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  • 1.
    Asp, Michaela
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Salmen, Fredrik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Stahl, Patrik L.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Felldin, Ulrika
    Lofling, Marie
    Navarro, Jose Fernandez
    Maaskola, Jonas
    Eriksson, Maria J.
    Persson, Bengt
    Corbascio, Matthias
    Persson, Hans
    Linde, Cecilia
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatial detection of fetal marker genes expressed at low level in adult human heart tissue2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 12941Article in journal (Refereed)
    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.

  • 2.
    Berglund, Emelie
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Maaskola, Jonas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Schultz, Niklas
    Friedrich, Stefanie
    Marklund, Maja
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Bergenstrahle, Joseph
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Tarish, Firas
    Tanoglidi, Anna
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Larsson, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Salmén, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ogris, Christoph
    Wallenborg, Karolina
    Lagergren, Jens
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Ståhl, Patrik
    Sonnhammer, Erik
    Helleday, Thomas
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity2018In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 2419Article in journal (Refereed)
    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.

  • 3.
    Carlberg, Konstantin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ståhl, Patrik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Salmén, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Korotkova, Marina
    Malmstrom, Vivianne
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    TRANSCRIPTOME VISUALISATION OF THE INFLAMED RHEUMATOID ARTHRITIS JOINT2017In: Annals of the Rheumatic Diseases, ISSN 0003-4967, E-ISSN 1468-2060, Vol. 76, p. A58-A59Article in journal (Refereed)
  • 4.
    Dezfouli, Mahya
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Iglesias, Maria Jesus
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ahmadian, Afshin
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Magnetic bead assisted labeling of antibodies at nanogram scale2014In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 14, no 1, p. 14-18Article in journal (Refereed)
    Abstract [en]

    There are currently several initiatives that aim to produce binding reagents for proteome-wide analysis. To enable protein detection, visualization, and target quantification, covalent coupling of reporter molecules to antibodies is essential. However, current labeling protocols recommend considerable amount of antibodies, require antibody purity and are not designed for automation. Given that small amounts of antibodies are often sufficient for downstream analysis, we developed a labeling protocol that combines purification and modification of antibodies at submicrogram quantities. With the support of magnetic microspheres, automated labeling of antibodies in parallel using biotin or fluorescent dyes was achieved.

  • 5.
    Dezfouli, Mahya
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Iglesias, Maria Jesus
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ahmadian, Afshin
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Parallel barcoding of antibodies for DNA-assisted proteomics2014In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 14, no 21-22, p. 2432-2436Article in journal (Refereed)
    Abstract [en]

    DNA-assisted proteomics technologies enable ultra-sensitive measurements in multiplex format using DNA-barcoded affinity reagents. Although numerous antibodies are available, nowadays targeting nearly the complete human proteome, the majority is not accessible at the quantity, concentration, or purity recommended for most bio-conjugation protocols. Here, we introduce a magnetic bead-assisted DNA-barcoding approach, applicable for several antibodies in parallel, as well as reducing required reagents quantities up to a thousand-fold. The success of DNA-barcoding and retained functionality of antibodies were demonstrated in sandwich immunoassays and standard quantitative Immuno-PCR assays. Specific DNA-barcoding of antibodies for multiplex applications was presented on suspension bead arrays with read-out on a massively parallel sequencing platform in a procedure denoted Immuno-Sequencing. Conclusively, human plasma samples were analyzed to indicate the functionality of barcoded antibodies in intended proteomics applications.

  • 6.
    Giacomello, Stefania
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Stockholm University, Sweden.
    Salmén, Fredrik
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Terebieniec, B. K.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navarro, J. F.
    Alexeyenko, A.
    Reimegård, J.
    McKee, Lauren S.
    KTH, School of Biotechnology (BIO), Glycoscience.
    Mannapperuma, C.
    Bulone, Vincent
    KTH, School of Biotechnology (BIO), Glycoscience. University of Adelaide, Australia.
    Ståhl, P. L.
    Sundström, J. F.
    Street, N. R.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatially resolved transcriptome profiling in model plant species2017In: Nature Plants, ISSN 2055-0278, Vol. 3, article id 17061Article in journal (Refereed)
    Abstract [en]

    Understanding complex biological systems requires functional characterization of specialized tissue domains. However, existing strategies for generating and analysing high-throughput spatial expression profiles were developed for a limited range of organisms, primarily mammals. Here we present the first available approach to generate and study high-resolution, spatially resolved functional profiles in a broad range of model plant systems. Our process includes high-throughput spatial transcriptome profiling followed by spatial gene and pathway analyses. We first demonstrate the feasibility of the technique by generating spatial transcriptome profiles from model angiosperms and gymnosperms microsections. In Arabidopsis thaliana we use the spatial data to identify differences in expression levels of 141 genes and 189 pathways in eight inflorescence tissue domains. Our combined approach of spatial transcriptomics and functional profiling offers a powerful new strategy that can be applied to a broad range of plant species, and is an approach that will be pivotal to answering fundamental questions in developmental and evolutionary biology.

  • 7. Grskovic, Branka
    et al.
    Zrnec, Dario
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Popovic, Maja
    Mrsic, Gordan
    DNA methylation: the future of crime scene investigation?2013In: Molecular Biology Reports, ISSN 0301-4851, E-ISSN 1573-4978, Vol. 40, no 7, p. 4349-4360Article in journal (Refereed)
    Abstract [en]

    Proper detection and subsequent analysis of biological evidence is crucial for crime scene reconstruction. The number of different criminal acts is increasing rapidly. Therefore, forensic geneticists are constantly on the battlefield, trying hard to find solutions how to solve them. One of the essential defensive lines in the fight against the invasion of crime is relying on DNA methylation. In this review, the role of DNA methylation in body fluid identification and other DNA methylation applications are discussed. Among other applications of DNA methylation, age determination of the donor of biological evidence, analysis of the parent-of-origin specific DNA methylation markers at imprinted loci for parentage testing and personal identification, differentiation between monozygotic twins due to their different DNA methylation patterns, artificial DNA detection and analyses of DNA methylation patterns in the promoter regions of circadian clock genes are the most important ones. Nevertheless, there are still a lot of open chapters in DNA methylation research that need to be closed before its final implementation in routine forensic casework.

  • 8.
    Kvastad, Linda
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Werne Solnestam, Beata
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Johansson, Erik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nygren, A. O.
    Laddach, N.
    Sahlén, Pelin
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bendigtsen, S. C.
    Aaserud, M.
    Floer, L.
    Borgen, E.
    Schwind, C.
    Himmelreich, R.
    Latta, D.
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Single cell analysis of cancer cells using an improved RT-MLPA method has potential for cancer diagnosis and monitoring2015In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, article id 16519Article in journal (Refereed)
    Abstract [en]

    Single cell analysis techniques have great potential in the cancer genomics feld. The detection and characterization of circulating tumour cells are important for identifying metastatic disease at an early stage and monitoring it. This protocol is based on transcript profiling using Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (RT-MLPA), which is a specific method for simultaneous detection of multiple mRNA transcripts. Because of the small amount of (circulating) tumour cells, a pre-amplification reaction is performed after reverse transcription to generate a sufficient number of target molecules for the MLPA reaction. We designed a highly sensitive method for detecting and quantifying a panel of seven genes whose expression patterns are associated with breast cancer, and optimized the method for single cell analysis. For detection we used a fluorescence-dependent semi-quantitative method involving hybridization of unique barcodes to an array. We evaluated the method using three human breast cancer cell lines and identified specific gene expression profiles for each line. Furthermore, we applied the method to single cells and confirmed the heterogeneity of a cell population. Successful gene detection from cancer cells in human blood from metastatic breast cancer patients supports the use of RT-MLPA as a diagnostic tool for cancer genomics.

  • 9.
    Maniatis, Silas
    et al.
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Aijo, Tarmo
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA..
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Braine, Catherine
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA.;Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Kang, Kristy
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagegaltier, Delphine
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA..
    Andrusivova, Zaneta
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Saarenpaa, Sami
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Saiz-Castro, Gonzalo
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Cuevas, Miguel
    Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Watters, Aaron
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Bonneau, Richard
    Flatiron Inst, Ctr Computat Biol, New York, NY 10010 USA.;NYU, Ctr Data Sci, New York, NY 10011 USA..
    Phatnani, Hemali
    New York Genome Ctr, Ctr Genom Neurodegenerat Dis, New York, NY 10013 USA.;Columbia Univ, Mortimer B Zuckerman Mind Brain Behav Inst, New York, NY 10032 USA..
    Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis2019In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 364, no 6435, p. 89-+Article in journal (Refereed)
    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.

  • 10.
    Salmén, Fredrik
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Ståhl, Patrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navarro Fernandez, José Carlos
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Frisen, Jonas
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections2018In: Nature Protocols, ISSN 1754-2189, E-ISSN 1750-2799, Vol. 13, no 11, p. 2501-2534Article in journal (Refereed)
    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.

  • 11.
    Salmén, Fredrik
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Stenbeck, Linnea
    KTH, School of Biotechnology (BIO), Gene Technology.
    Vallon-Christersson, Johan
    Lund.
    Ehinger, Anna
    Häkkinen, Jari
    Borg, Åke
    Frisén, Jonas
    Ståhl, Patrik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Three-dimensional spatial transcriptomics analysis for classification of breast cancerManuscript (preprint) (Other academic)
  • 12.
    Solnestam, Beata W.
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kvastad, Linda
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Johansson, Elin
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nygren, A. O.
    Laddach, N.
    Sahlén, Pellin
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lundberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Single cell analysis of cancer cells using an improved RT-MLPA method has potential for cancer diagnosis and monitoringManuscript (preprint) (Other academic)
  • 13.
    Stahl, Patrik L.
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Salmen, Fredrik
    KTH, School of Biotechnology (BIO), Gene Technology.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lundmark, Anna
    KTH, School of Biotechnology (BIO), Gene Technology.
    Navarro, Jose Fernandez
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Magnusson, Jens
    Giacomello, Stefania
    KTH, School of Biotechnology (BIO), Gene Technology.
    Asp, Michaela
    Westholm, Jakub O.
    Huss, Mikael
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Linnarsson, Sten
    Codeluppi, Simone
    Borg, Ake
    Ponten, Fredrik
    Costea, Paul Igor
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sahlen, Pelin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Mulder, Jan
    Bergmann, Olaf
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Frisen, Jonas
    Visualization and analysis of gene expression in tissue sections by spatial transcriptomics2016In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 353, no 6294, p. 78-82Article in journal (Refereed)
    Abstract [en]

    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.

  • 14.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Three-dimensional whole transcriptome analysis of tissue for classification of breast cancer2017Manuscript (preprint) (Other academic)
  • 15.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Three-dimensional whole transcriptome analysis of tissue for classification of breast cancer. Submitted manuscript.2017Manuscript (preprint) (Other academic)
  • 16.
    Vickovic, Sanja
    KTH, School of Biotechnology (BIO), Gene Technology.
    Transcriptome-wide analysis in cells and tissues2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    High-throughput sequencing has greatly influenced the amount of data produced and biological questions asked and answered. Sequencing approaches have also enabled rapid development of related technological fields such as single-cell and spatially resolved expression profiling. The introductory parts of this thesis give an overview of the basic molecular and technological apparatus needed to analyse the transcriptome in cells and tissues. This is succeeded by a summary of present investigations that report recent advancements in RNA profiling.

    RNA integrity needs to be preserved for accurate gene expression analysis. A method providing a low-cost alternative for RNA preservation was reported. Namely, a low concentration of buffered formaldehyde was used for fixation of human cell lines and peripheral blood cells (Paper I). The results from bulk RNA sequencing confirmed gene expression was not negatively impacted with the preservation procedure (r2>0.88) and that long-term storage of such samples was possible (r2=0.95). However, it is important to note that a small population of cells overexpressing a limited amount of genes can skew bulk gene expression analyses making them sufficient only in carefully designed studies. Therefore, gene expression should be investigated at the single cell resolution when possible. A method for high-throughput single cell expression profiling termed microarrayed single-cell sequencing was developed (Paper II). The method incorporated fluorescence-activated cell sorting, sample deposition and profiling of thousands of barcoded single cells in one reaction. After sample attachment to a barcoded array, a high-resolution image was taken which linked the position of each array barcode sequence to each individual deposited cell. The cDNA synthesis efficiency was estimated at 17.3% while detecting 27,427 transcripts per cell on average. Additionally, spatially resolved analysis is important in cell differentiation, organ development and pathological changes. Current methods are limited in terms of throughput, cost and time. For that reason, the spatial transcriptomics method was developed (Paper III). Here, the barcoded microarray was used to obtain spatially resolved expression profiles from tissue sections using the same imaging principle. The mouse olfactory bulb was profiled on a whole-transcriptome scale and the results showed that the expression correlated well (r2=0.94-0.97) as compared to bulk RNA sequencing. The method was 6.9% efficient, reported signal diffusion at ~2 μm and accurately deconvoluted layer-specific transcripts in an unbiased manner. Lastly, the spatial transcriptomics concept was applied to profile human breast tumours in three dimensions (Paper IV). Unbiased clustering revealed previously un-annotated regions and classified them as parts of the immune system, providing a detailed view into complex interactions and crosstalk in the whole tissue volume. Spatial tumour classification divulged that certain parts of the tumour clearly classified as other subtypes as compared to bulk analysis providing useful data for current practice diagnostics.

    The last part of the thesis discusses a look towards the future, how the presented methods could be used, improved upon or combined in translational research.

  • 17.
    Vickovic, Sanja
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ahmadian, Afshin
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lewensohn, Rolf
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Toward Rare Blood Cell Preservation for RNA Sequencing2015In: Journal of Molecular Diagnostics, ISSN 1525-1578, E-ISSN 1943-7811, Vol. 17, no 4, p. 352-359Article in journal (Refereed)
    Abstract [en]

    Cancer is driven by various events Leading to cell differentiation and disease progression. Molecular tools are powerful approaches for describing how and why these events occur. With the growing field of next-generation DNA sequencing, there is an increasing need for high-quality nucleic acids derived from human cells and tissues a prerequisite for successful cell profiting. Although advances in RNA preservation have been made, some of the largest biobanks still do not employ RNA blood preservation as standard because of Limitations in low blood-input volume and RNA stability over the whole gene body. Therefore, we have developed a robust protocol for blood preservation and tong-term storage while maintaining RNA integrity. Furthermore, we explored the possibility of using the protocol for preserving rare cell samples, such as circulating tumor cells. The results of our study confirmed that gene expression was not impacted by the preservation procedure (r(2) > 0.88) or by Long-term storage (r(2) = 0.95), with RNA integrity number values averaging over 8. Similarly, cell surface antigens were still available for antibody selection (r(2) = 0.95). Lastly, data mining for fusion events showed that it was possible to detect rare tumor cells among a background of other cells present in blood irrespective of fixation. Thus, the developed protocol would be suitable for rare blood cell preservation followed by RNA sequencing analysis.

  • 18.
    Vickovic, Sanja
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA..
    Eraslan, Gokcen
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA..
    Salmen, Fredrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Klughammer, Johanna
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA..
    Stenbeck, Linnea
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Schapiro, Denis
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA.;Harvard Med Sch, Lab Syst Pharmacol, Boston, MA 02115 USA..
    Aijo, Tarmo
    Flatiron Inst, Ctr Computat Biol, New York, NY USA..
    Bonneau, Richard
    NYU, Ctr Data Sci, New York, NY USA.;Brigham & Womens Hosp, Dept Pathol, 75 Francis St, Boston, MA 02115 USA..
    Bergenstrahle, Joseph
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fernandez Navarro, Jose
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gould, Joshua
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA..
    Griffin, Gabriel K.
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA.;Brigham & Womens Hosp, Dept Pathol, 75 Francis St, Boston, MA 02115 USA..
    Borg, Ake
    Lund Univ, Dept Clin Sci Lund, Div Oncol & Pathol, Lund, Sweden..
    Ronaghi, Mostafa
    Illumina Inc, San Diego, CA USA..
    Frisen, Jonas
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA..
    Regev, Aviv
    Broad Inst MIT & Harvard, Klarman Cell Observ, Cambridge, MA 02142 USA.;MIT, Howard Hughes Med Inst, Cambridge, MA USA.;MIT, Dept Biol, Koch Inst Integrat Canc Res, Cambridge, MA USA..
    Ståhl, Patrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    High-definition spatial transcriptomics for in situ tissue profiling2019In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 16, no 10, p. 987-+Article in journal (Refereed)
    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.

  • 19.
    Vickovic, Sanja
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Stahl, Patrik L.
    Salmen, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Giatrellis, Sarantis
    Westholm, Jakub Orzechowski
    Mollbrink, Annelie
    Navarro, Jose Fernandez
    Custodio, Joaquin
    Bienko, Magda
    Sutton, Lesley-Ann
    Rosenquist, Richard
    Frisen, Jonas
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Massive and parallel expression profiling using microarrayed single-cell sequencing2016In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 7, article id 13182Article in journal (Refereed)
    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.

1 - 19 of 19
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