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Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

ABSTRACT: The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage-Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage-C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells.

SUBMITTER: Duhring S

PROVIDER: S-EPMC5550964 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Modelling the host-pathogen interactions of macrophages and <i>Candida albicans</i> using Game Theory and dynamic optimization.

Dühring Sybille S Ewald Jan J Germerodt Sebastian S Kaleta Christoph C Dandekar Thomas T Schuster Stefan S

Journal of the Royal Society, Interface 20170701 132

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage-<i>Candida albicans< ...[more]

PMID: 28701506

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Project description:Purpose: The purpose of this study was to simulataneously examine the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Methods: Membrane stained (Deep Red),primary, bone marrow derived, murine macrophages and Candida albicans expressing GFP and mCherry were exposed to each other over a four hour time course. Samples were collected at 0, 1, 2 and 4 hours and sorted for four infection subpopulations: 1. Macrophages which phagocytosed live C. albicans (GFP+ /mCherry+ /Deep Red +), 2. Macrophages which phagocytosed dead C. albicans (GFP- /mCherry+ /Deep Red +), 3. Uninfected macrophages(GFP- /mCherry- /Deep Red +) and 4. Unengulfed C. albicans (GFP+ /mCherry + /Deep Red -). Unexposed controls were also collected for some time points (i.e. macrophages never exposed to C. albicans and C. albicans never exposed to macrophages). Single macrophages infected with live or dead C. albicans were also sorted. Smart-seq2 was used to create libraries for both infection subpopulation and single, infected cell samples that were sequenced on Illumina’s Miseqand Nextseq. Basic quality assessment of Illumina reads and sample demultiplexing was done with Picard version 1.107 and Trimmomatic. Samples profiling exclusively the mouse transcriptional response were aligned to the mouse transcriptome generated from the v. Dec. 2011 GRCm38/mm10 and a collection of mouse rRNA sequences from the UCSC genome website. Samples profiling exclusively the yeast transcriptional response were aligned to the C. albicans transcriptome strain SC5314 version A21-s02-m09-r10 downloaded from Candida Genome Database. Samples containing both macrophages and C. albicans were aligned to a “composite transcriptome” made by combining the mouse transcriptome and C. albicans transcriptomes described above and alignment was done via BWA (version 0.7.10-r789.) Multi-reads (reads that aligned to both host and pathogen transcripts) were discarded. Then, each host or pathogen sample file were aligned to its corresponding reference using Bowtie2 and RSEM (v.1.2.21). Transcript abundance was estimated using transcripts per million (TPM). For subpopulation samples, TPM was calculated using edgeR, all as implemented in the Trinity package version 2.1.. Genes were considered differentially expressed only if they had a 4-fold change difference (> 4 FC) in TPM values and a false discovery rate below or equal to 0.001 (FDR < 0.001), unless specified otherwise. For single macrophages infected with C. albicans, samples were aligned to the combined transcriptome as described above and RSEM was used to calculate TPM. Results: We were able to simultaneously measure the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Conclusions: Our study represents an analysis of both distinct infection populations of macrophages and fungus.

Dataset Information

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

Publications

Modelling the host-pathogen interactions of macrophages and <i>Candida albicans</i> using Game Theory and dynamic optimization.

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