication, disease exacerbation, metabolism, pathology, Central Nervous System Diseases, Disease Progression, Humans, Neurons
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-324939 (URN)10.1038/s41593-022-01097-3 (DOI)000813711500003 ()35726057 (PubMedID)2-s2.0-85132570612 (Scopus ID)
Note

QC 20230327

Available from: 2023-03-27 Created: 2023-03-27 Last updated: 2023-03-27Bibliographically approved
Venet, D., Wang, X., Dupont, F., Rouas, G., Stenbeck, L., Mollbrink, A., . . . Sotiriou, C. (2021). Contribution of the tumor and stroma compartments for TNBC molecular classification using spatial transcriptomics analysis. Cancer Research, 81(13)
Open this publication in new window or tab >>Contribution of the tumor and stroma compartments for TNBC molecular classification using spatial transcriptomics analysis
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2021 (English)In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 81, no 13Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
AMER ASSOC CANCER RESEARCH, 2021
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-300866 (URN)000680263505468 ()
Note

QC 20210928

Available from: 2021-09-28 Created: 2021-09-28 Last updated: 2022-06-25Bibliographically approved
Villacampa, E. G., Larsson, L., Mirzazadeh, R., Kvastad, L., Andersson, A., Mollbrink, A., . . . Lundeberg, J. (2021). Genome-wide spatial expression profiling in formalin-fixed tissues. Cell Genomics, 1(3), Article ID 100065.
Open this publication in new window or tab >>Genome-wide spatial expression profiling in formalin-fixed tissues
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2021 (English)In: Cell Genomics, E-ISSN 2666-979X, Vol. 1, no 3, article id 100065Article in journal (Refereed) Published
Abstract [en]

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3′ end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.

Place, publisher, year, edition, pages
Elsevier BV, 2021
Keywords
COVID-19, FFPE, genome-wide, mouse brain, organoids, ovarian carcinosarcoma, PFA, SARS-CoV-2, spatial transcriptomics, Visium
National Category
Cancer and Oncology Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-331727 (URN)10.1016/j.xgen.2021.100065 (DOI)2-s2.0-85126047493 (Scopus ID)
Note

QC 20230714

Available from: 2023-07-14 Created: 2023-07-14 Last updated: 2024-01-08Bibliographically approved
Wang, X., Venet, D., Dupont, F., Rouas, G., Stenberg, L., Mollbrink, A., . . . Sotiriou, C. (2021). Recapitulating spatial tumor morphology using automated classifier in triple negative breast cancer. Cancer Research, 81(13)
Open this publication in new window or tab >>Recapitulating spatial tumor morphology using automated classifier in triple negative breast cancer
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2021 (English)In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 81, no 13Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
AMER ASSOC CANCER RESEARCH, 2021
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-300867 (URN)000680263502286 ()
Note

QC 20210928

Available from: 2021-09-28 Created: 2021-09-28 Last updated: 2022-06-25Bibliographically approved
Hildebrandt, F., Andersson, A., Saarenpää, S., Larsson, L., Van Hul, N., Kanatani, S., . . . Ankarklev, J. (2021). Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the mouse liver. Nature Communications, 12(1), Article ID 7046.
Open this publication in new window or tab >>Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the mouse liver
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2021 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 12, no 1, article id 7046Article in journal (Refereed) Published
Abstract [en]

Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology. Global transcriptional differences across lobular units in the liver remain unknown. Here the authors perform spatial transcriptomics of liver tissue to delineate transcriptional differences in physical space, confirm lobular zonation along transcriptional gradients and suggest the presence of previously uncharacterized structures within liver tissue.

Place, publisher, year, edition, pages
Springer Nature, 2021
National Category
Cancer and Oncology Cell and Molecular Biology Biochemistry Molecular Biology
Identifiers
urn:nbn:se:kth:diva-306588 (URN)10.1038/s41467-021-27354-w (DOI)000727618000025 ()34857782 (PubMedID)2-s2.0-85120918294 (Scopus ID)
Note

QC 20211220

Available from: 2021-12-20 Created: 2021-12-20 Last updated: 2025-02-20Bibliographically approved
Kvastad, L., Carlberg, K., Larsson, L., Villacampa, E. G., Stuckey, A., Stenbeck, L., . . . Lundeberg, J. (2021). The spatial RNA integrity number assay for in situ evaluation of transcriptome quality. Communications Biology, 4(1), Article ID 57.
Open this publication in new window or tab >>The spatial RNA integrity number assay for in situ evaluation of transcriptome quality
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2021 (English)In: Communications Biology, E-ISSN 2399-3642, Vol. 4, no 1, article id 57Article in journal (Refereed) Published
Abstract [en]

The RNA integrity number (RIN) is a frequently used quality metric to assess the completeness of rRNA, as a proxy for the corresponding mRNA in a tissue. Current methods operate at bulk resolution and provide a single average estimate for the whole sample. Spatial transcriptomics technologies have emerged and shown their value by placing gene expression into a tissue context, resulting in transcriptional information from all tissue regions. Thus, the ability to estimate RNA quality in situ has become of utmost importance to overcome the limitation with a bulk rRNA measurement. Here we show a new tool, the spatial RNA integrity number (sRIN) assay, to assess the rRNA completeness in a tissue wide manner at cellular resolution. We demonstrate the use of sRIN to identify spatial variation in tissue quality prior to more comprehensive spatial transcriptomics workflows. Kvastad et al. develop the spatial RNA Integrity Number (sRIN) assay that evaluates the RNA integrity at cellular resolution. This method improves the resolution of a similar method called the RNA Integrity Number (RIN), demonstrating spatial variation in the quality of RNA samples.

Place, publisher, year, edition, pages
Springer Nature, 2021
National Category
Biochemistry Molecular Biology
Identifiers
urn:nbn:se:kth:diva-289901 (URN)10.1038/s42003-020-01573-1 (DOI)000608285700015 ()33420318 (PubMedID)2-s2.0-85098933855 (Scopus ID)
Note

QC 20210212

Available from: 2021-02-12 Created: 2021-02-12 Last updated: 2025-02-20Bibliographically approved
Ji, A. L., Rubin, A. J., Thrane, K., Jiang, S., Reynolds, D. L., Meyers, R. M., . . . Khavari, P. A. (2020). Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma. Cell, 182(2), 497-+
Open this publication in new window or tab >>Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma
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2020 (English)In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 182, no 2, p. 497-+Article in journal (Refereed) Published
Abstract [en]

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.

Place, publisher, year, edition, pages
Cell Press, 2020
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-279217 (URN)10.1016/j.cell.2020.05.039 (DOI)000552745000018 ()32579974 (PubMedID)2-s2.0-85087696271 (Scopus ID)
Note

QC 20200818

Available from: 2020-08-18 Created: 2020-08-18 Last updated: 2022-06-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7005-3050

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