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. 2022 Feb 14;12:2458. doi: 10.1038/s41598-022-06422-1

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Characterization of networks (PBINs and PCNs) complexity and expected cocktail efficacy. (A) Analysis of PBINs complexity and symmetry. Each dot represents a single matrix (see Fig. 2) and the fill (%) is represented by color intensity. The cyan line indicates the position of symmetric matrices. (B) Distribution of PCNs grouped by the number of phages (MCS). Each bar sector represents a PCN and its length correlates with the number of bacteria lysed by the cocktail. (C) Comparison of MCS and Φ estimators. 34 PBINs, taken from Molina et al.²⁵, were sorted by decreasing size. Bar length indicates the MCS, whereas color corresponds to the MCS/Φ ratio. (D) Expected cocktail efficacy vs. MCS. The fraction (%) of bacteria susceptible to at least one phage of the cocktail is shown for every PBIN. The number of bacteria is grouped by percentiles and represented by a density plot.