Towards spatial host-microbiome profiling

Abstract: Sequencing technologies and applications have pushed the limits and enablednovel studies of biological mechanisms, evolutionary relationships and communicationnetworks between cells. The technical developments leading to single cell RNA-sequencinghave enabled detection of rare cell populations while spatial resolution added insights intolarger biological environments, like tissues and organs. Massively parallel sequencing haspaved the way for integrated high-throughput analyses including that of studying geneexpression, protein expression and mapping of microbial communities. This thesis startswith an introduction describing the technical and biological advancements made in recentyears with focus on spatially resolved approaches. Then, a summary of recentaccomplishments is presented, which enabled ongoing work in a novel field of spatial hostmicrobiomeprofiling. Lastly, the concluding remarks include both a future perspective anda short reflection on the current developments in the spatial multi-omics field.16S sequencing is often used for taxonomic classification of bacteria. In Paper I,this sequencing technique was used to study the aerodigestive microbiome in pediatric lungtransplant recipients. Many of these patients regretfully reject the organ after transplant,but the underlying cause is, in many cases, unknown. In this paper, multiple factorsinfluencing rejection were examined including that of the aerodigestive microbiome.Pediatric lung transplant recipients often suffer from gastrointestinal dysmotility and thefocus of this study was also to analyze changes in the microbiome in relation to irregulargastric muscle movements. The results showed that lung transplant recipients had, ingeneral, lower microbial diversity in the gastric fluid and throat and also that the microbialoverlap between lung and gastric sampling sites was significantly less in transplantrecipients compared to controls. In addition, gastrointestinal dysmotility was shown toinfluence the gastric microbiome in lung transplant recipients, but, given the small samplesize available in this study, the correlation to patient outcome could not be examined.Integrated analysis of the transcriptome and the antibody-based proteome in thesame tissue section was enabled using the method developed in Paper II. Spatial Multi-Omics (SM-Omics) uses a barcoded glass array to capture mRNA and antibody-basedexpression of selected proteins in the same section. The antibody-based profiling of thetissue section was enabled by either immunofluorescence or DNA-barcoded antibodies thatwere then decoded by sequencing. The protocol was scaled-up using an automated liquidhandlingsystem. Using this method, simultaneous profiling of the transcriptome andmultiplexed protein values was determined in both the mouse brain cortex and mousespleen. Results showed a high correlation in spatial pattern between gene expression andantibody measurements, independently of the antibody labelling technique. SM-Omicsgenerates a high-plex multi-omics characterization of the tissue in a high throughputmanner while exhibiting low technical variation.