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  • 1.
    Akhter, Shirin
    et al.
    Swedish Univ Agr Sci, Linnean Ctr Plant Biol, Uppsala Bioctr, Dept Plant Biol, Uppsala, Sweden..
    Kretzschmar, Warren W.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Sch Engn Sci Biotechnol Chem & Hlth, Dept Gene Technol, Sci Life Lab, Solna, Sweden..
    Nordal, Veronika
    Swedish Univ Agr Sci, Linnean Ctr Plant Biol, Uppsala Bioctr, Dept Plant Biol, Uppsala, Sweden..
    Delhomme, Nicolas
    Swedish Univ Agr Sci, Dept Forest Genet & Plant Physiol, Umea Plant Sci Ctr, Umea, Sweden..
    Street, Nathaniel R.
    Umea Sweden, Dept Plant Physiol, Umea Plant Sci Ctr, Umea, Sweden..
    Nilsson, Ove
    Swedish Univ Agr Sci, Dept Forest Genet & Plant Physiol, Umea Plant Sci Ctr, Umea, Sweden..
    Emanuelsson, Olof
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sundström, Jens F.
    Swedish Univ Agr Sci, Linnean Ctr Plant Biol, Uppsala Bioctr, Dept Plant Biol, Uppsala, Sweden..
    Integrative Analysis of Three RNA Sequencing Methods Identifies Mutually Exclusive Exons of MADS-Box Isoforms During Early Bud Development in Picea abies2018In: Frontiers in Plant Science, ISSN 1664-462X, E-ISSN 1664-462X, Vol. 9, article id 1625Article in journal (Refereed)
    Abstract [en]

    Recent efforts to sequence the genomes and transcriptomes of several gymnosperm species have revealed an increased complexity in certain gene families in gymnosperms as compared to angiosperms. One example of this is the gymnosperm sister Glade to angiosperm TM3-like MADS-box genes, which at least in the conifer lineage has expanded in number of genes. We have previously identified a member of this subclade, the conifer gene DEFICIENS AGAMOUS LIKE 19 (DAL19), as being specifically upregulated in cone-setting shoots. Here, we show through Sanger sequencing of mRNA-derived cDNA and mapping to assembled conifer genomic sequences that DAL19 produces six mature mRNA splice variants in Picea abies. These splice variants use alternate first and last exons, while their four central exons constitute a core region present in all six transcripts. Thus, they are likely to be transcript isoforms. Quantitative Real-Time PCR revealed that two mutually exclusive first DAL19 exons are differentially expressed across meristems that will form either male or female cones, or vegetative shoots. Furthermore, mRNA in situ hybridization revealed that two mutually exclusive last DAL19 exons were expressed in a cell-specific pattern within bud meristems. Based on these findings in DAL19, we developed a sensitive approach to transcript isoform assembly from short-read sequencing of mRNA. We applied this method to 42 putative MADS-box core regions in P abies, from which we assembled 1084 putative transcripts. We manually curated these transcripts to arrive at 933 assembled transcript isoforms of 38 putative MADS-box genes. 152 of these isoforms, which we assign to 28 putative MADS-box genes, were differentially expressed across eight female, male, and vegetative buds. We further provide evidence of the expression of 16 out of the 38 putative MADS-box genes by mapping PacBio Iso-Seq circular consensus reads derived from pooled sample sequencing to assembled transcripts. In summary, our analyses reveal the use of mutually exclusive exons of MADS-box gene isoforms during early bud development in P. abies, and we find that the large number of identified MADS-box transcripts in P. abies results not only from expansion of the gene family through gene duplication events but also from the generation of numerous splice variants.

  • 2.
    Alneberg, Johannes
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bioinformatic Methods in Metagenomics2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Microbial organisms are a vital part of our global ecosystem. Yet, our knowledge of them is still lacking. Direct sequencing of microbial communities, i.e. metagenomics, have enabled detailed studies of these microscopic organisms by inspection of their DNA sequences without the need to culture them. Furthermore, the development of modern high- throughput sequencing technologies have made this approach more powerful and cost-effective. Taken together, this has shifted the field of microbiology from previously being centered around microscopy and culturing studies, to largely consist of computational analyses of DNA sequences. One such computational analysis which is the main focus of this thesis, aims at reconstruction of the complete DNA sequence of an organism, i.e. its genome, directly from short metagenomic sequences.

    This thesis consists of an introduction to the subject followed by five papers. Paper I describes a large metagenomic data resource spanning the Baltic Sea microbial communities. This dataset is complemented with a web-interface allowing researchers to easily extract and visualize detailed information. Paper II introduces a bioinformatic method which is able to reconstruct genomes from metagenomic data. This method, which is termed CONCOCT, is applied on Baltic Sea metagenomics data in Paper III and Paper V. This enabled the reconstruction of a large number of genomes. Analysis of these genomes in Paper III led to the proposal of, and evidence for, a global brackish microbiome. Paper IV presents a comparison between genomes reconstructed from metagenomes with single-cell sequenced genomes. This further validated the technique presented in Paper II as it was found to produce larger and more complete genomes than single-cell sequencing.

  • 3.
    Alneberg, Johannes
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Bennke, Christin
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Beier, Sara
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Pinhassi, Jarone
    Centre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, Kalmar, Sweden.
    Jürgens, Klaus
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Ekman, Martin
    Department of Ecology, Environment and Plant Sciences, Stockholm University Science for Life Laboratory, Solna, Sweden.
    Ininbergs, Karolina
    Department of Ecology, Environment and Plant Sciences, Stockholm University Science for Life Laboratory, Solna, Sweden.
    Labrenz, Matthias
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Andersson, Anders F.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Recovering 2,032 Baltic Sea microbial genomes by optimized metagenomic binningManuscript (preprint) (Other academic)
    Abstract [en]

    Aquatic microorganism are key drivers of global biogeochemical cycles and form the basis of aquatic food webs. However, there is still much left to be learned about these organisms and their interaction within specific environments, such as the Baltic Sea. Crucial information for such an understanding can be found within the genome sequences of organisms within the microbial community.

    In this study, the previous set of Baltic Sea clusters, constructed by Hugert et al., is greatly expanded using a large set of metagenomic samples, spanning the environmental gradients of the Baltic Sea. In total, 124 samples were individually assembled and binned to obtain 2,032 Metagenome Assembled Genomes (MAGs), clustered into 353 prokaryotic and 14 eukaryotic species- level clusters. The prokaryotic genomes were widely distributed over the prokaryotic tree of life, representing 20 different phyla, while the eukaryotic genomes were mostly limited to the division of Chlorophyta. The large number of reconstructed genomes allowed us to identify key factors determining the quality of the genome reconstructions.

    The Baltic Sea is heavily influenced of human activities of which we might not see the full implications. The genomes reported within this study will greatly aid further studies in our strive for an understanding of the Baltic Sea microbial ecosystem.

  • 4.
    Alneberg, Johannes
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Karlsson, Christofer M. G.
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst, EEMiS, Kalmar, Sweden..
    Divne, Anna-Maria
    Uppsala Univ, Dept Cell & Mol Biol, SciLifeLab, Uppsala, Sweden..
    Bergin, Claudia
    Uppsala Univ, Dept Cell & Mol Biol, SciLifeLab, Uppsala, Sweden..
    Homa, Felix
    Uppsala Univ, Dept Cell & Mol Biol, SciLifeLab, Uppsala, Sweden..
    Lindh, Markus V.
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst, EEMiS, Kalmar, Sweden.;Lund Univ, Dept Biol, Lund, Sweden..
    Hugerth, Luisa
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ettema, Thijs J. G.
    Uppsala Univ, Dept Cell & Mol Biol, SciLifeLab, Uppsala, Sweden..
    Bertilsson, Stefan
    Uppsala Univ, Dept Ecol & Genet, Sci Life Lab, Limnol, Uppsala, Sweden..
    Andersson, Anders F.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Sch Engn Sci Chem Biotechnol & Hlth, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Pinhassi, Jarone
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst, EEMiS, Kalmar, Sweden..
    Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes2018In: Microbiome, ISSN 0026-2633, E-ISSN 2049-2618, Vol. 6, article id 173Article in journal (Refereed)
    Abstract [en]

    Background: Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms. Results: We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (average 99.51% sequence identity; range 98.77-99.84%) across overlapping regions (30-80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs. Conclusions: The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

  • 5.
    Alneberg, Johannes
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Karlsson, Christofer M.G.
    Centre for Ecology and Evolution in Microbial Model Systems, EEMiS, Linnaeus University, Barlastgatan 11, 391 82 Kalmar, Sweden.
    Divne, Anna-Maria
    Department of Cell and Molecular Biology, SciLifeLab, Uppsala University, Uppsala, Sweden .
    Bergin, Claudia
    Department of Cell and Molecular Biology, SciLifeLab, Uppsala University, Uppsala, Sweden .
    Homa, Felix
    Department of Cell and Molecular Biology, SciLifeLab, Uppsala University, Uppsala, Sweden .
    Lindh, Markus V.
    Centre for Ecology and Evolution in Microbial Model Systems, EEMiS, Linnaeus University, Barlastgatan 11, 391 82 Kalmar, Sweden.
    Hugerth, Luisa W.
    Karolinska Institutet, Science for Life Laboratory, Department of Molecular, Tumour and Cell Biology, Centre for Translational Microbiome Research, Solna, Sweden.
    Ettema, Thijs JG
    Department of Cell and Molecular Biology, SciLifeLab, Uppsala University, Uppsala, Sweden.
    Bertilsson, Stefan
    Department of Ecology and Genetics, Limnology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
    Andersson, Anders F.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Pinhassi, Jarone
    Centre for Ecology and Evolution in Microbial Model Systems, EEMiS, Linnaeus University, Barlastgatan 11, 391 82 Kalmar, Sweden.
    Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomesManuscript (preprint) (Other academic)
    Abstract [en]

    Background: Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms.

    Results: We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (>98.7% identity) across overlapping regions (30-80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs; the metagenome assembly was found to cause incompleteness to a higher degree than the binning procedure.

    Conclusions: The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

  • 6.
    Alneberg, Johannes
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sundh, John
    Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden.
    Bennke, Christin
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Beier, Sara
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Lundin, Daniel
    Centre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, Kalmar, Sweden.
    Hugerth, Luisa
    KTH Royal Institute of Technology, Science for Life Laboratory, School of Biotechnology, Stockholm, Sweden.
    Pinhassi, Jarone
    Centre for Ecology and Evolution in Microbial Model Systems, Linnaeus University, Kalmar, Sweden.
    Kisand, Veljo
    University of Tartu, Institute of Technology, Tartu, Estonia.
    Riemann, Lasse
    Section for Marine Biological Section, Department of Biology, University of Copenhagen, Helsingør, Denmark.
    Jürgens, Klaus
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Labrenz, Matthias
    Leibniz Institute for Baltic Sea Research, Warnemünde, Germany.
    Andersson, Anders F.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    BARM and BalticMicrobeDB, a reference metagenome and interface to meta-omic data for the Baltic SeaManuscript (preprint) (Other academic)
    Abstract [en]

    The Baltic Sea is one of the world’s largest brackish water bodies and is characterised by pronounced physicochemical gradients where microbes are the main biogeochemical catalysts. Meta-omic methods provide rich information on the composition of, and activities within microbial ecosystems, but are computationally heavy to perform. We here present the BAltic Sea Reference Metagenome (BARM), complete with annotated genes to facilitate further studies with much less computational effort. The assembly is constructed using 2.6 billion metagenomic reads from 81 water samples, spanning both spatial and temporal dimensions, and contains 6.8 million genes that have been annotated for function and taxonomy. The assembly is useful as a reference, facilitating taxonomic and functional annotation of additional samples by simply mapping their reads against the assembly. This capability is demonstrated by the successful mapping and annotation of 24 external samples. In addition, we present a public web interface, BalticMicrobeDB, for interactive exploratory analysis of the dataset.

  • 7.
    Alneberg, Johannes
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sundh, John
    Stockholm Univ, Sci Life Lab, Dept Biochem & Biophys, S-17165 Solna, Sweden..
    Bennke, Christin
    Leibniz Inst Balt Sea Res Warnemunde, D-18119 Rostock, Germany..
    Beier, Sara
    Leibniz Inst Balt Sea Res Warnemunde, D-18119 Rostock, Germany..
    Lundin, Daniel
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst, S-39182 Kalmar, Sweden..
    Hugerth, Luisa W.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Mol Tumor & Cell Biol, Ctr Translat Microbiome Res, Sci Life Lab, S-17165 Solna, Sweden..
    Pinhassi, Jarone
    Linnaeus Univ, Ctr Ecol & Evolut Microbial Model Syst, S-39182 Kalmar, Sweden..
    Kisand, Veljo
    Univ Tartu, Inst Technol, EE-50411 Tartu, Estonia..
    Riemann, Lasse
    Univ Copenhagen, Sect Marine Biol Sect, Dept Biol, DK-3000 Helsingor, Denmark..
    Juergens, Klaus
    Leibniz Inst Balt Sea Res Warnemunde, D-18119 Rostock, Germany..
    Labrenz, Matthias
    Leibniz Inst Balt Sea Res Warnemunde, D-18119 Rostock, Germany..
    Andersson, Anders F.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    BARM and BalticMicrobeDB, a reference metagenome and interface to meta-omic data for the Baltic Sea2018In: Scientific Data, E-ISSN 2052-4463, Vol. 5, article id 180146Article in journal (Refereed)
    Abstract [en]

    The Baltic Sea is one of the world's largest brackish water bodies and is characterised by pronounced physicochemical gradients where microbes are the main biogeochemical catalysts. Meta-omic methods provide rich information on the composition of, and activities within, microbial ecosystems, but are computationally heavy to perform. We here present the Baltic Sea Reference Metagenome (BARM), complete with annotated genes to facilitate further studies with much less computational effort. The assembly is constructed using 2.6 billion metagenomic reads from 81 water samples, spanning both spatial and temporal dimensions, and contains 6.8 million genes that have been annotated for function and taxonomy. The assembly is useful as a reference, facilitating taxonomic and functional annotation of additional samples by simply mapping their reads against the assembly. This capability is demonstrated by the successful mapping and annotation of 24 external samples. In addition, we present a public web interface, BalticMicrobeDB, for interactive exploratory analysis of the dataset.

  • 8.
    Asp, Michaela
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Spatially Resolved Gene Expression Analysis2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Spatially resolved transcriptomics has greatly expanded our knowledge of complex multicellular biological systems. To date, several technologies have been developed that combine gene expression data with information about its spatial tissue context. There is as yet no single spatial method superior to all others, and the existing methods have jointly contributed to progress in this field of technology. Some challenges presented by existing protocols include having a limited number of targets, being labor extensive, being tissue-type dependent and having low throughput or limited resolution. Within the scope of this thesis, many aspects of these challenges have been taken into consideration, resulting in a detailed evaluation of a recently developed spatial transcriptome-wide method. This method, termed Spatial Transcriptomics (ST), enables the spatial location of gene activity to be preserved and visually links it to its histological position and anatomical context. Paper I describes all the details of the experimental protocol, which starts when intact tissue sections are placed on barcoded microarrays and finishes with high throughput sequencing. Here, spatially resolved transcriptome-wide data are obtained from both mouse olfactory bulb and breast cancer samples, demonstrating the broad tissue applicability and robustness of the approach. In Paper II, the ST technology is applied to samples of human adult heart, a tissue type that contains large proportions of fibrous tissue and thus makes RNA extraction substantially more challenging. New protocol strategies are optimized in order to generate spatially resolved transcriptome data from heart failure patients. This demonstrates the advantage of using the technology for the identification of lowly expressed biomarkers that have previously been seen to correlate with disease progression in patients suffering heart failure. Paper III shows that, although the ST technology has limited resolution compared to other techniques, it can be combined with single-cell RNA-sequencing and hence allow the spatial positions of individual cells to be recovered. The combined approach is applied to developing human heart tissue and reveals cellular heterogeneity of distinct compartments within the complete organ. Since the ST technology is based on the sequencing of mRNA tags, Paper IV describes a new version of the method, in which spatially resolved analysis of full-length transcripts is being developed. Exploring the spatial distribution of full-length transcripts in tissues enables further insights into alternative splicing and fusion transcripts and possible discoveries of new genes.  

  • 9.
    Asp, Michaela
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Borgström, Erik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Stuckey, Alexander
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Gruselius, Joel
    Carlberg, Konstantin
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Andrusivova, Zaneta
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Salmén, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Käller, Max
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ståhl, Patrik
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatial Isoform Profiling within Individual Tissue SectionsManuscript (preprint) (Other academic)
    Abstract [en]

    Spatial Transcriptomics has been shown to be a persuasive RNA sequencing

    technology for analyzing cellular heterogeneity within tissue sections. The

    technology efficiently captures and barcodes 3’ tags of all polyadenylated

    transcripts from a tissue section, and thus provides a powerful platform when

    performing quantitative spatial gene expression studies. However, the current

    protocol does not recover the full-length information of transcripts, and

    consequently lack information regarding alternative splice variants. Here, we

    introduce a novel protocol for spatial isoform profiling, using Spatial

    Transcriptomics barcoded arrays.

  • 10.
    Asp, Michaela
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Giacomello, Stefania
    Fürth, Daniel
    Reimegård, Johan
    Wärdell, Eva
    Custodio, Joaquin
    Salmén, Fredrik
    Sundström, Erik
    Åkesson, Elisabet
    Bienko, Magda
    Månsson‐Broberg, Agneta
    Ståhl, Patrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Sylvén, Christer
    Lundeberg, Joakim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    An organ‐wide gene expression atlas of the developing human heartManuscript (preprint) (Other academic)
    Abstract [en]

    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. 

  • 11. Bell, E.
    et al.
    Lamminmäki, T.
    Alneberg, Johannes
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Andersson, Anders F.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Qian, C.
    Xiong, W.
    Hettich, R. L.
    Balmer, L.
    Frutschi, M.
    Sommer, G.
    Bernier-Latmani, R.
    Biogeochemical cycling by a low-diversity microbial community in deep groundwater2018In: Frontiers in Microbiology, ISSN 1664-302X, E-ISSN 1664-302X, Vol. 9, no SEP, article id 2129Article in journal (Refereed)
    Abstract [en]

    Olkiluoto, an island on the south-west coast of Finland, will host a deep geological repository for the storage of spent nuclear fuel. Microbially induced corrosion from the generation of sulphide is therefore a concern as it could potentially compromise the longevity of the copper waste canisters. Groundwater at Olkiluoto is geochemically stratified with depth and elevated concentrations of sulphide are observed when sulphate-rich and methane-rich groundwaters mix. Particularly high sulphide is observed in methane-rich groundwater from a fracture at 530.6 mbsl, where mixing with sulphate-rich groundwater occurred as the result of an open drill hole connecting two different fractures at different depths. To determine the electron donors fuelling sulphidogenesis, we combined geochemical, isotopic, metagenomic and metaproteomic analyses. This revealed a low diversity microbial community fuelled by hydrogen and organic carbon. Sulphur and carbon isotopes of sulphate and dissolved inorganic carbon, respectively, confirmed that sulphate reduction was ongoing and that CO2 came from the degradation of organic matter. The results demonstrate the impact of introducing sulphate to a methane-rich groundwater with limited electron acceptors and provide insight into extant metabolisms in the terrestrial subsurface. 

  • 12.
    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.

  • 13.
    Giacomello, Stefania
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Natl Bioinformat Infrastruct Sweden, Stockholm, Sweden..
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Preparation of plant tissue to enable Spatial Transcriptomics profiling using barcoded microarrays2018In: Nature Protocols, ISSN 1754-2189, E-ISSN 1750-2799, Vol. 13, no 11, p. 2425-2446Article in journal (Refereed)
    Abstract [en]

    Elucidation of the complex processes involved in plant growth requires analysis of the spatial gene expression patterns in all affected tissues. This protocol extension is an adaptation of a protocol that describes how to use barcoded oligo-dT microarrays to evaluate spatial global gene expression profiles in mammalian tissue to enable it to be applied to plant material. Here, we explain the required adjustments for preparing and treating plant tissue sections on the array surface, specifically in regard to how to permeabilize and remove the tissue. Once the tissue has been removed, the cDNA-mRNA hybrid that is left on the slide is processed in the same way as cDNA obtained during experiments on mammalian tissue; thus the later stages of the protocol are not included here, and readers should follow the accompanying protocol for those. We have previously used our protocol to generate high-quality sequencing libraries for Arabidopsis thaliana inflorescence, Populus tremula developing and dormant leaf buds, and Picea abies female cones. However, we anticipate that the protocol can be adapted to other tissue types and species. The entire protocol for preparing samples and processing libraries can be completed in 3-4 d.

  • 14.
    Jahn, Michael
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab. K.
    Vialas, Vital
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Karlsen, Jan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Maddalo, Gianluca
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edfors, Fredrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsström, Björn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Käll, Lukas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hudson, Elton P.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Growth of Cyanobacteria Is Constrained by the Abundance of Light and Carbon Assimilation Proteins2018In: Cell reports, ISSN 2211-1247, E-ISSN 2211-1247, Vol. 25, no 2, p. 478-+Article in journal (Refereed)
    Abstract [en]

    Cyanobacteria must balance separate demands for energy generation, carbon assimilation, and biomass synthesis. We used shotgun proteomics to investigate proteome allocation strategies in the model cyanobacterium Synechocystis sp. PCC 6803 as it adapted to light and inorganic carbon (C-i) limitation. When partitioning the proteome into seven functional sectors, we find that sector sizes change linearly with growth rate. The sector encompassing ribosomes is significantly smaller than in E. coli, which may explain the lower maximum growth rate in Synechocystis. Limitation of light dramatically affects multiple proteome sectors, whereas the effect of C-i limitation is weak. Carbon assimilation proteins respond more strongly to changes in light intensity than to C-i. A coarse-grained cell economy model generally explains proteome trends. However, deviations from model predictions suggest that the large proteome sectors for carbon and light assimilation are not optimally utilized under some growth conditions and may constrain the proteome space available to ribosomes.

  • 15.
    Johansson, Sebastian
    et al.
    Stockholms Universitet.
    Juhos, Szilveszter
    Stockholms Universitet.
    Redin, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Ahmadian, Afshin
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Käller, Max
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Comprehensive haplotyping of the HLA gene family using nanopore sequencingManuscript (preprint) (Other academic)
    Abstract [en]

    The HLA gene family is the most polymorphic loci in the human genome; it encodes for the major histocompatibility complexes (MHC) which mediates the immune response in terms of cellular interactions with antigens. Compatibility between HLA alleles is thus of great medical interest for recipients of allogeneic transplantations. Traditional serological techniques to evaluate compatibility are now being replaced by more accurate DNA sequencing-based methods. However, short read sequencing data typically result in collapsed sequences representing a mixture of variants from native haplotypes. In addition, most previous studies have been limited to a few highly polymorphic exons of various HLA genes. Here we present haplotype-resolved full-length sequencing of the six most clinically relevant MHC Class I and Class II genes, to characterize the haplotypes of eight reference individuals, using a single MinION flow cell. The results show that full-length sequencing of single molecules enables haplotypes to be resolved to the highest degree of accuracy (four-field resolution). In this study, a majority of the alleles were classified with four-field resolution and could be verified through previously published genotyping studies. These results support the notion that nanopore sequencing could be a viable solution for highly accurate clinical evaluation of histocompatibility.

  • 16. Kannan, P.
    et al.
    Kretzschmar, Warren W.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Winter, H.
    Warren, D.
    Bates, R.
    Allen, P. D.
    Syed, N.
    Irving, B.
    Papiez, B. W.
    Kaeppler, J.
    Markelc, B.
    Kinchesh, P.
    Gilchrist, S.
    Smart, S.
    Schnabel, J. A.
    Maughan, T.
    Harris, A. L.
    Muschel, R. J.
    Partridge, M.
    Sharma, R. A.
    Kersemans, V.
    Functional parameters derived from magnetic resonance imaging reflect vascular morphology in preclinical tumors and in human liver metastases2018In: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265, Vol. 24, no 19, p. 4694-4704Article in journal (Refereed)
    Abstract [en]

    Purpose: Tumor vessels influence the growth and response of tumors to therapy. Imaging vascular changes in vivo using dynamic contrast-enhanced MRI (DCE-MRI) has shown potential to guide clinical decision making for treatment. However, quantitative MR imaging biomarkers of vascular function have not been widely adopted, partly because their relationship to structural changes in vessels remains unclear. We aimed to elucidate the relationships between vessel function and morphology in vivo. Experimental Design: Untreated preclinical tumors with different levels of vascularization were imaged sequentially using DCE-MRI and CT. Relationships between functional parameters from MR (iAUC, Ktrans, and BATfrac) and structural parameters from CT (vessel volume, radius, and tortuosity) were assessed using linear models. Tumors treated with anti-VEGFR2 antibody were then imaged to determine whether antiangiogenic therapy altered these relationships. Finally, functional-structural relationships were measured in 10 patients with liver metastases from colorectal cancer. Results: Functional parameters iAUC and Ktrans primarily reflected vessel volume in untreated preclinical tumors. The relationships varied spatially and with tumor vascularity, and were altered by antiangiogenic treatment. In human liver metastases, all three structural parameters were linearly correlated with iAUC and Ktrans. For iAUC, structural parameters also modified each other's effect. Conclusions: Our findings suggest that MR imaging biomarkers of vascular function are linked to structural changes in tumor vessels and that antiangiogenic therapy can affect this link. Our work also demonstrates the feasibility of three-dimensional functional-structural validation of MR biomarkers in vivo to improve their biological interpretation and clinical utility. 

  • 17. Lundmark, A.
    et al.
    Gerasimcik, N.
    Båge, T.
    Jemt, A.
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. Science for Life Laboratory, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden.
    Salmén, F.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Centre Utrecht, Cancer Genomics Netherlands, Utrecht, The Netherlands.
    Lundeberg, Joakim
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Yucel-Lindberg, T.
    Gene expression profiling of periodontitis-affected gingival tissue by spatial transcriptomics2018In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, no 1, article id 9370Article in journal (Refereed)
    Abstract [en]

    Periodontitis is a highly prevalent chronic inflammatory disease of the periodontium, leading ultimately to tooth loss. In order to characterize the gene expression of periodontitis-affected gingival tissue, we have here simultaneously quantified and localized gene expression in periodontal tissue using spatial transcriptomics, combining RNA sequencing with histological analysis. Our analyses revealed distinct clusters of gene expression, which were identified to correspond to epithelium, inflamed areas of connective tissue, and non-inflamed areas of connective tissue. Moreover, 92 genes were identified as significantly up-regulated in inflamed areas of the gingival connective tissue compared to non-inflamed tissue. Among these, immunoglobulin lambda-like polypeptide 5 (IGLL5), signal sequence receptor subunit 4 (SSR4), marginal zone B and B1 cell specific protein (MZB1), and X-box binding protein 1 (XBP1) were the four most highly up-regulated genes. These genes were also verified as significantly higher expressed in gingival tissue of patients with periodontitis compared to healthy controls, using reverse transcription quantitative polymerase chain reaction. Moreover, the protein expressions of up-regulated genes were verified in gingival biopsies by immunohistochemistry. In summary, in this study, we report distinct gene expression signatures within periodontitis-affected gingival tissue, as well as specific genes that are up-regulated in inflamed areas compared to non-inflamed areas of gingival tissue. The results obtained from this study may add novel information on the genes and cell types contributing to pathogenesis of the chronic inflammatory disease periodontitis. 

  • 18.
    Redin, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Phasing single DNA molecules with barcode linked sequencing2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Elucidation of our genetic constituents has in the past decade predominately taken the form of short-read DNA sequencing. Revolutionary technology developments have enabled vast amounts of biological information to be obtained, but from a medical standpoint it has yet to live up to the promise of associating individual genotypes to phenotypic states of wide-spread clinical relevance. The mechanisms by which complex phenotypes arise have been difficult to ascertain and the value of short-read sequencing platforms have been limited in this regard. It has become evident that resolving the full spectrum of genetic heterogeneity requires accurate long range information of individual haplotypes to be distinguished. Long-range haplotyping information can be obtained experimentally by long-read sequencing platforms or through linkage of short sequencing reads by means of a common barcode. This thesis explores these solutions, primarily through the development of novel technologies to phase short sequences of single molecules using DNA barcoding. A new method for high-throughput phasing of single DNA molecules, achieved by the production and utilization of uniquely barcoded beads in emulsion droplets, is described in Paper I. The results confirm that complex libraries of beads featuring mutually exclusive barcodes can be generated through clonal PCR amplification, and that these beads can be used to phase variations of the 16s rRNA gene which reduces the ambiguity of classifying bacterial species for metagenomics. Paper II describes a second methodology (‘Droplet Barcode Sequencing’) which simplifies the concept of barcoding DNA fragments by omitting the need for beads and instead relying on clonal amplification of single barcoding oligonucleotides. This study also increases the amount of information that can be linked, which is showcased by phasing all exons of the HLA-A gene and successfully resolving all the alleles present in a sample pool of eight individuals. Paper III expands on this work and explores the use of a single molecule sequencing platform to provide full-length sequencing coverage of six genes of the HLA family. The results show that while genes shorter than 10 kb can be resolved with a high degree of accuracy, compensating for a relatively high error rate by means of increased coverage can be challenging for larger genomic loci. Finally, Paper IV introduces the use of barcode-linked reads on an unprecedented scale, with a new assay that enables low-cost haplotyping of whole genomes without the need for predetermined capture sequences. This technology is utilized to generate a haplotype-resolved human genome, call large-scale structural variants and perform reference-free assembly of bacterial and human genomes. At a cost of only $19 USD per sample, this technology makes the benefits of long-range haplotyping available to the vast majority of laboratories which currently rely solely on short-read sequencing platforms.

  • 19.
    Redin, David
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Frick, Tobias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Aghelpasand, Hooman
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Theland, Jennifer
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Käller, Max
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Borgström, Erik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Olsen, Remi-Andre
    Stockholms Universitet.
    Ahmadian, Afshin
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Efficient whole genome haplotyping and single molecule phasing with barcode-linked readsManuscript (preprint) (Other academic)
    Abstract [en]

    The future of human genomics is one that seeks to resolve the entirety of genetic variation through sequencing. The prospect of utilizing genomics for medical purposes require cost-efficient and accurate base calling, long-range haplotyping capability, and reliable calling of structural variants. Short-read sequencing has lead the development towards such a future but has struggled to meet the latter two of these needs. To address this limitation, we developed a technology that preserves the molecular origin of short sequencing reads, with an insignificant increase to sequencing costs. We demonstrate a library preparation method which enables whole genome haplotyping, long-range phasing of single DNA molecules, and de novo genome assembly through barcode-linked reads (BLR). Millions of random barcodes are used to reconstruct megabase-scale phase blocks and call structural variants. We also highlight the versatility of our technology by generating libraries from different organisms using picograms to nanograms of input material.

  • 20.
    Salmén, Fredrik
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden.;KNAW Royal Netherlands Acad Arts & Sci, Hubrecht Inst, Utrecht, Netherlands.;Univ Med Ctr Utrecht, Canc Genom Netherlands, Utrecht, Netherlands..
    Ståhl, Patrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Mollbrink, Annelie
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Navarro Fernandez, José Carlos
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Vickovic, Sanja
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden.;Broad Inst Harvard & Massachusetts Inst Technol, Cambridge, MA 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. KTH Royal Inst Technol, Dept Gene Technol, Sci Life Lab, Stockholm, Sweden..
    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.

  • 21.
    The, Matthew
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Statistical and machine learning methods to analyze large-scale mass spectrometry data2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Modern biology is faced with vast amounts of data that contain valuable information yet to be extracted. Proteomics, the study of proteins, has repositories with thousands of mass spectrometry experiments. These data gold mines could further our knowledge of proteins as the main actors in cell processes and signaling. Here, we explore methods to extract more information from this data using statistical and machine learning methods.

    First, we present advances for studies that aggregate hundreds of runs. We introduce MaRaCluster, which clusters mass spectra for large-scale datasets using statistical methods to assess similarity of spectra. It identified up to 40% more peptides than the state-of-the-art method, MS-Cluster. Further, we accommodated large-scale data analysis in Percolator, a popular post-processing tool for mass spectrometry data. This reduced the runtime for a draft human proteome study from a full day to 10 minutes.

    Second, we clarify and promote the contentious topic of protein false discovery rates (FDRs). Often, studies report lists of proteins but fail to report protein FDRs. We provide a framework to systematically discuss protein FDRs and take away hesitance. We also added protein FDRs to Percolator, opting for the best-peptide approach which proved superior in a benchmark of scalable protein inference methods.

    Third, we tackle the low sensitivity of protein quantification methods. Current methods lack proper control of error sources and propagation. To remedy this, we developed Triqler, which controls the protein quantification FDR through a Bayesian framework. We also introduce MaRaQuant, which proposes a quantification-first approach that applies clustering prior to identification. This reduced the number of spectra to be searched and allowed us to spot unidentified analytes of interest. Combining these tools outperformed the state-of-the-art method, MaxQuant/Perseus, and found enriched functional terms for datasets that had none before.

  • 22.
    The, Matthew
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Käll, Lukas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Distillation of label-free quantification data by clustering and Bayesian modelingManuscript (preprint) (Other academic)
    Abstract [en]

    In shotgun proteomics, the amount of information that can be extracted from label-free quantification experiments is typically limited by the identification rate as well as the noise level of the quantitative signals. This generally causes a low sensitivity in differential expression analysis on protein level. Here, we present a new method, MaRaQuant, in which we reverse the typical identification-first workflow into a quantification-first approach. Specifically, we apply unsupervised clustering on both MS1 and MS2 level to summarize all analytes of interest without assigning identities. This ensures that no valuable information is discarded due to analytes missing identification thresholds and allows us to spend more effort on the identification process due to the data reduction achieved by clustering. Furthermore, we propagate error probabilities from feature level all the way to protein level and input these to our probabilistic protein quantification method, Triqler. Applying this methodology to an engineered dataset, we managed to identify multiple analytes of interest that would have gone unnoticed in traditional pipelines, specifically, through the use of open modification and de novo searches. MaRaQuant/Triqler obtains significantly more identifications on all levels compared to MaxQuant/Perseus, including differentially expressed proteins. Notably, we managed to identify differentially expressed proteins in a clinical dataset where previously none were discovered. Furthermore, our differentially expressed proteins allowed us to attribute multiple functional annotation terms to both clinical datasets that we investigated.

  • 23.
    The, Matthew
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Käll, Lukas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Integrated identification and quantification error probabilities for shotgun proteomicsManuscript (preprint) (Other academic)
    Abstract [en]

    Protein quantification by label-free shotgun proteomics experiments is plagued by a multitude of error sources. Typical pipelines for identifying differentially expressed proteins use intermediate filters in an attempt to control the error rate. However, they often ignore certain error sources and, moreover, regard filtered lists as completely correct in subsequent steps. These two indiscretions can easily lead to a loss of control of the false discovery rate (FDR). We propose a probabilistic graphical model, Triqler, that propagates error information through all steps, employing distributions in favor of point estimates, most notably for missing value imputation. The model outputs posterior probabilities for fold changes between treatment groups, highlighting uncertainty rather than hiding it. We analyzed 3 engineered datasets and achieved FDR control and high sensitivity, even for truly absent proteins. In a bladder cancer clinical dataset we discovered 35 proteins at 5% FDR, with the original study discovering none at this threshold. Compellingly, these proteins showed enrichment for functional annotation terms. The model executes in minutes and is freely available at https://pypi.org/project/triqler/.

  • 24.
    Thrane, Kim
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Eriksson, Hanna
    Karolinska Inst, Dept Oncol Pathol, SE-17176 Stockholm, Sweden.;Karolinska Univ Hosp, Dept Oncol, SE-17176 Stockholm, Sweden..
    Maaskola, Jonas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hansson, Johan
    Karolinska Inst, Dept Oncol Pathol, SE-17176 Stockholm, Sweden.;Karolinska Univ Hosp, Dept Oncol, SE-17176 Stockholm, Sweden..
    Lundeberg, Joakim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatially Resolved Transcriptomics Enables Dissection of Genetic Heterogeneity in Stage III Cutaneous Malignant Melanoma2018In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 78, no 20, p. 5970-5979Article in journal (Refereed)
    Abstract [en]

    Cutaneous malignant melanoma (melanoma) is characterized by a high mutational load, extensive intertumoral and intratumoral genetic heterogeneity, and complex tumor microenvironment (TME) interactions. Further insights into the mechanisms underlying melanoma are crucial for understanding tumor progression and responses to treatment. Here we adapted the technology of spatial transcriptomics (ST) to melanoma lymph node biopsies and successfully sequenced the transcriptomes of over 2,200 tissue domains. Deconvolution combined with traditional approaches for dimensional reduction of transcriptome-wide data enabled us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Our unsupervised analysis revealed a complex spatial intratumoral composition of melanoma metastases that was not evident through morphologic annotation. Each biopsy showed distinct gene expression profiles and included examples of the coexistence of multiple melanoma signatures within a single tumor region as well as shared profiles for lymphoid tissue characterized according to their spatial location and gene expression profiles. The lymphoid area in close proximity to the tumor region displayed a specific expression pattern, which may reflect the TME, a key component to fully understanding tumor progression. In conclusion, using the ST technology to generate gene expression profiles reveals a detailed landscape of melanoma metastases. This should inspire researchers to integrate spatial information into analyses aiming to identify the factors underlying tumor progression and therapy outcome. Significance: Applying ST technology to gene expression profiling in melanoma lymph node metastases reveals a complex transcriptional landscape in a spatial context, which is essential for understanding the multiple components of tumor progression and therapy outcome. (C) 2018 AACR.

  • 25.
    Wong, Kim
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navarro, Jose Fernandez
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Bergenstrahle, Ludvig
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Royal Inst Technol KTH, Sch Biotechnol, Div Gene Technol, Sci Life Lab, SE-10691 Solna, Sweden..
    Stahl, Patrik L.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lundeberg, Joakim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets2018In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 34, no 11, p. 1966-1968Article in journal (Refereed)
    Abstract [en]

    Motiviation: Spatial Transcriptomics (ST) is a method which combines high resolution tissue imaging with high troughput transcriptome sequencing data. This data must be aligned with the images for correct visualization, a process that involves several manual steps. Results: Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface.

  • 26.
    Zhang, Miao
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Materials and Nanophysics. KTH.
    Ngampeerapong, Chonmanart
    Redin, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ahmadian, Afshin
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sychugov, Ilya
    KTH, School of Engineering Sciences (SCI), Applied Physics, Materials and Nanophysics.
    Linnros, Jan
    KTH, School of Engineering Sciences (SCI), Applied Physics, Materials and Nanophysics.
    Thermophoresis-Controlled Size-Dependent DNA Translocation through an Array of Nanopores2018In: ACS Nano, ISSN 1936-0851, E-ISSN 1936-086X, Vol. 12, no 5, p. 4574-4582Article in journal (Refereed)
    Abstract [en]

    Large arrays of nanopores can be used for high-throughput biomolecule translocation with applications toward size discrimination and sorting at the single-molecule level. In this paper, we propose to discriminate DNA length by the capture rate of the molecules to an array of relatively large nanopores (50–130 nm) by introducing a thermal gradient by laser illumination in front of the pores balancing the force from an external electric field. Nanopore arrays defined by photolithography were batch processed using standard silicon technology in combination with electrochemical etching. Parallel translocation of single, fluorophore-labeled dsDNA strands is recorded by imaging the array with a fast CMOS camera. The experimental data show that the capture rates of DNA molecules decrease with increasing DNA length due to the thermophoretic effect of the molecules. It is shown that the translocation can be completely turned off for the longer molecule using an appropriate bias, thus allowing a size discrimination of the DNA translocation through the nanopores. A derived analytical model correctly predicts the observed capture rate. Our results demonstrate that by combining a thermal and a potential gradient at the nanopores, such large nanopore arrays can potentially be used as a low-cost, high-throughput platform for molecule sensing and sorting.

1 - 26 of 26
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