{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T11:05:01Z","timestamp":1788001501053,"version":"build-2784847793"},"reference-count":49,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T00:00:00Z","timestamp":1673222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000897","name":"Cystic Fibrosis Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000897","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Pulmonary exacerbations (PEx) in persons with cystic fibrosis (CF) are primarily related to acute or chronic inflammation associated with bacterial lung infections, which may be caused by several bacteria that activate similar bacterial genes and produce similar by-products. The goal of our study was to perform a stratified functional analysis of bacterial genes at three distinct time points in the treatment of a PEx in order to determine the role that specific airway microbiome community members may play within each clinical state (i.e., PEx, end of antibiotic treatment, and follow-up). Our secondary goal was to compare the change between clinical states with the metabolic activity of specific airway microbiome community members.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This was a prospective observational study of persons with CF treated with intravenous antibiotics for PEx between 2016 and 2020 at Children\u2019s National Hospital. Demographic and clinical information as well as respiratory samples were collected at hospital admission for PEx, end of antibiotic treatment, and follow-up. Metagenomic sequencing was performed; MetaPhlAn3 and HUMANn3 were used to assign sequences to bacterial species and bacterial metabolic genes, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Twenty-two persons with CF, with a mean age of 14.5 (range 7\u201323) years, experienced 45 PEx during the study period. Two-hundred twenty-one bacterial species were identified in the respiratory samples from the study cohort. Ten bacterial species had differential gene abundance across changes in the clinical state including <jats:italic>Staphylococcus aureus<\/jats:italic>, <jats:italic>Streptococcus salivarius<\/jats:italic>, and <jats:italic>Veillonella atypica<\/jats:italic> (all padj &amp;lt; 0.01 and log2FoldChange &amp;gt; |2|). These corresponded to a differential abundance of bacterial genes, with <jats:italic>S. aureus<\/jats:italic> accounting for 81% of the genes more abundant in PEx and <jats:italic>S. salivarius<\/jats:italic> accounting for 83% of the genes more abundant in follow-up, all compared to the end of treatment. Lastly, 8,653 metabolic pathways were identified across samples, with again <jats:italic>S. aureus<\/jats:italic> and <jats:italic>S. salivarius<\/jats:italic> contributing to the differential abundance of pathways (106 in PEx vs. 66 in follow-up, respectively). <jats:italic>V. atypica<\/jats:italic> was associated with a single metabolic pathway (UDP-<jats:italic>N<\/jats:italic>-acetyl-<jats:sc>D<\/jats:sc>-glucosamine biosynthesis) increased in follow-up compared to PEx.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Taken together, these data suggest that the metabolic potential of bacterial species can provide more insight into changes across clinical states than the relative abundance of the bacteria alone.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2022.1082125","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T09:22:37Z","timestamp":1673256157000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Using metabolic potential within the airway microbiome as predictors of clinical state in persons with cystic 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