Biology subjects

Larripa, K.

Publications and source records attributed to Larripa, K..

4 recordsLinked to original sources

bioRxiv2025

Modeling Bistable Dynamics Arising from Macrophage-Tumor Interactions in the Tumor Microenvironment

Macrophages in the tumor microenvironment (TME), known as tumor-associated macrophages (TAMs), originate primarily from circulating monocytes that differentiate under the influence of tumor-derived signals. Within the TME, naive macrophages can adopt either a pro-inflammatory, anti-tumor (M1-like) or anti-inflammatory, pro-tumor (M2-like) phenotype. These pheno-typic shifts significantly affect tumor progression, making TAMs attractive targets for therapeutic intervention aimed at blocking recruitment, promoting anti-tumor polarization, or disrupting tumor-macrophage interactions. In this study, we develop a mathematical model capturing the temporal dynamics of tumor volume alongside populations of naive, M1-like, M2-like, and mixed (M1/M2) phenotype TAMs. The model incorporates the bidirectional influence between tumor development and macrophage polarization. We conduct the bifurcation as well as global sensitivity analyses to identify regions of bistability for tumor dynamics in the parameter space and the impact of sensitive parameters on TME. The model results are then linked to treatment strategies that may effectively induce transitions from high to low tumor burden. HighlightsO_LIWe propose a mathematical model to describe the temporal evolution of the tumor volume alongside different phenotypes of tumor-associated macrophages (TAMs). C_LIO_LIWe investigate the impact of TAMs on tumor growth and decline as well as the influence of the tumor on transition rates between different TAM phenotypes. C_LIO_LIBifurcation and global sensitivity analyses reveal the regions of bistability for tumor dynamics and the impact of sensitive model parameters on the tumor microenvironment. C_LIO_LIModel results are linked to treatment strategies that manipulate the bistable system to transition from high to low tumor volume. C_LI

systems biology↗

bioRxiv2022

Macrophage phenotype transitions in a stochasticgene-regulatory network model

Polarization is the process by which a macrophage cell commits to a phenotype based on external signal stimulation. To know how this process is affected by random fluctuations and events within a cell is of utmost importance to better understand the underlying dynamics and predict possible phenotype transitions. For this purpose, we develop a stochastic modeling approach for the macrophage polarization process. We classify phenotype states using the Robust Perron Cluster Analysis and quantify transition pathways and probabilities by applying Transition Path Theory. Depending on the model parameters, we identify four bistable and one tristable phenotype configuration. We find that bistable transitions are fast but their states less robust. In contrast, phenotype transitions in the tristable situation have a comparatively long time duration, which reflects the robustness of the states. The results indicate parallels in the overall transition behavior of macrophage cells with other heterogeneous and plastic cell types, such as cancer cells. Our approach allows for a probabilistic interpretation of macrophage phenotype transitions and biological inference on phenotype robustness. In general, the methodology can easily be adapted to other systems where random state switches are known to occur.

systems biology↗

bioRxiv2020

MATHEMATICAL MODELING OF RETINAL DEGENERATION: AEROBIC GLYCOLYSIS IN A SINGLE CONE

Cell degeneration, including that resulting in retinal diseases, is linked to metabolic issues. In the retina, photoreceptor degeneration can result from imbalance in lactate production and consumption as well as disturbances to pyruvate and glucose levels. To identify the key mechanisms in metabolism that may be culprits of this degeneration, we use a nonlinear system of differential equations to mathematically model the metabolic pathway of aerobic glycolysis in a healthy cone photoreceptor. This model allows us to analyze the levels of lactate, glucose, and pyruvate within a single cone cell. We perform numerical simulations, use available metabolic data to estimate parameters and fit the model to this data, and conduct a sensitivity analysis using two different methods (LHS/PRCC and eFAST) to identify pathways that have the largest impact on the system. Using bifurcation techniques, we find that the system has a bistable regime, biologically corresponding to a healthy versus a pathological state. The system exhibits a saddle node bifurcation and hysteresis. This work confirms the necessity for the external glucose concentration to sustain the cell even at low initial internal glucose levels. It also validates the role of {beta}-oxidation of fatty acids which fuel oxidative phosphorylation under glucose- and lactate-depleted conditions, by showing that the rate of {beta}-oxidation of ingested outer segment fatty acids in a healthy cone cell must be low. Model simulations reveal the modulating effect of external lactate in bringing the system to steady state; the bigger the difference between external lactate and initial internal lactate concentrations, the longer the system takes to achieve steady state. Parameter estimation for metabolic data demonstrates the importance of rerouting glucose and other intermediate metabolites to produce glycerol 3-phosphate (G3P), thus increasing lipid synthesis (a precursor to fatty acid production) to support their high growth rate. While a number of parameters are found to be significant by one or both of the methods for sensitivity analysis, the rate of {beta}-oxidation of ingested outer segment fatty acids is shown to consistently play an important role in the concentration of glucose, G3P, and pyruvate, whereas the extracellular lactate level is shown to consistently play an important role in the concentration of lactate and acetyl coenzyme A. The ability of these mechanisms to affect key metabolites variability and levels (as revealed in our analyses) signifies the importance of inter-dependent and inter-connected feedback processes modulated by and affecting both the RPEs and cones metabolism.

systems biology↗

bioRxiv2020

Bifurcation and sensitivity analysis reveal key drivers of multistability in a model of macrophage polarization.

In this paper, we present and analyze a mathematical model for polarization of a single macrophage which, despite its simplicity, exhibits complex dynamics in terms of multistability. In particular, we demonstrate that an asymmetry in the regulatory mechanisms and parameter values is important for observing multiple phenotypes. Bifurcation and sensitivity analyses show that external signaling cues are necessary for macrophage commitment and emergence to a phenotype, but that the intrinsic macrophage metabolism is equally important. Based on our numerical results, we formulate hypotheses that could be further investigated by in vitro experiments to deepen our understanding of macrophage polarization. 2010 MSC93A30, 34C23, 49Q12, 92C42, 37N25

systems biology↗