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Publications (8 of 8) Show all publications
Vickovic, S., Eraslan, G., Salmen, F., Klughammer, J., Stenbeck, L., Schapiro, D., . . . Ståhl, P. (2019). High-definition spatial transcriptomics for in situ tissue profiling. Nature Methods, 16(10), 987-+
Open this publication in new window or tab >>High-definition spatial transcriptomics for in situ tissue profiling
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2019 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 16, no 10, p. 987-+Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-262787 (URN)10.1038/s41592-019-0548-y (DOI)000488225900027 ()31501547 (PubMedID)2-s2.0-85072716890 (Scopus ID)
Note

QC 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
Maniatis, S., Aijo, T., Vickovic, S., Braine, C., Kang, K., Mollbrink, A., . . . Phatnani, H. (2019). Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis. Science, 364(6435), 89-+
Open this publication in new window or tab >>Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis
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2019 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 364, no 6435, p. 89-+Article in journal (Refereed) Published
Abstract [en]

Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervation of skeletal muscle as a consequence of motor neuron degeneration. Interactions between motor neurons and glia contribute to motor neuron loss, but the spatiotemporal ordering of molecular events that drive these processes in intact spinal tissue remains poorly understood. Here, we use spatial transcriptomics to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients, to characterize the underlying molecular mechanisms in ALS. We identify pathway dynamics, distinguish regional differences between microglia and astrocyte populations at early time points, and discern perturbations in several transcriptional pathways shared between murine models of ALS and human postmortem spinal cords.

Place, publisher, year, edition, pages
AMER ASSOC ADVANCEMENT SCIENCE, 2019
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-251500 (URN)10.1126/science.aav9776 (DOI)000463585700040 ()30948552 (PubMedID)2-s2.0-85064324686 (Scopus ID)
Note

QC 20190515

Available from: 2019-05-15 Created: 2019-05-15 Last updated: 2019-05-15Bibliographically approved
Salmén, F., Ståhl, P., Mollbrink, A., Navarro Fernandez, J. C., Vickovic, S., Frisen, J. & Lundeberg, J. (2018). Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections. Nature Protocols, 13(11), 2501-2534
Open this publication in new window or tab >>Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections
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2018 (English)In: Nature Protocols, ISSN 1754-2189, E-ISSN 1750-2799, Vol. 13, no 11, p. 2501-2534Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-239078 (URN)10.1038/s41596-018-0045-2 (DOI)000448980400004 ()30353172 (PubMedID)2-s2.0-85055531492 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationSwedish Research CouncilSwedish Foundation for Strategic Research Swedish Cancer SocietyTorsten Söderbergs stiftelseÅke Wiberg FoundationRagnar Söderbergs stiftelse
Note

QC 20181121

Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-05-17Bibliographically approved
Berglund, E., Maaskola, J., Schultz, N., Friedrich, S., Marklund, M., Bergenstrahle, J., . . . Lundeberg, J. (2018). Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity. Nature Communications, 9, Article ID 2419.
Open this publication in new window or tab >>Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity
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2018 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 2419Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2018
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-231699 (URN)10.1038/s41467-018-04724-5 (DOI)000435650800010 ()29925878 (PubMedID)2-s2.0-85048864922 (Scopus ID)
Note

QC 20180823

Available from: 2018-08-23 Created: 2018-08-23 Last updated: 2018-08-23Bibliographically approved
Asp, M., Salmen, F., Stahl, P. L., Vickovic, S., Felldin, U., Lofling, M., . . . Lundeberg, J. (2017). Spatial detection of fetal marker genes expressed at low level in adult human heart tissue. Scientific Reports, 7, Article ID 12941.
Open this publication in new window or tab >>Spatial detection of fetal marker genes expressed at low level in adult human heart tissue
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 12941Article in journal (Refereed) Published
Abstract [en]

Heart failure is a major health problem linked to poor quality of life and high mortality rates. Hence, novel biomarkers, such as fetal marker genes with low expression levels, could potentially differentiate disease states in order to improve therapy. In many studies on heart failure, cardiac biopsies have been analyzed as uniform pieces of tissue with bulk techniques, but this homogenization approach can mask medically relevant phenotypes occurring only in isolated parts of the tissue. This study examines such spatial variations within and between regions of cardiac biopsies. In contrast to standard RNA sequencing, this approach provides a spatially resolved transcriptome- and tissue-wide perspective of the adult human heart, and enables detection of fetal marker genes expressed by minor subpopulations of cells within the tissue. Analysis of patients with heart failure, with preserved ejection fraction, demonstrated spatially divergent expression of fetal genes in cardiac biopsies.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2017
National Category
Genetics
Identifiers
urn:nbn:se:kth:diva-217038 (URN)10.1038/s41598-017-13462-5 (DOI)000412781300009 ()29021611 (PubMedID)2-s2.0-85031126431 (Scopus ID)
Note

QC 20171101

Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2018-10-01Bibliographically approved
Carlberg, K., Vickovic, S., Ståhl, P., Salmén, F., Korotkova, M., Malmstrom, V. & Lundeberg, J. (2017). TRANSCRIPTOME VISUALISATION OF THE INFLAMED RHEUMATOID ARTHRITIS JOINT. Paper presented at 37th European Workshop on Rheumatology Research (EWRR), MAR 02-04, 2017, Athens, GREECE. Annals of the Rheumatic Diseases, 76, A58-A59
Open this publication in new window or tab >>TRANSCRIPTOME VISUALISATION OF THE INFLAMED RHEUMATOID ARTHRITIS JOINT
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2017 (English)In: Annals of the Rheumatic Diseases, ISSN 0003-4967, E-ISSN 1468-2060, Vol. 76, p. A58-A59Article in journal (Refereed) Published
Place, publisher, year, edition, pages
BMJ Publishing Group Ltd, 2017
National Category
Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:kth:diva-216641 (URN)10.1136/annrheumdis-2016-211052.16 (DOI)000411783100085 ()
Conference
37th European Workshop on Rheumatology Research (EWRR), MAR 02-04, 2017, Athens, GREECE
Note

QC 20171101

Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2017-11-01Bibliographically approved
Vickovic, S., Stahl, P. L., Salmen, F., Giatrellis, S., Westholm, J. O., Mollbrink, A., . . . Lundeberg, J. (2016). Massive and parallel expression profiling using microarrayed single-cell sequencing. Nature Communications, 7, Article ID 13182.
Open this publication in new window or tab >>Massive and parallel expression profiling using microarrayed single-cell sequencing
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2016 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 7, article id 13182Article in journal (Refereed) Published
Abstract [en]

Single-cell transcriptome analysis overcomes problems inherently associated with averaging gene expression measurements in bulk analysis. However, single-cell analysis is currently challenging in terms of cost, throughput and robustness. Here, we present a method enabling massive microarray-based barcoding of expression patterns in single cells, termed MASC-seq. This technology enables both imaging and high-throughput single-cell analysis, characterizing thousands of single-cell transcriptomes per day at a low cost (0.13 USD/cell), which is two orders of magnitude less than commercially available systems. Our novel approach provides data in a rapid and simple way. Therefore, MASC-seq has the potential to accelerate the study of subtle clonal dynamics and help provide critical insights into disease development and other biological processes.

Place, publisher, year, edition, pages
Nature Publishing Group, 2016
National Category
Cell Biology
Identifiers
urn:nbn:se:kth:diva-196395 (URN)10.1038/ncomms13182 (DOI)000385549400001 ()2-s2.0-84991694317 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationSwedish Cancer SocietySwedish Foundation for Strategic Research Swedish Research CouncilTorsten Söderbergs stiftelse
Note

QC 20161128

Available from: 2016-11-28 Created: 2016-11-14 Last updated: 2017-11-29Bibliographically approved
Salmén, F., Vickovic, S., Stenbeck, L., Vallon-Christersson, J., Ehinger, A., Häkkinen, J., . . . Lundeberg, J.Three-dimensional spatial transcriptomics analysis for classification of breast cancer.
Open this publication in new window or tab >>Three-dimensional spatial transcriptomics analysis for classification of breast cancer
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(English)Manuscript (preprint) (Other academic)
National Category
Biochemistry and Molecular Biology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-200367 (URN)
Projects
Spatially resolved and single cell transcriptomics
Note

QC 20170125

Available from: 2017-01-25 Created: 2017-01-25 Last updated: 2017-01-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0985-9885

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