{"doi":"10.1101/2022.07.18.500470","title":"Spatial host-microbiome sequencing","abstract":"<h4>ABSTRACT</h4> Mucosal and barrier tissues such as the gut, lung or skin, are composed of a complex network of cells and microbes forming a tight niche that prevents pathogen colonization and supports host-microbiome symbiosis. Characterizing these networks at high molecular and cellular resolution is crucial for our understanding of homeostasis and disease. Spatial transcriptomics has emerged as a key technology to positionally profile RNAs at high resolution in tissues. Here, we present spatial host-microbiome sequencing, an all-sequencing based approach that captures tissue histology, polyadenylated RNAs and bacterial 16S sequences directly from tissues on spatially barcoded glass surfaces. We apply our approach to the mouse gut as a model system, use a novel deep learning approach for data mapping and detect spatial niches impacted by microbial biogeography. Spatial host-microbiome sequencing should enhance study of native host-microbe interactions in health and disease.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":1631,"datarank":0.6144202337840485,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.21856163434175965,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.21856163434175965,"corpus_percentile":null,"corpus_rank":null,"citation_count":13,"citer_count":12,"citers_with_citation_signal":12,"citers_with_endowment":12,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.065,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-07-19","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":18736,"name":"Martin Stražar","orcid":"0000-0003-3064-1055","position":1,"is_corresponding":false},{"id":5342,"name":"Preben Bo Mortensen","orcid":"0000-0002-5230-9865","position":2,"is_corresponding":false},{"id":29633,"name":"Prisca Liberali","orcid":"0000-0003-0695-6081","position":3,"is_corresponding":false},{"id":483,"name":"Sanja Vicković","orcid":"0000-0003-0985-9885","position":4,"is_corresponding":false},{"id":18735,"name":"Britta Lötstedt","orcid":"0000-0003-3545-5489","position":0,"is_corresponding":true}],"reference_count":96,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}