Release kinetics and cell trafficking in relation to bacterial growth explain the time course of blood neutrophils and monocytes during primary Salmonella infection

An Integrative multi-lineage model of variation in leukopoiesis and acute myelogenous leukemia

Background

Acute myelogenous leukemia (AML) progresses uniquely in each patient. However, patients are typically treated with the same types of chemotherapy, despite biological differences that lead to differential responses to treatment.

Results

Here we present a multi-lineage multi-compartment model of the hematopoietic system that captures patient-to-patient variation in both the concentration and rates of change of hematopoietic cell populations. By constraining the model against clinical hematopoietic cell recovery data derived from patients who have received induction chemotherapy, we identified trends for parameters that must be met by the model; for example, the mitosis rates and the probability of self-renewal of progenitor cells are inversely related. Within the data-consistent models, we found 22,796 parameter sets that meet chemotherapy response criteria. Simulations of these parameter sets display diverse dynamics in the cell populations. To identify large trends in these model outputs, we clustered the simulated cell population dynamics using k-means clustering and identified thirteen ‘representative patient’ dynamics. In each of these patient clusters, we simulated AML and found that clusters with the greatest mitotic capacity experience clinical cancer outcomes more likely to lead to shorter survival times. Conversely, other parameters, including lower death rates or mobilization rates, did not correlate with survival times.

Conclusions

Using the multi-lineage model of hematopoiesis, we have identified several key features that determine leukocyte homeostasis, including self-renewal probabilities and mitosis rates, but not mobilization rates. Other influential parameters that regulate AML model behavior are responses to cytokines/growth factors produced in peripheral blood that target the probability of self-renewal of neutrophil progenitors. Finally, our model predicts that the mitosis rate of cancer is the most predictive parameter for survival time, followed closely by parameters that affect the self-renewal of cancer stem cells; most current therapies target mitosis rate, but based on our results, we propose that additional therapeutic targeting of self-renewal of cancer stem cells will lead to even higher survival rates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0469-2) contains supplementary material, which is available to authorized users.

PSGL-1 and mTOR regulate translation of ROCK-1 and physiological functions of macrophages

Rho-associated kinases (ROCKs) are critical molecules involved in the physiological functions of macrophages, such as chemotaxis and phagocytosis. We demonstrate that macrophage adherence promotes rapid changes in physiological functions that depend on translational upregulation of preformed ROCK-1 mRNA, but not ROCK-2 mRNA. Before adherence, both ROCK mRNAs were present in the cytoplasm of macrophages, whereas ROCK proteins were undetectable. Macrophage adherence promoted signaling through P-selectin glycoprotein ligand-1 (PSGL-1)/Akt/mTOR that resulted in synthesis of ROCK-1, but not ROCK-2. Following synthesis, ROCK-1 was catalytically active. In addition, there was a rapamycin/sirolimus-sensitive enhanced loading of ribosomes on preformed ROCK-1 mRNAs. Inhibition of mTOR by rapamycin abolished ROCK-1 synthesis in macrophages resulting in an inhibition of chemotaxis and phagocytosis. Macrophages from PSGL-1-deficient mice recapitulated pharmacological inhibitor studies. These results indicate that receptor-mediated regulation at the level of translation is a component of a rapid set of mechanisms required to direct the macrophage phenotype upon adherence and suggest a mechanism for the immunosuppressive and anti-inflammatory effects of rapamycin/sirolimus.