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Towards comprehensive cellular atlases: High-throughput cell mapping by in situ sequencing
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.ORCID iD: 0000-0001-7509-8071
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

With recent technological advancements in single-cell biology, many aspects of individual cells are characterized with unprecedented resolution and details. Cell types in human and model organisms are redefined, and multiple organ-wide atlases are proposed to integrate different types of data to provide a comprehensive view of biological systems at cellular resolution. Incorporating location information of cells in such atlases is crucial to understanding the structure and functions. Several spatially resolved transcriptomics technologies may serve this purpose, and in situ sequencing (ISS) is among the most powerful ones.

ISS detects the expression of tens to hundreds of genes in situ, i.e. inside preserved cells and tissues. ISS is a targeted approach, using probes designed to identify specific transcripts. Its key advantages, as compared to other spatially resolved gene expression analysis methods, are high throughput, cellular resolution and tissue compatibility, making it a tool ideally suited for spatial cell mapping. The work included in this thesis aims to develop tools and methods for this application.

In paper I, a network analysis tool was developed to analyze ISS and other spatially resolved data. The tool enables smooth visualization of large datasets and generates networks based on colocalization. It also includes functions to test statistical significance and resolve tissue heterogeneity.

In paper II, we studied spatio-temporal patterns of immune response in tuberculosis granuloma by targeting immune markers with ISS. Using the tool developed in paper I together with other methods, we established an immune response time course at the granuloma sites and found histologically different granulomas based on transcriptional information. The paper demonstrated that ISS can robustly detect transcripts in formalin-fixed paraffin-embedded tissues across biological samples and reveal biologically relevant structures.

In paper III, we developed probabilistic cell typing by in situ sequencing (pciSeq), a method to spatially map cell types defined by single-cell RNA-sequencing. pciSeq is an integrated pipeline that includes gene selection, image analysis, barcode calling and cell type calling. We mapped closely related interneuron cell types of the mouse hippocampal CA1 region in 14 coronal sections and validated the results against ground truth.

In paper IV, we investigated the quantification bias of ISS resulting from the probe target selection. We developed a method to sequence in situ synthesized cDNA and found that the read coverage of in situ cDNA library reflected ISS counts more closely than conventional RNA sequencing, making it possible, to some extent, to predict a probe’s performance and guide the probe design.

Taken together, the developments described in this thesis comprise several tools that make ISS suitable for building cellular atlases via large-scale spatial mapping.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University , 2019. , p. 60
Keywords [en]
Spatially resolved transcriptomics, in situ sequencing, cell type, spatial analysis
National Category
Biochemistry and Molecular Biology
Research subject
Biochemistry
Identifiers
URN: urn:nbn:se:su:diva-174755ISBN: 978-91-7797-883-1 (print)ISBN: 978-91-7797-884-8 (electronic)OAI: oai:DiVA.org:su-174755DiVA, id: diva2:1359663
Public defence
2019-11-25, Air & Fire, SciLifeLab, Tomtebodavägen 23 A, Solna, 09:30 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Accepted. Paper 4: Manuscript.

Available from: 2019-10-30 Created: 2019-10-10 Last updated: 2019-10-22Bibliographically approved
List of papers
1. Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet
Open this publication in new window or tab >>Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet
2018 (English)In: Cell Systems, ISSN 2405-4712, Vol. 6, no 5, p. 626-630Article in journal (Refereed) Published
Abstract [en]

In situ sequencing methods generate spatially resolved RNA localization and expression data at an almost single-cell resolution. Few methods, however, currently exist to analyze and visualize the complex data that is produced, which can encode the localization and expression of a million or more individual transcripts in a tissue section. Here, we present InsituNet, an application that converts in situ sequencing data into interactive network-based visualizations, where each unique transcript is a node in the network and edges represent the spatial co-expression relationships between transcripts. InsituNet is available as an app for the Cytoscape platform at http://apps.cytoscape.org/apps/insitunet. InsituNet enables the analysis of the relationships that exist between these transcripts and can uncover how spatial co-expression profiles change in different regions of the tissue or across different tissue sections.

Keywords
network biology, data visualization, in situ sequencing, gene expression, Cytoscape, spatial transcriptomics, spatial co-expression
National Category
Biological Sciences
Research subject
Biochemistry
Identifiers
urn:nbn:se:su:diva-157730 (URN)10.1016/j.cels.2018.03.010 (DOI)000433906700011 ()29753646 (PubMedID)
Available from: 2018-08-02 Created: 2018-08-02 Last updated: 2019-10-11Bibliographically approved
2. Spatial and temporal localization of immune transcripts defines hallmarks and diversity in the tuberculosis granuloma
Open this publication in new window or tab >>Spatial and temporal localization of immune transcripts defines hallmarks and diversity in the tuberculosis granuloma
Show others...
2019 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 1823Article in journal (Refereed) Published
Abstract [en]

Granulomas are the pathological hallmark of tuberculosis (TB) and the niche where bacilli can grow and disseminate or the immunological microenvironment in which host cells interact to prevent bacterial dissemination. Here we show 34 immune transcripts align to the morphology of lung sections from Mycobacterium tuberculosis-infected mice at cellular resolution. Colocalizing transcript networks at <10 mu m in C57BL/6 mouse granulomas increase complexity with time after infection. B-cell clusters develop late after infection. Transcripts from activated macrophages are enriched at subcellular distances from M. tuberculosis. Encapsulated C3HeB/FeJ granulomas show necrotic centers with transcripts associated with immunosuppression (Foxp3, Il10), whereas those in the granuloma rims associate with activated T cells and macrophages. We see highly diverse networks with common interactors in similar lesions. Different immune landscapes of M. tuberculosis granulomas depending on the time after infection, the histopathological features of the lesion, and the proximity to bacteria are here defined.

National Category
Biological Sciences
Identifiers
urn:nbn:se:su:diva-169112 (URN)10.1038/s41467-019-09816-4 (DOI)000465200000004 ()31015452 (PubMedID)
Available from: 2019-06-07 Created: 2019-06-07 Last updated: 2019-10-10Bibliographically approved
3. Probabilistic cell typing enables fine mapping of closely related cell types in situ
Open this publication in new window or tab >>Probabilistic cell typing enables fine mapping of closely related cell types in situ
Show others...
2019 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105Article in journal (Refereed) Epub ahead of print
Abstract [en]

Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related neuronal types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages prior scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method by mapping the inhibitory neurons of mouse hippocampal area CA1, for which ground truth is available from extensive prior work identifying their laminar organization. Our method identified these neuronal classes in a spatial arrangement matching ground truth, and further identified multiple classes of isocortical pyramidal cell in a pattern matching their known organization. This method will allow identifying the spatial organization of closely related cell types across the brain and other tissues.

Keywords
cell type, spatial transcriptome, hippocampus
National Category
Biochemistry and Molecular Biology
Research subject
Biochemistry
Identifiers
urn:nbn:se:su:diva-174727 (URN)10.1038/s41592-019-0631-4 (DOI)
Funder
Swedish Research Council, 2016-03645
Available from: 2019-10-09 Created: 2019-10-09 Last updated: 2019-12-07
4. Target sequence design of padlock probes based on experimentally determined in situ synthesized cDNA fragments
Open this publication in new window or tab >>Target sequence design of padlock probes based on experimentally determined in situ synthesized cDNA fragments
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Padlock probes are widely used to target a short fragment of DNA. For example, in in situ sequencing (ISS), an image-based technology for highly multiplexed spatial gene expression analysis, cDNA target detection is mediated by padlock probes. Transcript counts from ISS generally has good correlation with next-generation sequencing read counts, but bias between different genes are also observed. Therefore, we developed a new method to isolate and sequence in situ synthesized cDNA and sought to use the read coverage information from it to guide padlock probe design. The results show limited correlation between cDNA library sequencing and ISS counts, but it can still help the probe design process by eliminating target sequences that are very unlikely to be detected. In addition, the method provides a way to systematically characterize in situ reverse transcription.

Keywords
probe design, in situ sequencing
National Category
Biochemistry and Molecular Biology
Research subject
Biochemistry
Identifiers
urn:nbn:se:su:diva-174737 (URN)
Available from: 2019-10-09 Created: 2019-10-09 Last updated: 2019-10-10Bibliographically approved

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