journal article·2026-05Open access

Alternating High‐Fat and Polysaccharide Diets Modulates Gut Phage‐Bacterial Interplay

Fengxiang Zhao, Ruiqi Zhang, Rujun Wei, Huimin Fan, Yongfei Hu, Wenyu Shi, Jinfeng Wang

Advanced Science· Volume 13· Issue 29

Abstract

ABSTRACT Phages dominate the human gut virome and are known for their ability to prey on bacteria and shape microbiota. However, their response to diet has only been elucidated using small‐scale studies. By integrating a massive meta‐analysis of 6932 diet‐associated metagenomes with a time‐resolved mouse model of a high‐fat diet and polysaccharide intake, the impact of diet on the gut virome and phage–bacterial interactions was systematically characterized. Diet types, particularly high‐fat and polysaccharide‐rich diets, exert the strongest shaping force on the gut virome, enhancing the crosstalk between phages and bacteria. High‐fat diets promote changes in phage abundance across a broad taxonomic range, from 34.21% to 50.00%, drive phages of diet‐associated bacteria toward a lytic lifestyle, and remarkably enrich auxiliary metabolic genes related to amino acid metabolism. Conversely, fucoidan reversed HFD‐induced dysbiosis and enhanced phage‐mediated horizontal gene transfer by 8.5‐fold relative to the baseline. crAssphages and Parabacteroides phages may be important contributors, broadly supporting horizontal gene transfer and auxiliary metabolism or strengthening phage–host interactions in polysaccharide interventions, including fucoidan supplementation. These findings provide a comprehensive landscape of diet‐driven cross‐kingdom interactions and phage‐mediated gene exchange in the gut, offering new insights into potential strategies for precise nutritional interventions targeting the intestinal microbiota.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Bacteriophages and microbial interactions · Gut microbiota and health · Fecal contamination and water quality

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

Affiliations

College of Food Science & Nutritional Engineering China Agricultural University Beijing China

State Key Laboratory of Animal Nutrition and Feeding College of Animal Science and Technology China Agricultural University Beijing China

College of Biological Sciences China Agricultural University Beijing China

Key Laboratory of Fruit and Vegetable Processing of Ministry of Agriculture and Rural Affairs & Beijing Key Laboratory for Food Non‐Thermal Processing China Agricultural University Beijing China

Funding

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

References (100+)

Show source-provided references
1. 10.1093/ije/dyr20710.1093/ije/dyr207 ↗
2. 10.1038/s41522‐021‐00245‐010.1038/s41522‐021‐00245‐0 ↗
3. 10.1016/j.celrep.2018.05.01810.1016/j.celrep.2018.05.018 ↗
4. 10.3945/jn.112.16632210.3945/jn.112.166322 ↗
5. 10.1016/j.cell.2011.09.02510.1016/j.cell.2011.09.025 ↗
6. 10.1136/gut.2007.13466810.1136/gut.2007.134668 ↗
7. 10.1002/hep.3145910.1002/hep.31459 ↗
8. 10.1016/j.chom.2020.01.00410.1016/j.chom.2020.01.004 ↗
9. 10.1053/j.gastro.2021.06.05610.1053/j.gastro.2021.06.056 ↗
10. 10.1080/19490976.2021.188771910.1080/19490976.2021.1887719 ↗
11. 10.1002/advs.20230581810.1002/advs.202305818 ↗
12. 10.4049/jimmunol.080022410.4049/jimmunol.0800224 ↗
13. 10.1126/science.aat969110.1126/science.aat9691 ↗
14. 10.1038/s41579‐021‐00536‐510.1038/s41579‐021‐00536‐5 ↗
15. 10.1093/gastro/goac01210.1093/gastro/goac012 ↗
16. 10.1073/pnas.110216410810.1073/pnas.1102164108 ↗
17. 10.1002/advs.20230215910.1002/advs.202302159 ↗
18. 10.3389/fcimb.2019.0034810.3389/fcimb.2019.00348 ↗
19. 10.1136/gutjnl‐2019‐32000510.1136/gutjnl‐2019‐320005 ↗
20. 10.1111/1462‐2920.1318210.1111/1462‐2920.13182 ↗
21. 10.1128/MMBR.68.3.560‐602.200410.1128/MMBR.68.3.560‐602.2004 ↗
22. 10.1038/s41396‐018‐0061‐910.1038/s41396‐018‐0061‐9 ↗
23. 10.1101/gr.122705.11110.1101/gr.122705.111 ↗
24. 10.1016/j.celrep.2021.10913210.1016/j.celrep.2021.109132 ↗
25. 10.1128/mSystems.00044‐1810.1128/mSystems.00044‐18 ↗
26. 10.1038/s41467‐022‐32832‐w10.1038/s41467‐022‐32832‐w ↗
27. 10.1016/j.chom.2019.09.00910.1016/j.chom.2019.09.009 ↗
28. 10.1038/s41564‐024‐01906‐410.1038/s41564‐024‐01906‐4 ↗
29. 10.1136/gutjnl‐2017‐31395210.1136/gutjnl‐2017‐313952 ↗
30. 10.1128/msystems.00931‐2210.1128/msystems.00931‐22 ↗
31. 10.1017/S002531540601350610.1017/S0025315406013506 ↗
32. 10.1016/j.cell.2015.01.00210.1016/j.cell.2015.01.002 ↗
33. 10.1038/ismej.2015.18310.1038/ismej.2015.183 ↗
34. 10.3389/fcimb.2021.67192610.3389/fcimb.2021.671926 ↗
35. 10.1128/mSphere.00833‐1910.1128/mSphere.00833‐19 ↗
36. 10.1111/mec.1689310.1111/mec.16893 ↗
37. 10.1038/s41467‐024‐49840‐710.1038/s41467‐024‐49840‐7 ↗
38. 10.1136/gutjnl‐2024‐33451610.1136/gutjnl‐2024‐334516 ↗
39. 10.1080/19490976.2016.127081110.1080/19490976.2016.1270811 ↗
40. 10.3389/fmicb.2022.85920610.3389/fmicb.2022.859206 ↗
41. 10.1038/s41579‐022‐00755‐410.1038/s41579‐022‐00755‐4 ↗
42. 10.3390/md2109046110.3390/md21090461 ↗
43. 10.1016/j.carbpol.2014.08.06810.1016/j.carbpol.2014.08.068 ↗
44. 10.1016/j.carbpol.2011.05.05910.1016/j.carbpol.2011.05.059 ↗
45. 10.1023/B:JAPH.0000047783.36600.ef10.1023/B:JAPH.0000047783.36600.ef ↗
46. 10.1016/j.biopha.2008.03.00610.1016/j.biopha.2008.03.006 ↗
47. 10.1016/j.bpj.2014.08.03210.1016/j.bpj.2014.08.032 ↗
48. 10.1529/biophysj.107.11547710.1529/biophysj.107.115477 ↗
49. 10.1016/j.ijbiomac.2024.13284510.1016/j.ijbiomac.2024.132845 ↗
50. 10.1016/j.carbpol.2022.12046010.1016/j.carbpol.2022.120460 ↗
51. 10.1016/S0144‐8617(96)00128‐210.1016/S0144‐8617(96)00128‐2 ↗
52. 10.1016/j.intimp.2007.10.01710.1016/j.intimp.2007.10.017 ↗
53. 10.1016/j.celrep.2024.11463610.1016/j.celrep.2024.114636 ↗
54. 10.1126/science.aaf845110.1126/science.aaf8451 ↗
55. 10.1038/nature1719310.1038/nature17193 ↗
56. 10.1038/npjbiofilms.2016.1010.1038/npjbiofilms.2016.10 ↗
57. 10.1038/s41467‐025‐58856‐610.1038/s41467‐025‐58856‐6 ↗
58. 10.1038/s41522‐023‐00445‐w10.1038/s41522‐023‐00445‐w ↗
59. 10.1016/j.cell.2018.10.05910.1016/j.cell.2018.10.059 ↗
60. 10.1016/j.chom.2019.10.00910.1016/j.chom.2019.10.009 ↗
61. 10.1186/s40168‐022‐01384‐y10.1186/s40168‐022‐01384‐y ↗
62. 10.1016/j.chom.2018.11.01610.1016/j.chom.2018.11.016 ↗
63. 10.1016/j.jgg.2024.04.01310.1016/j.jgg.2024.04.013 ↗
64. 10.1021/acs.est.3c0545210.1021/acs.est.3c05452 ↗
65. 10.1038/1841079b010.1038/1841079b0 ↗
66. 10.1038/s41580‐023‐00645‐410.1038/s41580‐023‐00645‐4 ↗
67. 10.1080/19490976.2025.248976510.1080/19490976.2025.2489765 ↗
68. 10.1093/femsle/fnac07210.1093/femsle/fnac072 ↗
69. 10.1083/jcb.20190103310.1083/jcb.201901033 ↗
70. 10.1038/srep2899010.1038/srep28990 ↗
71. 10.3945/jn.108.10412510.3945/jn.108.104125 ↗
72. 10.1126/sciadv.adq462410.1126/sciadv.adq4624 ↗
73. 10.1186/s40168‐024‐01876‐z10.1186/s40168‐024‐01876‐z ↗
74. 10.1186/1471‐2180‐2‐810.1186/1471‐2180‐2‐8 ↗
75. 10.1016/j.ijbiomac.2020.11.11610.1016/j.ijbiomac.2020.11.116 ↗
76. 10.1021/acs.jafc.0c0255510.1021/acs.jafc.0c02555 ↗
77. 10.1016/j.cmet.2024.10.00110.1016/j.cmet.2024.10.001 ↗
78. 10.3748/wjg.v22.i32.735310.3748/wjg.v22.i32.7353 ↗
79. 10.3390/v1105043510.3390/v11050435 ↗
80. 10.1186/s40168‐018‐0410‐y10.1186/s40168‐018‐0410‐y ↗
81. 10.3389/fcimb.2021.69865710.3389/fcimb.2021.698657 ↗
82. 10.1038/s41598‐019‐46087‐x10.1038/s41598‐019‐46087‐x ↗
83. 10.1002/0471250953.bi0103s1310.1002/0471250953.bi0103s13 ↗
84. 10.1093/bioinformatics/btp16310.1093/bioinformatics/btp163 ↗
85. 10.1093/nar/gkq101910.1093/nar/gkq1019 ↗
86. 10.1093/bioinformatics/bty56010.1093/bioinformatics/bty560 ↗
87. 10.1093/bioinformatics/btac13710.1093/bioinformatics/btac137 ↗
88. 10.1093/bioinformatics/btp35210.1093/bioinformatics/btp352 ↗
89. 10.1186/s13059‐019‐1891‐010.1186/s13059‐019‐1891‐0 ↗
90. 10.1371/journal.pone.016396210.1371/journal.pone.0163962 ↗
91. 10.1101/gr.213959.11610.1101/gr.213959.116 ↗
92. 10.1186/s40168‐020‐00990‐y10.1186/s40168‐020‐00990‐y ↗
93. 10.1038/s41587‐020‐00774‐710.1038/s41587‐020‐00774‐7 ↗
94. 10.1016/S0022‐2836(05)80360‐210.1016/S0022‐2836(05)80360‐2 ↗
95. 10.1186/1471‐2105‐10‐42110.1186/1471‐2105‐10‐421 ↗
96. 10.1093/nar/gkaa94610.1093/nar/gkaa946 ↗
97. 10.1093/bioinformatics/btl15810.1093/bioinformatics/btl158 ↗
98. 10.1093/bioinformatics/bts01410.1093/bioinformatics/bts014 ↗
99. 10.7717/peerj.1139610.7717/peerj.11396 ↗
100. 10.1186/s40168‐020‐00867‐010.1186/s40168‐020‐00867‐0 ↗