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The outcome of phagocytic cell division with infectious cargo depends on single phagosome formation.

ABSTRACT: Given that macrophages can proliferate and that certain microbes survive inside phagocytic cells, the question arises as to the post-mitotic distribution of microbial cargo. Using macrophage-like cells we evaluated the post-mitotic distribution of intracellular Cryptococcus yeasts and polystyrene beads by comparing experimental data to a stochastic model. For beads, the post-mitotic distribution was that expected from chance alone. However, for yeast cells the post-mitotic distribution was unequal, implying preferential sorting to one daughter cell. This mechanism for unequal distribution was phagosomal fusion, which effectively reduced the intracellular particle number. Hence, post-mitotic intracellular particle distribution is stochastic, unless microbial and/or host factors promote unequal distribution into daughter cells. In our system unequal cargo distribution appeared to benefit the microbe by promoting host cell exocytosis. Post-mitotic infectious cargo distribution is a new parameter to consider in the study of intracellular pathogens since it could potentially define the outcome of phagocytic-microbial interactions.

SUBMITTER: Luo Y

PROVIDER: S-EPMC2535564 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature

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The outcome of phagocytic cell division with infectious cargo depends on single phagosome formation.

Luo Yong Y Alvarez Mauricio M Xia Lingchuan L Casadevall Arturo A

PloS one 20080916 9

Given that macrophages can proliferate and that certain microbes survive inside phagocytic cells, the question arises as to the post-mitotic distribution of microbial cargo. Using macrophage-like cells we evaluated the post-mitotic distribution of intracellular Cryptococcus yeasts and polystyrene beads by comparing experimental data to a stochastic model. For beads, the post-mitotic distribution was that expected from chance alone. However, for yeast cells the post-mitotic distribution was unequ ...[more]

PMID: 18795151

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Project description:The receptors engaged during phagocytic particle uptake determine the signaling events that occur during phagosome formation and maturation. However, pathogens generally have multiple ligands, making it difficult to dissect the roles of individual receptors in these processes. Here, we used latex beads coupled to single ligands, focusing on IgG, mannan, LPS and avidin, and monitored phagocytic uptake rates, phago-lysosomal fusion events, macrophage gene expression and the proteomic composition of isolated phagosomes. The pattern of gene expression and the protein composition of isolated phagosomes showed that each bead ligand altered a distinct pattern of genes and led to a different composition of phagosomes. These data argue that activation of each receptor initiates a specific signature of signaling events that last many hours and influences several phagocytosis functions. All samples and controls were carried out in triplicates. J774.A1 cells (mouse macrophage-like cell line) were seeded onto 6-well plates one day before the experiment. Subsequently, cells were incubated with serum-free DME medium containing 0.01 % latex beads of 1 Âµm diameter coupled to the following ligands: avidin (Av), the Fc fragment of mouse IgG (Fc), lipopolysaccharides from Klebsiella pneumoniae (LPS) and mannan from Saccharomyces cerevisae (Man) for 30 and 60 minutes. After incubation, samples as well as untreated controls were washed twice in PBS and total RNA was extracted using RNeasy kit (Qiagen) following manufacturer's instructions. Each sample was hybridized to CodeLink Mouse whole genome bioarray slides (Amersham). This study was intended to analyze the role of receptor-ligand interactions on phagosome maturation and gene expression after receptor-mediated phagocytosis in macrophages. CodeLink EXP v4.0-processed data are represented in the Sample tables, GeneSpring-processed data are linked as a supplementary files to the matrix table, additional results available as a supplementary file on the Series record. http://www.biologie.uni-rostock.de/tierphysiologie/agkuznetsov.html

Project description:The ability to kill infecting microbes is an essential facet of our immune response to an infection. However, phagocytic ability is often overlooked as a part of immunological profile in infected patients' diagnosis, as the understanding of phagocytic capabilities in disease states is incomplete. In this work, we have evaluated for the first time the relationship between blood lactate level and the neutrophil phagocytic activity at a single-cell level. Blood samples (N = 19) were grouped on the basis of their blood lactate levels i.e., below (control) or above 2 mmol L-1 (high-risk) (i.e., 2 mmol L-1 is a common clinical lactate threshold used for patients' triage). Neutrophils were isolated from whole blood and then incubated with fluorescent IgG coated beads for 40 minutes, and the ability of each neutrophil to internalize beads was quantified. Single-cell phagocytic activity analysis has shown interesting findings such as: (i) a single neutrophil was able to internalize up to 7 beads, (ii) for a control group, 39.76% cells didn't internalize any beads, while for a high-risk group, 30.65% cells didn't show any phagocytic activity, (iii) similarly, 30.46% cells internalize only 1 bead in a control group, while for a high-risk group the activity is slightly higher with only 31.73% cells showing single bead internalization, and (iv) 7 bead internalization activity was much higher for samples in a high-risk group (0.6% cells) compared to a control group (0.17% cells). We used multiple statistical tests to compare these differences. For a two-tailed T-test, we used the mean phagocytic activity of the cells (i.e., the average number of beads internalized by cells) isolated from the blood samples in the two groups (1.14 vs. 1.35) and found the p-value to be 0.08. We also used principal component analysis (PCA) on this high dimensional phagocytic activity distribution data and performed dimension reduction. However, the first 3 principal components didn't show a clear distinction between groups. Next, we developed machine learning models using artificial neural networks (ANNs) to differentiate between the distribution of phagocytic activity in neutrophil populations of the two groups. Our models yielded area under curve (AUC) values below 0.7 for receiver operator characteristic curves. Although our study highlighted interesting phagocytic activity findings at a single cell level, it further highlights the need for integration of an individual patient's medical record to get more personalized insights into individual phagocytic activity in the future.

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The outcome of phagocytic cell division with infectious cargo depends on single phagosome formation.

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The outcome of phagocytic cell division with infectious cargo depends on single phagosome formation.

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