An in silico framework for the rational design of vaginal probiotic therapy.
Bacterial vaginosis (BV) is a common condition characterized by a shift in vaginal microbiome composition that is linked to negative reproductive outcomes and increased susceptibility to sexually transmitted infections. Despite the commonality of BV, standard-of-care antibiotics provide limited cont...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-02-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012064 |
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| author | Christina Y Lee Sina Bonakdar Kelly B Arnold |
| author_facet | Christina Y Lee Sina Bonakdar Kelly B Arnold |
| author_sort | Christina Y Lee |
| collection | DOAJ |
| description | Bacterial vaginosis (BV) is a common condition characterized by a shift in vaginal microbiome composition that is linked to negative reproductive outcomes and increased susceptibility to sexually transmitted infections. Despite the commonality of BV, standard-of-care antibiotics provide limited control of recurrent BV episodes and development of new biotherapies is limited by the lack of controlled models needed to evaluate new dosing and treatment regimens. Here, we develop an in silico framework to evaluate selection criteria for potential probiotic strains, test adjunctive therapy with antibiotics, and alternative dosing strategies. This computational framework highlighted the importance of resident microbial species on the efficacy of hypothetical probiotic strains, identifying specific interaction parameters between resident non-optimal anaerobic bacteria (nAB) and Lactobacillus spp. with candidate probiotic strains as a necessary selection criterion. Model predictions were able to replicate results from a recent phase 2b clinical trial for the live biotherapeutic product, Lactin-V, demonstrating the relevance of the in silico platform. Results from the computational model support that the probiotic strain in Lactin-V requires adjunctive antibiotic therapy to be effective, and that increasing the dosing frequency of the probiotic could have a moderate impact on BV recurrence at 12 and 24 weeks. Altogether, this framework could provide evidence for the rational selection of probiotic strains and help optimize dosing frequency or adjunctive therapies. |
| format | Article |
| id | doaj-art-41825be784f94fec80cfadb63c328f77 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-41825be784f94fec80cfadb63c328f772025-08-20T02:28:41ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-02-01212e101206410.1371/journal.pcbi.1012064An in silico framework for the rational design of vaginal probiotic therapy.Christina Y LeeSina BonakdarKelly B ArnoldBacterial vaginosis (BV) is a common condition characterized by a shift in vaginal microbiome composition that is linked to negative reproductive outcomes and increased susceptibility to sexually transmitted infections. Despite the commonality of BV, standard-of-care antibiotics provide limited control of recurrent BV episodes and development of new biotherapies is limited by the lack of controlled models needed to evaluate new dosing and treatment regimens. Here, we develop an in silico framework to evaluate selection criteria for potential probiotic strains, test adjunctive therapy with antibiotics, and alternative dosing strategies. This computational framework highlighted the importance of resident microbial species on the efficacy of hypothetical probiotic strains, identifying specific interaction parameters between resident non-optimal anaerobic bacteria (nAB) and Lactobacillus spp. with candidate probiotic strains as a necessary selection criterion. Model predictions were able to replicate results from a recent phase 2b clinical trial for the live biotherapeutic product, Lactin-V, demonstrating the relevance of the in silico platform. Results from the computational model support that the probiotic strain in Lactin-V requires adjunctive antibiotic therapy to be effective, and that increasing the dosing frequency of the probiotic could have a moderate impact on BV recurrence at 12 and 24 weeks. Altogether, this framework could provide evidence for the rational selection of probiotic strains and help optimize dosing frequency or adjunctive therapies.https://doi.org/10.1371/journal.pcbi.1012064 |
| spellingShingle | Christina Y Lee Sina Bonakdar Kelly B Arnold An in silico framework for the rational design of vaginal probiotic therapy. PLoS Computational Biology |
| title | An in silico framework for the rational design of vaginal probiotic therapy. |
| title_full | An in silico framework for the rational design of vaginal probiotic therapy. |
| title_fullStr | An in silico framework for the rational design of vaginal probiotic therapy. |
| title_full_unstemmed | An in silico framework for the rational design of vaginal probiotic therapy. |
| title_short | An in silico framework for the rational design of vaginal probiotic therapy. |
| title_sort | in silico framework for the rational design of vaginal probiotic therapy |
| url | https://doi.org/10.1371/journal.pcbi.1012064 |
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