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.

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.

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.

Upon infecting its vertebrate host, the malaria parasite initially invades the liver where it undergoes massive replication, whilst remaining clinically silent. The coordination of host responses across the complex liver tissue during malaria infection remains unexplored. Here, we perform spatial transcriptomics in combination with single-nuclei RNA sequencing over multiple time points to delineate host-pathogen interactions across Plasmodium berghei-infected liver tissues. Our data reveals significant changes in spatial gene expression in the malaria-infected tissues. These include changes related to lipid metabolism in the proximity to sites of Plasmodium infection, distinct inflammation programs between lobular zones, and regions with enrichment of different inflammatory cells, which we term 'inflammatory hotspots'. We also observe significant upregulation of genes involved in inflammation in the control liver tissues of mice injected with mosquito salivary gland components. However, this response is considerably delayed compared to that observed in P. berghei-infected mice. Our study establishes a benchmark for investigating transcriptome changes during host-parasite interactions in tissues, it provides informative insights regarding in vivo study design linked to infection and offers a useful tool for the discovery and validation of de novo intervention strategies aimed at malaria liver stage infection.

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.

While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy.

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.

Several important human infectious diseases are caused by microscale-sized parasitic nematodes like filarial worms. Filarial worms have their own spatial tissue organization; to uncover this tissue structure, we need methods that can spatially resolve these miniature specimens. Most filarial worms evolved a mutualistic association with endosymbiotic bacteria Wolbachia. However, the mechanisms underlying the dependency of filarial worms on the fitness of these bacteria remain unknown. As Wolbachia is essential for the development, reproduction, and survival of filarial worms, we spatially explored how Wolbachia interacts with the worm’s reproductive system by performing a spatial characterization using Spatial Transcriptomics (ST) across a posterior region containing reproductive tissue and developing embryos of adult female Brugia malayi worms. We provide a proof-of-concept for miniature-ST to explore spatial gene expression patterns in small sample types, demonstrating the method’s ability to uncover nuanced tissue region expression patterns, observe the spatial localization of key B. malayi - Wolbachia pathway genes, and co-localize the B. malayi spatial transcriptome in Wolbachia tissue regions, also under antibiotic treatment. We envision our approach will open up new avenues for the study of infectious diseases caused by micro-scale parasitic worms.

The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.

Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology. Global transcriptional differences across lobular units in the liver remain unknown. Here the authors perform spatial transcriptomics of liver tissue to delineate transcriptional differences in physical space, confirm lobular zonation along transcriptional gradients and suggest the presence of previously uncharacterized structures within liver tissue.

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.

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