{"doi":"10.1002/advs.202409338","title":"Microbiome Single Cell Atlases Generated with a Commercial Instrument","abstract":"Single-cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single-cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, EASi-seq (Easily Accessible Single microbe sequencing) is presented. By adapting the single-cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbial genomes. EASi-seq allows tens of thousands of microbes to be sequenced per run and, as it is shown, can generate detailed atlases of human and environmental microbiomes. The ability to capture large genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, a companion bioinformatic pipeline is developed that clusters genome by sequence similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, the integration of metagenomic contigs with the EASi-seq datasets is demonstrated to reduce capture bias and increase coverage. EASi-seq enables high-quality single-cell genomic sequencing for microbiome samples using a simple workflow run on a commercially available platform.","journal":"Advanced Science","year":2025,"id":550683,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9162,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":671946,"name":"Linfeng Xu","orcid":"0000-0002-6386-1815","position":1,"is_corresponding":false},{"id":267244,"name":"Benjamin Demaree","orcid":"0000-0003-2278-6633","position":2,"is_corresponding":false},{"id":578394,"name":"Cecilia Noecker","orcid":"0000-0003-1417-2383","position":3,"is_corresponding":false},{"id":301873,"name":"Jordan E. Bisanz","orcid":"0000-0002-8649-1706","position":4,"is_corresponding":false},{"id":700655,"name":"Daniel W. Weisgerber","orcid":"0000-0003-3187-634X","position":5,"is_corresponding":false},{"id":411850,"name":"Cyrus Modavi","orcid":"0000-0003-4586-012X","position":6,"is_corresponding":false},{"id":36356,"name":"Peter J. Turnbaugh","orcid":"0000-0002-0888-2875","position":7,"is_corresponding":false},{"id":3390,"name":"Adam R. Abate","orcid":"0000-0001-9614-4831","position":8,"is_corresponding":false},{"id":568291,"name":"Xiangpeng Li","orcid":"0000-0002-4230-5676","position":0,"is_corresponding":true}],"reference_count":124,"raw_metadata":null,"created_at":"2026-07-19T02:54:20.915388Z","pmid":"40462354","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":[]}