Aditya Jeevannavar, Javier Florenza, Anna-Maria Divne, Manu Tamminen, Stefan Bertilsson
{"title":"Cellular heterogeneity in metabolism and associated microbiome of a non-model phytoflagellate","authors":"Aditya Jeevannavar, Javier Florenza, Anna-Maria Divne, Manu Tamminen, Stefan Bertilsson","doi":"10.1093/ismejo/wraf046","DOIUrl":null,"url":null,"abstract":"Single-cell transcriptomics is a key tool for unravelling metabolism and tissue diversity in model organisms. Its potential for elucidating the ecological roles of microeukaryotes, especially non-model ones, remains largely unexplored. This study employed the Smart-seq2 protocol on Ochromonas triangulata, a microeukaryote lacking a reference genome, showcasing how transcriptional states align with two distinct growth phases: a fast-growing phase and a slow-growing phase. Besides the two expected expression clusters, each corresponding to either growth phase, a third transcriptional state was identified across both growth phases. Metabolic mapping revealed a boost of photosynthetic activity in the fast growth over the slow growth stage, as well as down-regulation trend in pathways associated with ribosome functioning, CO2 fixation, and carbohydrate catabolism characteristic of the third transcriptional state. In addition, carry-over rRNA reads recapitulated the taxonomic identity of the target while revealing distinct bacterial communities, in co-culture with the eukaryote, each associated with distinct transcriptional states. This study underscores single-cell transcriptomics as a powerful tool for characterizing metabolic states in microeukaryotes without a reference genome, offering insights into unknown physiological states and individual-level interactions with different bacterial taxa. This approach holds broad applicability to describe the ecological roles of environmental microeukaryotes, culture-free and reference-free, surpassing alternative methods like metagenomics or metatranscriptomics.","PeriodicalId":516554,"journal":{"name":"The ISME Journal","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The ISME Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ismejo/wraf046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Single-cell transcriptomics is a key tool for unravelling metabolism and tissue diversity in model organisms. Its potential for elucidating the ecological roles of microeukaryotes, especially non-model ones, remains largely unexplored. This study employed the Smart-seq2 protocol on Ochromonas triangulata, a microeukaryote lacking a reference genome, showcasing how transcriptional states align with two distinct growth phases: a fast-growing phase and a slow-growing phase. Besides the two expected expression clusters, each corresponding to either growth phase, a third transcriptional state was identified across both growth phases. Metabolic mapping revealed a boost of photosynthetic activity in the fast growth over the slow growth stage, as well as down-regulation trend in pathways associated with ribosome functioning, CO2 fixation, and carbohydrate catabolism characteristic of the third transcriptional state. In addition, carry-over rRNA reads recapitulated the taxonomic identity of the target while revealing distinct bacterial communities, in co-culture with the eukaryote, each associated with distinct transcriptional states. This study underscores single-cell transcriptomics as a powerful tool for characterizing metabolic states in microeukaryotes without a reference genome, offering insights into unknown physiological states and individual-level interactions with different bacterial taxa. This approach holds broad applicability to describe the ecological roles of environmental microeukaryotes, culture-free and reference-free, surpassing alternative methods like metagenomics or metatranscriptomics.