journal article·2026-02Open access

Unveiling Global Diversity of Patescibacteriota and Functional Interactions with Host Microbes

Yanhan Ji, Xu Liu, Shuai Zhao, Sihan Zhou, Yufan Yang, Ping Zhang, Yu Shi, Wei Qin, Guibing Zhu, Yongguan Zhu, Yanzheng Gao, Jiandong Jiang, Baozhan Wang

Advanced Science· Volume 13· Issue 11

Abstract

Abstract Patescibacteriota, also known as Candidate Phyla Radiation (CPR), is a diverse clade of ultra‐small bacteria with an epibiotic lifestyle. Despite their ubiquity across diverse ecosystems and ecological importance in microbial networks, the global distribution of Patescibacteriota and functional interactions with their host organisms remain largely unknown. Here, by leveraging comprehensive Patescibacteriota genomic resources and global multi‐habitat metagenomic datasets, it is demonstrated that ribosomal protein S3 (rpS3) as a reliable phylogenetic marker, enabling accurate recovery of Patescibacteriota diversity from short‐read metagenomes. Using this framework, extensive taxonomic diversity and pronounced community heterogeneity are uncovered across eight ecosystems. Through network analysis and genome‐wide functional screening, habitat‐specific co‐occurrence patterns are also revealed between Patescibacteriota and host‐associated bacteria, especially potential functional synergies mediated by metabolic pathway cascades. Notably, Patescibacteriota‐encoded NirK may assist sulfate‐reducing bacteria in resisting nitrite stress, while NorB can mitigate nitric oxide toxicity for complete ammonia‐oxidizing bacteria. Taken together, this study highlights the underappreciated diversity of Patescibacteriota and elucidates its important role in supporting host metabolism through complementary biochemical functions, offering new insights into its ecological significance and evolutionary adaptations in the global ecosystem.
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Research context

OpenAlex topics: Microbial Community Ecology and Physiology · Genomics and Phylogenetic Studies · Gut microbiota and health

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Agricultural and Environmental Microbiology Ministry of Agriculture and Rural Affairs Department of Microbiology College of Life Sciences Nanjing Agricultural University Nanjing Jiangsu 210014 China

State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi 830011 China

State Key Laboratory of Crop Stress Adaptation and Improvement School of Life Sciences Henan University Kaifeng 475004 China

School of Biological Sciences and Institute for Environmental Genomics University of Oklahoma Norman OK 73072 USA

Research Center for Eco‐Environmental Sciences Chinese Academy of Sciences Beijing 100085 China

State Key Laboratory of Urban and Regional Ecology Research Centre for Eco‐Environmental Sciences Chinese Academy of Sciences Beijing 100085 China

State Key Laboratory of Herbage Improvement and Grassland Agro‐ecosystems Centre for Grassland Microbiome, College of Pastoral Agriculture Science and Technology Lanzhou University Lanzhou Gansu 730020 China

Funding

National Natural Science Foundation of China · National Key Research and Development Program of China · Natural Science Foundation of Jiangsu Province

References (75)

Show source-provided references
1. 10.1038/nature1448610.1038/nature14486 ↗
2. 10.1038/nbt.422910.1038/nbt.4229 ↗
3. 10.1038/nmicrobiol.2016.4810.1038/nmicrobiol.2016.48 ↗
4. 10.1038/s41579-018-0076-210.1038/s41579-018-0076-2 ↗
5. 10.1038/ncomms737210.1038/ncomms7372 ↗
6. 10.1073/pnas.141903811210.1073/pnas.1419038112 ↗
7. 10.1038/s41467-021-22762-410.1038/s41467-021-22762-4 ↗
8. 10.1128/mbio.01711-2210.1128/mbio.01711-22 ↗
9. 10.1073/pnas.221599011910.1073/pnas.2215990119 ↗
10. 10.1016/j.cell.2018.02.01610.1016/j.cell.2018.02.016 ↗
11. 10.1016/j.cub.2023.12.02410.1016/j.cub.2023.12.024 ↗
12. 10.1126/science.122404110.1126/science.1224041 ↗
13. 10.1038/nature1235210.1038/nature12352 ↗
14. 10.1038/sdata.2017.20310.1038/sdata.2017.203 ↗
15. 10.1186/s40168-022-01274-310.1186/s40168-022-01274-3 ↗
16. 10.1128/msystems.01205-2010.1128/msystems.01205-20 ↗
17. 10.1186/s40168-018-0499-z10.1186/s40168-018-0499-z ↗
18. 10.1016/j.cub.2017.10.04010.1016/j.cub.2017.10.040 ↗
19. 10.1128/cmr.00140-2110.1128/cmr.00140-21 ↗
20. 10.1073/pnas.130242611010.1073/pnas.1302426110 ↗
21. 10.1186/s40168-021-01202-x10.1186/s40168-021-01202-x ↗
22. 10.1038/nmicrobiol.2015.3210.1038/nmicrobiol.2015.32 ↗
23. 10.1101/gr.183012.11410.1101/gr.183012.114 ↗
24. 10.1186/s40168-023-01494-110.1186/s40168-023-01494-1 ↗
25. 10.1038/s41467-024-48498-510.1038/s41467-024-48498-5 ↗
26. 10.1038/s41564-020-00840-510.1038/s41564-020-00840-5 ↗
27. 10.1038/s41564-019-0449-y10.1038/s41564-019-0449-y ↗
28. 10.1016/j.cell.2023.08.01710.1016/j.cell.2023.08.017 ↗
29. 10.1073/pnas.211490911910.1073/pnas.2114909119 ↗
30. 10.1016/j.chom.2021.09.00910.1016/j.chom.2021.09.009 ↗
31. 10.1073/pnas.231979012110.1073/pnas.2319790121 ↗
32. 10.1038/s41587-023-01845-110.1038/s41587-023-01845-1 ↗
33. Gou X. · Soils · 2023 · 55 · 1044
34. 10.1038/nrmicro354910.1038/nrmicro3549 ↗
35. 10.1021/acs.est.1c0248310.1021/acs.est.1c02483 ↗
36. 10.1177/002203452090579210.1177/0022034520905792 ↗
37. 10.1073/pnas.230876912110.1073/pnas.2308769121 ↗
38. 10.1128/mBio.00521-2110.1128/mBio.00521-21 ↗
39. 10.1073/pnas.181062511510.1073/pnas.1810625115 ↗
40. 10.1038/s41396-020-00736-610.1038/s41396-020-00736-6 ↗
41. 10.1111/j.1462-2920.2006.01198.x10.1111/j.1462-2920.2006.01198.x ↗
42. Sears J. T. · MA. Reinsel · 1996
43. 10.1016/j.watres.2021.11735410.1016/j.watres.2021.117354 ↗
44. 10.1016/j.tim.2016.05.00410.1016/j.tim.2016.05.004 ↗
45. 10.1038/nature1645910.1038/nature16459 ↗
46. 10.1038/nature1646110.1038/nature16461 ↗
47. Pinto Ameet J. · mSphere · 2015 · 1
48. 10.1073/pnas.161105111310.1073/pnas.1611051113 ↗
49. 10.1038/ismej.2016.210.1038/ismej.2016.2 ↗
50. 10.3389/fmicb.2012.0027310.3389/fmicb.2012.00273 ↗
51. 10.1186/1471-2105-11-11910.1186/1471-2105-11-119 ↗
52. 10.1038/nmeth.317610.1038/nmeth.3176 ↗
53. 10.1093/nar/gkr98810.1093/nar/gkr988 ↗
54. 10.1371/journal.pone.016396210.1371/journal.pone.0163962 ↗
55. 10.1093/bioinformatics/btac67210.1093/bioinformatics/btac672 ↗
56. 10.1093/nar/gkf43610.1093/nar/gkf436 ↗
57. 10.1093/oxfordjournals.molbev.a02633410.1093/oxfordjournals.molbev.a026334 ↗
58. 10.1371/journal.pone.000949010.1371/journal.pone.0009490 ↗
59. 10.1093/nar/gkab30110.1093/nar/gkab301 ↗
60. Corrêa F. B. · Nucleic Acids Res. · 2020 · 48 · D626
61. 10.1093/bioinformatics/btu17010.1093/bioinformatics/btu170 ↗
62. 10.1038/nmeth.192310.1038/nmeth.1923 ↗
63. 10.1093/bioinformatics/btv03310.1093/bioinformatics/btv033 ↗
64. 10.7717/peerj.735910.7717/peerj.7359 ↗
65. 10.1101/gr.186072.11410.1101/gr.186072.114 ↗
66. 10.1093/bioinformatics/btq46110.1093/bioinformatics/btq461 ↗
67. 10.1038/ismej.2017.12610.1038/ismej.2017.126 ↗
68. 10.1038/s41587-019-0209-910.1038/s41587-019-0209-9 ↗
69. 10.1038/nmeth.419710.1038/nmeth.4197 ↗
70. 10.1002/imt2.9210.1002/imt2.92 ↗
71. 10.1093/nar/gkaa101810.1093/nar/gkaa1018 ↗
72. 10.1093/nar/gkaa91310.1093/nar/gkaa913 ↗
73. 10.1093/molbev/msaa01510.1093/molbev/msaa015 ↗
74. Hall T. · GERF Bull Biosci · 2011 · 2 · 60
75. 10.1038/s41596-022-00728-010.1038/s41596-022-00728-0 ↗