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Spatial Transcriptomics across kingdoms
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-4731-6857
2025 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Understanding how organisms develop and function requires decoding the complex interactions between cellular heterogeneity and gene expression. In multicellular organisms, specialized cell types differentiate from a single origin, responding to genetic regulatory programs and environmental cues to form tissues and organs. In contrast, unicellular organisms exhibit striking functional diversity at the single-cell level and can adapt to dynamic environments through regulated gene expression programs. Recent advances in spatially resolved transcriptomics, particularly in the Spatial Transcriptomics (ST) technology, have provided critical insights into these processes, characterizing gene expression patterns and regulatory networks in unicellular and multicellular systems.

This thesis leverages the ST technology to introduce methodological advancements for studying gene expression patterns across kingdoms, especially in plant development, microbial diversity, and host-microbe interactions.

In Article A, we presented an automated approach for ST library preparation, improving the efficiency and reproducibility of spatial gene expression profiling. It improved ST’s scalability and robustness for large-scale studies, facilitating the analysis of spatial organization in tissue sections.

For Article B, we generated a comprehensive spatiotemporal gene expression atlas for Picea abies shoot primordia, combining morphological and gene expression analysis. Through the atlas, we revealed gene expression patterns for previously unknown genes and provided initial annotations for several key developmental genes, while previously, annotations were based mainly on data from other species. Overall, this study advances our understanding of the molecular mechanisms that govern the reproductive development of conifers.

In Article C, we introduced a multimodal ST approach that simultaneously captures the host transcriptome and microbial abundance. Applying this method to Arabidopsis thaliana leaves, we identified distinct microbial hotspots and examined their spatial interactions with the host, providing insights into the complex dynamics of the host-microbiome relationships.

We applied the ST technology to various plankton species in Article D and generated parallel imaging and transcriptomic data. The findings offer new perspectives on these microorganisms’ cellular diversity and ecological roles and highlight the potential of array-based approaches in the study of microbial communities.

In conclusion, these studies advance the spatially resolved transcriptomics field and answer questions related to gene regulation in unicellular and multicellular organisms. As such, they expand our knowledge of orchestrated gene expression patterns that underlie life at diverse biological levels. They also provide a resource for applying sustainable development goals to improve crop resilience, forestry, and disease risk.

Abstract [sv]

Hur organismer utvecklas och fungerar beror på komplexa interaktioner mellan cellulär heterogenitet och genuttryck. Hos flercelliga organismer så differentieras specialiserade celltyper från en gemensam ursprungscell. Genom att svara på genetiska regleringsprogram och signaler från den omgivande miljön så bildar dessa celler vävnader och organ. Samtidigt uppvisar encelliga organismer en anmärkningsvärd funktionell mångfald, då enskilda celler kan anpassa sig till dynamiska miljöer genom reglerade genuttrycksprogram. Nya framsteg inom spatialt upplöst transkriptomik, i synnerhet Spatial Transcriptomics (ST)-teknologin, har lett till avgörande insikter i dessa processer genom att kartlägga genuttrycksmönster och regulatoriska nätverk i både encelliga och flercelliga system.

I denna avhandling används ST-teknologin för att introducera metodologiska framsteg för studier av genuttrycksmönster i olika biologiska riken, med särskilt fokus på utvecklingsbiologi hos växter, mikrobiell mångfald och värd-mikrobinteraktioner.

I Artikel A presenterar vi en automatiserad metod för beredning av ST-bibliotek, vilket förbättrar effektiviteten och reproducerbarheten i kartläggningen av spatialt genuttryck. Det ökar skalbarhet och robusthet för storskaliga studier med ST och underlättar analysen av vävnadsorganisation i snittprover.

För Artikel B skapade vi en omfattande spatiotemporal genuttrycksatlas för primordier av skott hos Picea abies där analys av morfologi och genuttryck kombinerats. Genom atlaskartläggningen avslöjade vi genuttrycksmönster för tidigare okända gener och tillhandahöll initiala annoteringar för flera viktiga utvecklingsgener, där tidigare annoteringar huvudsakligen baserades på data från andra arter. Sammanfattningsvis förbättrar denna studie vår förståelse av de molekylära mekanismer som styr barrträds reproduktiva utveckling. 

I Artikel C introducerade vi en multimodal ST-metod som fångar både värdorganismens transkriptom och den omgivande mikrobiella abundansen samtidigt. Genom att applicera denna metod på blad från Arabidopsis thaliana identifierade vi distinkta mikrobiella hotspots och undersökte deras rumsliga interaktioner med värden. Detta gav insikter i den komplexa dynamik som utgör värdmikrobiomrelationer. 

Vi tillämpade ST-teknologi på olika planktonarter i Artikel D, där vi parallelt producerade bild- och transkriptomikdata. Resultaten ger nya perspektiv på dessa mikroorganismers cellulära mångfald och ekologiska roller, och belyser potentialen hos array-baserade metoder för studier av mikrobiella samhällen. 

Sammanfattningsvis bidrar dessa studier till framsteg inom spatialt upplöst transkriptomik och besvarar frågor om genreglering i både encelliga och flercelliga organismer. De utökar därmed vår förståelse av de koordinerade genuttrycksmönster som ligger till grund för livet. Slutligen utgör de också en resurs för att tillämpa hållbarhetsmål för att förbättra jordbrukets resiliens, skogsbruk och sjukdomsrisker.

Abstract [fi]

Eliöiden kehittymisen ja toiminnan ymmärtäminen edellyttää solujen heterogeenisyyden ja geeniekspression välisen monimutkaisen vuorovaikutuksen tulkintaa. Monisoluisissa eliöissä erikoistuneet solutyypit erilaistuvat yhdestä solusta ja reagoivat geneettisiin säätelyverkostoihin ja ympäristöstä tuleviin signaaleihin muodostaen solukoita ja erilaisia rakenteita. Sen sijaan yksisoluiset eliöt ovat valtavan laaja ja monimuotoinen eliöryhmä, joka pystyy sopeutumaan muuttuviin ympäristöihin geneettisten säätelyverkostojen avulla. Viimeaikainen kehitys spatiaalisessa transkriptomiikassa (ST) on paljastanut tärkeää tietoa näistä prosesseista, tunnistaen geeniekspressiomalleja ja säätelyverkostoja yksisoluisista ja monisoluisista eliöistä. 

Tämä väitöskirja hyödyntää ST-teknologiaa ja esittelee uusia menetelmiä geeniekspression tutkimukseen eri eliökunnissa. Väitöskirja keskittyy erityisesti kasvien kehitysbiologiaan, mikrobien monimuotoisuuteen sekä isäntäeliön ja mikrobien välisiin vuorovaikutussuhteisiin.

Artikkelissa A esittelemme automatisoidun menetelmän sekvensointikirjastojen valmistamiseen ST-teknologialla. Menetelmä parantaa ST-teknologian tehokkuutta, toistettavuutta, skaalautuvuutta ja tarkkuutta erityisesti isoihin tutkimushankkeisiin, jotka ovat tärkeitä solukkorakenteiden geeniekspressiokuvioiden ja spatiaalisten säätelyverkkojen ymmärtämiseen. 

Artikkelissa B tuotimme laajan spatiotemporaalisen geeniekspressiokartaston kuusen (Picea abies) kasvusilmujen alkioille. Me yhdistimme morfologisen ja geeniekspressioanalyysin uusien kehitysbiologisesti merkittävien geenien ja niiden säätelyverkostojen tunnistamiseen. Kartaston avulla tunnistimme aiemmin tuntemattomia geenejä ja niiden geeniekspressiokuviot toimivat ensimmäisinä annotaatioina, kun aiemmin tällainen tieto on perustunut toisiin lajeihin. Tämä tutkimus edistää ymmärrystämme havupuiden lisääntymisbiologiasta ja sitä ohjaavista molekyylimenetelmistä.

Artikkelissa C esittelimme multimodaalisen lähestymistavan spatiaalisen geeniekspression tutkimukseen. Menetelmän avulla pystyimme samanaikaisesti tutkimaan isäntäeliön transkriptomia ja mikrobien määrää ja monimuotoisuutta solukkoleikkeissä. Sovelsimme menetelmää lituruohon (Arabidopsis thaliana) lehdistä tehtyihin ohuisiin leikkeisiin, ja havaitsimme mikrobipesäkkeitä ja tutkimme miten ne vaikuttavat isäntäkasvin paikalliseen geeniekspressioon. Tutkimus havainnollistaa isäntäkasvin ja mikrobiomin välisiä monimutkaisia vuorovaikutuksia.

Artikkelissa D sovelsimme ST-teknologiaa erilaisiin planktonlajeihin menetelmällä, joka mahdollisti näiden lajien samanaikaisen kuvaamisen ja transkriptomin tutkimisen. Tulokset perusteella saimme uutta tietoa näiden mikro-organismien monimuotoisuudesta ja ekologisista rooleista. Tulokset myös korostavat sirutekniikkaan perustuvien menetelmien mahdollisuuksia mikrobiyhteisöjen tutkimuksessa.

Tähän väitöskirjaan sisältyvät tutkimukset edistävät spatiaalisen transkriptomiikan alaa ja vastaavat yksi- ja monisoluisten eliöiden geenien säätelyyn liittyviin kysymyksiin. Nämä tutkimukset laajentavat tietämystä geeniekspression säätelymekanismeista, jotka ovat kaiken biologisen elämän taustalla. Ne toimivat myös resursseina muille tutkijoille, jotka voivat käyttää tuloksia kestävän kehityksen tavoitteiden saavuttamiseksi, kuten viljelykasvien sietokyvyn, metsätalouden tehokkuuden ja tautiriskin parantamiseksi.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2025. , p. 77
Series
TRITA-CBH-FOU ; 2025:5
Keywords [en]
Spatial Transcriptomics, spatially resolved transcriptomics, plant biology, non-model organisms, method development, microbiome
Keywords [fi]
Spatiaalinen transkriptomiikka, kasvibiologia, ei-malliorganismi, tuotekehitys, mikrobiomi
Keywords [sv]
Spatiella Transkriptomik, spatialt upplöst transkriptomik, växtbiologi, icke-modellorganismer, metodutveckling, mikrobiom
National Category
Genetics and Genomics Cell Biology Molecular Biology Microbiology Plant Biotechnology
Research subject
Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-360492ISBN: 978-91-8106-211-3 (print)OAI: oai:DiVA.org:kth-360492DiVA, id: diva2:1940491
Public defence
2025-03-27, Air&Fire, Tomtebodavägen 23B, via Zoom: https://kth-se.zoom.us/j/65605519312, Solna, 13:30 (English)
Opponent
Supervisors
Note

QC 20250227

Available from: 2025-02-27 Created: 2025-02-26 Last updated: 2025-12-17Bibliographically approved
List of papers
1. Automation of Spatial Transcriptomics library preparation to enable rapid and robust insights into spatial organization of tissues
Open this publication in new window or tab >>Automation of Spatial Transcriptomics library preparation to enable rapid and robust insights into spatial organization of tissues
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2020 (English)In: BMC Genomics, E-ISSN 1471-2164, Vol. 21, no 1Article in journal (Refereed) Published
Abstract [en]

Background: Interest in studying the spatial distribution of gene expression in tissues is rapidly increasing. Spatial Transcriptomics is a novel sequencing-based technology that generates high-throughput information on the distribution, heterogeneity and co-expression of cells in tissues. Unfortunately, manual preparation of high-quality sequencing libraries is time-consuming and subject to technical variability due to human error during manual pipetting, which results in sample swapping and the accidental introduction of batch effects. All these factors complicate the production and interpretation of biological datasets.

Results: We have integrated an Agilent Bravo Automated Liquid Handling Platform into the Spatial Transcriptomics workflow. Compared to the previously reported Magnatrix 8000+ automated protocol, this approach increases the number of samples processed per run, reduces sample preparation time by 35%, and minimizes batch effects between samples. The new approach is also shown to be highly accurate and almost completely free from technical variability between prepared samples.

Conclusions: The new automated Spatial Transcriptomics protocol using the Agilent Bravo Automated Liquid Handling Platform rapidly generates high-quality Spatial Transcriptomics libraries. Given the wide use of the Agilent Bravo Automated Liquid Handling Platform in research laboratories and facilities, this will allow many researchers to quickly create robust Spatial Transcriptomics libraries.

Place, publisher, year, edition, pages
Springer Nature, 2020
National Category
Cell and Molecular Biology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-273016 (URN)10.1186/s12864-020-6631-z (DOI)000529208400002 ()32293264 (PubMedID)2-s2.0-85083405329 (Scopus ID)
Note

QC 20200512

Available from: 2020-05-05 Created: 2020-05-05 Last updated: 2025-02-26Bibliographically approved
2. Spatiotemporal gene expression dynamics reveal the reproductive signaling regulators in Norway spruce
Open this publication in new window or tab >>Spatiotemporal gene expression dynamics reveal the reproductive signaling regulators in Norway spruce
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Conifers are essential components of forest ecosystems; however, their reproductive development remains largely understudied due to their genomes’ complexity. 

Here, we present a time-resolved spatial transcriptomics (ST) atlas of 88 tissue sections across three time points from developing reproductive and vegetative shoots in wild type Norway spruce (Picea abies) as well as transition shoots from the acrocona mutant. By comparing their different spatiotemporal gene expression dynamics, we identified the molecular processes responsible for the vegetative-to-reproductive shift, which occupy specific spatial domains in the shoots. We also discovered a new gene, DAL55, involved in the reproductive signaling cascade. Moreover, we shed light on the evolutionary relationships between gymnosperm and angiosperm YABBY genes, which are responsible for inner or outer cell layers in complex structures. 

Overall, our spatiotemporal atlas identifies genes, pathways and evolutionary relationships associated with plant reproductive organs; providing a valuable resource for studying conifer reproductive development. 

National Category
Natural Sciences Genetics and Genomics
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-360114 (URN)
Note

QC 20250218

Available from: 2025-02-18 Created: 2025-02-18 Last updated: 2025-02-26Bibliographically approved
3. Spatial metatranscriptomics resolves host–bacteria–fungi interactomes
Open this publication in new window or tab >>Spatial metatranscriptomics resolves host–bacteria–fungi interactomes
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2024 (English)In: Nature Biotechnology, ISSN 1087-0156, E-ISSN 1546-1696, Vol. 42, no 9, p. 1384-1393Article in journal (Refereed) Published
Abstract [en]

The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host–microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host–microbiome interplay.

Place, publisher, year, edition, pages
Springer Nature, 2024
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-350240 (URN)10.1038/s41587-023-01979-2 (DOI)001104879700001 ()37985875 (PubMedID)2-s2.0-85177077071 (Scopus ID)
Note

QC 20240711

Available from: 2024-07-11 Created: 2024-07-11 Last updated: 2025-02-26Bibliographically approved
4. Towards high-throughput parallel imaging and single-cell transcriptomics of microbial eukaryotic plankton
Open this publication in new window or tab >>Towards high-throughput parallel imaging and single-cell transcriptomics of microbial eukaryotic plankton
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2024 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 19, no 1 January, article id e0296672Article in journal (Refereed) Published
Abstract [en]

Single-cell transcriptomics has the potential to provide novel insights into poorly studied microbial eukaryotes. Although several such technologies are available and benchmarked on mammalian cells, few have been tested on protists. Here, we applied a microarray single-cell sequencing (MASC-seq) technology, that generates microscope images of cells in parallel with capturing their transcriptomes, on three species representing important plankton groups with different cell structures; the ciliate Tetrahymena thermophila, the diatom Phaeodactylum tricornutum, and the dinoflagellate Heterocapsa sp. Both the cell fixation and permeabilization steps were adjusted. For the ciliate and dinoflagellate, the number of transcripts of microarray spots with single cells were significantly higher than for background spots, and the overall expression patterns were correlated with that of bulk RNA, while for the much smaller diatom cells, it was not possible to separate single-cell transcripts from background. The MASC-seq method holds promise for investigating "microbial dark matter”, although further optimizations are necessary to increase the signal-to-noise ratio.

Place, publisher, year, edition, pages
Public Library of Science (PLoS), 2024
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-342835 (URN)10.1371/journal.pone.0296672 (DOI)001150526800053 ()38241213 (PubMedID)2-s2.0-85182856467 (Scopus ID)
Note

QC 20240201

Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2025-02-26Bibliographically approved

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Saarenpää, Sami

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