{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T18:50:40Z","timestamp":1773687040128,"version":"3.50.1"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"vor","delay-in-days":15,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82341109"],"award-info":[{"award-number":["82341109"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82173645"],"award-info":[{"award-number":["82173645"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Comprehensive pan-domain metagenomic classification is increasingly constrained by the memory and runtime costs of building and querying the rapidly expanding reference genome space. We introduce Kun-peng, a taxonomic classifier powered by an intelligent block-partitioned database structure and optimized search strategies, enabling ultra-scalable, memory-efficient pan-domain profiling. Using the Critical Assessment of Metagenome Interpretation II benchmark, Kun-peng substantially reduces the memory usage of database-building and querying by up to 24-fold, and accelerates sample classification by up to 4.73-fold compared with Kraken2. Kun-peng achieves competitive accuracy with fewer false positives than Kraken2, Centrifuger, and even KrakenUniq, while maintaining consistently high sensitivity across diverse datasets. In a real-world evaluation of 586 metagenomic samples spanning air, water, soil, and human-associated environments, we performed classification using a 4.3\u00a0TB pan-domain database comprising 204,477 genomes, which was built by Kun-peng with only 4.1\u00a0GB peak memory. Kun-peng processed each sample in 0.2\u201311.2\u00a0min with 4.0\u201335.4\u00a0GB peak memory, corresponding to a 54\u2013473-fold reduction in memory usage relative to Kraken2. Compared with Sylph, Kun-peng achieved up to a 46-fold speedup while requiring 21-fold less memory. Kun-peng classified 69.8%\u201394.3% of reads, improving coverage by 20%\u201360% over the standard Kraken2 database with 62,026 genomes. This improvement reflects expanded reference coverage, although a small fraction of false positives is inherent to k-mer-based methods. Overall, Kun-peng effectively eliminates the long-standing memory bottleneck in pan-domain database building and classification, enabling rapid and scalable pan-domain taxonomic analysis of complex environmental, ecological, and exposomic sequencing datasets.<\/jats:p>","DOI":"10.1093\/bib\/bbag119","type":"journal-article","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T12:45:12Z","timestamp":1772023512000},"source":"Crossref","is-referenced-by-count":0,"title":["Kun-peng enables scalable and accurate pan-domain metagenomic classification"],"prefix":"10.1093","volume":"27","author":[{"given":"Qiong","family":"Chen","sequence":"first","affiliation":[{"name":"MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University , No. 866 Yuhangtang Road, Xihu District, Hangzhou, Zhejiang 310058 ,","place":["China"]},{"name":"State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine , No. 79 Qingchun Road, Shangcheng District, Hangzhou, Zhejiang 310003 ,","place":["China"]}]},{"given":"Boliang","family":"Zhang","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University , No. 866 Yuhangtang Road, Xihu District, Hangzhou, Zhejiang 310058 ,","place":["China"]}]},{"given":"Chen","family":"Peng","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University , No. 866 Yuhangtang Road, Xihu District, Hangzhou, Zhejiang 310058 ,","place":["China"]}]},{"given":"Jiajun","family":"Huang","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University , No. 866 Yuhangtang Road, Xihu District, Hangzhou, Zhejiang 310058 ,","place":["China"]}]},{"given":"Zhen","family":"Liu","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University , No. 866 Yuhangtang Road, Xihu District, Hangzhou, Zhejiang 310058 ,","place":["China"]}]},{"given":"Xiaotao","family":"Shen","sequence":"additional","affiliation":[{"name":"Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore; School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University , 62 Nanyang Drive, Singapore 637459 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