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    188宝金博页面版: Towards modeling phage therapy_2026_Rob J. de Boer

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    内容提示： PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1014408 June 22, 2026 1 / 31 OPEN ACCESSCitation: de Boer RJ, Schooley R, Perelson AS (2026) Towards modeling phage therapy. PLoS Comput Biol 22(6): e1014408. https://doi.org/10.1371/journal.pcbi.1014408Editor: Roland R Regoes, ETH Zurich Department of Environmental Systems Science: Eidgenossische Technische Hochschule Departement Umweltsystemwissenschaften, SWITZERLANDReceived: November 10, 2025Accepted: June 4, 2026Published: June 22, 202...

    文档格式：PDF | 页数：31 | 浏览次数：3 | 上传日期：2026-07-06 20:35:24 | 文档星级：
    PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1014408 June 22, 2026 1 / 31 OPEN ACCESSCitation: de Boer RJ, Schooley R, Perelson AS (2026) Towards modeling phage therapy. PLoS Comput Biol 22(6): e1014408. https://doi.org/10.1371/journal.pcbi.1014408Editor: Roland R Regoes, ETH Zurich Department of Environmental Systems Science: Eidgenossische Technische Hochschule Departement Umweltsystemwissenschaften, SWITZERLANDReceived: November 10, 2025Accepted: June 4, 2026Published: June 22, 2026Peer Review History: PLOS recognizes the benef i ts of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside fi nal, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pcbi.1014408Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modif i ed, built upon, or otherwise used by anyone for any lawful RESEARCH ARTICLETowards modeling phage therapyRob J. de Boer1,2 *, Robert Schooley 3 , Alan S. Perelson 2,41 Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands, 2 Santa Fe Institute, Santa Fe, New Mexico, United States of America, 3 Department of Medicine, University of California, San Diego, La Jolla, California, United States of America, 4 Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico , United States of America * r.j.deboer@uu.nlAbstract Patients infected with life-threatening multi-drug resistant (MDR) bacteria have been treated with cocktails of bacteriophages. This is a complicated form of personalized medicine as the phages given to a patient have to be selected beforehand on the basis of their lytic capacity of the infecting bacteria. Because bacteria rapidly become resistant, the evolution of resistance to a diverse cocktail of phages is a complicated dynamical process, during which competing bacterial strains replace one another by accumulating several resistance mechanisms, each of which may involve a fitness cost. As a consequence, it is typically not known why a particular phage therapy succeeded or failed, and how one can optimize the composition of the cocktails to maximize the rate of success. To improve upon this, we extend an existing in vivo- calibrated mouse model into a novel mathematical model for the human situation, and include multiple phages infecting multiple bacterial strains, differing in their resis-tance to each of the phages. We adjust several parameter estimates of the bacterial model to the human situation, and use the model to describe a successful case of phage therapy involving several cocktails, each containing several phages. In the model, treatment success crucially depended on pretreatment resistance levels, and on the diversity and the timing of the cocktails. Once an appropriate cocktail is found, it is less important to further optimize the infection rates of the phages. Resistant bac-terial strains expand rapidly when sensitive strains decline, and the higher the infec-tivity of the phages, the faster resistant strains expand. Because resistance evolves rapidly, it is best to provide a diverse set of phages right from the start of therapy, i.e., to hit hard and early, and create a high genetic barrier to bacterial resistance.Author summary Patients with dangerous antibiotic-resistant bacteria have been treated with mixtures of bacteriophages — viruses that infect bacteria. This treatment is highly

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