{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T15:50:34Z","timestamp":1779897034272,"version":"3.53.1"},"reference-count":64,"publisher":"American Society for Microbiology","issue":"6","license":[{"start":{"date-parts":[[2023,12,21]],"date-time":"2023-12-21T00:00:00Z","timestamp":1703116800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,12,21]],"date-time":"2023-12-21T00:00:00Z","timestamp":1703116800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["mSystems"],"published-print":{"date-parts":[[2023,12,21]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n          <jats:p>\n            Current methods for the identification of specific microorganisms based on an\n            <jats:italic>in situ<\/jats:italic>\n            metabolism are often hampered by insufficient sensitivity and habitat complexity. Here, we present a novel approach for identifying and sequencing single microbial cells metabolizing a specific organic compound with high sensitivity and without prior knowledge of the microbial community. The workflow consists of labeling individual cells with a [\n            <jats:sup>14<\/jats:sup>\n            C] substrate based on their metabolic activity, followed by encapsulating cells in alginate with nuclear emulsion by using microfluidics. We here adapted the concept of microautoradiography to visually distinguish between encapsulated labeled and non-labeled cells, which are then sorted via flow cytometry for single cell genomics. As a proof-of-concept, we labeled, separated, lysed, and sequenced single cells of the benzene degrader\n            <jats:italic>Pseudomonas veronii<\/jats:italic>\n            from mock microbial communities. The cells of\n            <jats:italic>P. veronii<\/jats:italic>\n            were isolated with 100% specificity. Single-cell microautoradiography and genome sequencing is an innovative method for elucidating microbial identity, activity, and function in diverse habitats, contributing to elucidate novel taxa and genes with potential for biotechnological applications such as bioremediation.\n          <\/jats:p>\n          <jats:sec>\n            <jats:title>IMPORTANCE<\/jats:title>\n            <jats:p>\n              A central question in microbial ecology is which member of a community performs a particular metabolism. Several sophisticated isotope labeling techniques are available for analyzing the metabolic function of populations and individual cells in a community. However, these methods are generally either insufficiently sensitive or throughput-limited and thus have limited applicability for the study of complex environmental samples. Here, we present a novel approach that combines highly sensitive radioisotope tracking, microfluidics, high-throughput sorting, and single-cell genomics to simultaneously detect and identify individual microbial cells based solely on their\n              <jats:italic>in situ<\/jats:italic>\n              metabolic activity, without prior information on community structure.\n            <\/jats:p>\n          <\/jats:sec>","DOI":"10.1128\/msystems.00998-23","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T14:03:40Z","timestamp":1700489020000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":2,"title":["scMAR-Seq: a novel workflow for targeted single-cell genomics of microorganisms using radioactive labeling"],"prefix":"10.1128","volume":"8","author":[{"given":"Hao-Yu","family":"Lo","sequence":"first","affiliation":[{"name":"Institute for Biological Interfaces (IBG-5), Karlsruhe 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