Biology subjects

Mac Gabhann, F.

Publications and source records attributed to Mac Gabhann, F..

8 recordsLinked to original sources

bioRxiv2025

Computational modeling of hormone- and cytokine-dependent proliferation of endometrial cells in 3D co-culture

The endometrium and menstrual disorders, such as endometriosis and adenomyosis, are difficult to study, partly because menstruation depends on interactions between multiple cell types through complex molecular mechanisms. To help understand this system, researchers need humanized experimental and computational models that can interrogate how endometrial cell populations impact each other in both physiological and pathological conditions. Here, we use ordinary differential equations (ODEs) to model changes in the rates of endometrial cell proliferation and death in response to hormones, cytokines, and the specific cell types present. To calibrate this computational model, we used previous-published experimental datasets from a 3D co-culture platform supporting primary human endometrial epithelial organoids and endometrial stromal cells. Our ODE-based model can simulate the size of endometrial epithelial organoids and the density of stromal cells over time under multiple hormone/cytokine conditions in mono- and co-cultures. We further created a second, partial differential equation (PDE)-based model that simulates the diffusion of molecules added to these 3D cultures and their uptake by proliferating endometrial cells using the predicted cell densities from the ODE model as inputs to the PDE simulations. We show that the exposure to hormones and cytokines used in the experiments is reasonably homogenous throughout the 3D culture and identify conditions where this would not be true. Altogether we use these models to quantify the influence of stromal cells on epithelial cell proliferation and vice versa, to identify differences across cells from different donors, and to provide a quantitative assessment of experimental designs.

systems biology↗

bioRxiv2025

Data-driven simulations elucidate how lymphocyte motility behaviors drive cell-cell interactions within germinal centers

Lymphocytes rely on cell motility to surveil immune microenvironments and engage in contact-mediated interactions with other cells as part of the adaptive immune response. Within the germinal center (GC) light zone, germinal center B-cells (GCBs) and T-follicular helper cells (Tfhs) engage in cell-cell interactions that enable antibody affinity maturation. The number and duration of GCB-Tfh interactions correlate with the success of the germinal center in effectively generating antibodies that can bind and neutralize antigens. Prior studies have shown that GCBs and Tfhs exploit distinct motility patterns to surveil the GC light zone and engage in these cell-cell interactions. However, the quantitative relationship between lymphocyte motility parameters (such as speed and tortuosity) and GCB-Tfh interactions has not been systematically explored. Here, we analyzed single-cell trajectories of GCBs and Tfhs from two-photon intravital microscopy videos of GCs within mouse popliteal lymph nodes. We found that these cells exhibit seven distinct motility behaviors, each with characteristic speeds and tortuosities. GCBs tended to move in slow and tortuous paths, while Tfhs adopted faster and more directed trajectories. We then developed a three-dimensional agent-based model (ABM) to simulate these experimentally-observed GCB and Tfh motility behaviors and predict their impact on GCB-Tfh interactions. Using the ABM, we found that the baseline motility behaviors of GCBs and Tfhs allow GCBs to maximize interactions with distinct Tfhs in a confined space.

systems biology↗

bioRxiv2025

Quantitative systems pharmacology modeling of pyrrolobenzodiazepine antibody-drug conjugates targeting BCMA

Antibody-drug conjugates (ADCs) are novel therapeutics combining two molecules linked together: an antibody that provides targeting to specific cells, and a cytotoxic drug (warhead) that can deconjugate from the antibody and kill those cells. The warhead by itself would be too nonspecific and toxic; the antibody by itself would be insufficiently effective at killing the cells. As more and more ADCs enter the drug development pipeline, understanding the mechanistic reasons behind efficacy and toxicity is critical to evaluating both successful and failed trials. Here, we have developed a mechanistic computational model of ADCs, and specifically parameterize it using data for MEDI2228, an anti-BCMA antibody conjugated to pyrrolobenzodiazepine (PBD) warheads. We build the model to track not only the concentrations of ADC and its released warhead drug inside and outside the cell, but also to track the recent history of the warhead, so that we can distinguish between pathways for on-target and bystander (nontargeted) cell killing. We show that this effect is predicted to be small under in vitro conditions due to dilution in large volumes of media, but likely to form a significant part of both targeted and nontargeted cell killing in vivo, where the extracellular volume has less of a dilution effect. We also explore the impact of key design parameters of ADCs, including drug to antibody ratio (DAR), warhead potency, and lipophilicity; this analysis demonstrates the balance needed between killing of targeted and nontargeted cells. Using this quantitative systems pharmacology model, we can generate insights for optimization of ADC design and determine which factors are most critical to efficacy and toxicity, leading to more informed and rational development of cancer therapies.

systems biology↗

bioRxiv2025

Mechanistic computational modeling of sFLT1 secretion dynamics

Constitutively secreted by endothelial cells, soluble FLT1 (sFLT1 or sVEGFR1) binds and sequesters extracellular vascular endothelial growth factors (VEGF), thereby reducing VEGF binding to VEGF receptor tyrosine kinases and their downstream signaling. In doing so, sFLT1 plays an important role in vascular development and in the patterning of new blood vessels in angiogenesis. Here, we develop multiple mechanistic models of sFLT1 secretion and identify a minimal mechanistic model that recapitulates key qualitative and quantitative features of temporal experimental datasets of sFLT1 secretion from multiple studies. We show that the experimental data on sFLT1 secretion is best represented by a delay differential equation (DDE) system including a maturation term, reflecting the time required between synthesis and secretion. Using optimization to identify appropriate values for the key mechanistic parameters in the model, we show that two model parameters (extracellular degradation rate constant and maturation time) are very strongly constrained by the experimental data, and that the remaining parameters are related by two strongly constrained constants. Thus, only one degree of freedom remains, and measurements of the intracellular levels of sFLT1 would fix the remaining parameters. Comparison between simulation predictions and additional experimental data of the outcomes of chemical inhibitors and genetic perturbations suggest that intermediate values of the secretion rate constant best match the simulation with experiments, which would completely constrain the model. However, some of the inhibitors tested produce results that cannot be reproduced by the model simulations, suggesting that additional mechanisms not included here are required to explain those inhibitors. Overall, the model reproduces most available experimental data and suggests targets for further quantitative investigation of the sFLT1 system. Author SummaryProteins that are typically found outside cells are initially made inside cells, and later secreted into extracellular space. Many of these secreted proteins have important functions outside the cell that are well-studied; however, usually much less is known about the pre-secretion life of these molecules. Many computational models only represent the extracellular versions of secreted proteins, reducing all production and secretion steps into a single modeled process. Here, we develop a mechanistic model of the production and secretion of a specific secreted protein, sFLT1, which inhibits blood vessel growth by acting as an extracellular sponge for another set of secreted proteins, the vascular endothelial growth factors. We compare several models to existing experimentally-measured sFLT1 data, and we show that the data are most simply explained by including a delay between intracellular sFLT1 production and sFLT1 transport or degradation. This is consistent with the biology of the cells secretory pathway, where immature proteins are gradually processed into mature forms over minutes to hours. Our approach could be incorporated into improved models for any pathway involving secreted proteins, including sFLT1-regulated models of blood vessel biology.

bioinformatics↗

bioRxiv2024

Impact of ligand binding on VEGFR1, VEGFR2, and NRP1 localization in human endothelial cells

The vascular endothelial growth factor receptors (VEGFRs) bind to cognate ligands to facilitate signaling pathways critical for angiogenesis, the growth of new capillaries from existing vasculature. Intracellular trafficking regulates the availability of receptors on the cell surface to bind ligands, which regulate activation, and the movement of activated receptors between the surface and intracellular pools, where they can initiate different signaling pathways. Using experimental data and computational modeling, we recently demonstrated and quantified the differential trafficking of three VEGF receptors, VEGFR1, VEGFR2, and coreceptor Neuropilin-1 (NRP1). Here, we expand that approach to quantify how the binding of different VEGF ligands alters the trafficking of these VEGF receptors and demonstrate the consequences of receptor localization and ligand binding on the localization and dynamics of signal initiation complexes. We include simulations of four different splice isoforms of VEGF-A and PLGF, each of which binds to different combinations of the VEGF receptors, and we use new experimental data for two of these ligands to parameterize and validate our model. We show that VEGFR2 trafficking is altered in response to ligand binding, but that trafficking of VEGFR1 is not; we also show that the altered trafficking can be explained by a single mechanistic process, increased internalization of the VEGFR2 receptor when bound to ligand; other processes are unaffected. We further show that even though the canonical view of receptor tyrosine kinases is of activation on the cell surface, most of the ligand-receptor complexes for both VEGFR1 and VEGFR2 are intracellular. We also explore the competition between the receptors for ligand binding, the so-called decoy effect, and show that while in vitro on the cell surface minimal such effect would be observed, inside the cell the effect can be substantial and may influence signaling. We term this location dependence the reservoir effect as the size of the local ligand reservoir (large outside the cell, small inside the cell) plays an integral role in the receptor-receptor competition. These results expand our understanding of receptor-ligand trafficking dynamics and are critical for the design of therapeutic agents to regulate ligand availability to VEGFR1 and hence VEGF receptor signaling in angiogenesis.

systems biology↗

bioRxiv2023

Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

systems biology↗

bioRxiv2023

A defined clathrin-mediated trafficking pathway regulates sFLT1/VEGFR1 secretion from endothelial cells

FLT1/VEGFR1 negatively regulates VEGF-A signaling and is required for proper vessel morphogenesis during vascular development and vessel homeostasis. Although a soluble isoform, sFLT1, is often mis-regulated in disease and aging, how sFLT1 is trafficked and secreted from endothelial cells is not well understood. Here we define requirements for constitutive sFLT1 trafficking and secretion in endothelial cells from the Golgi to the plasma membrane, and we show that sFLT1 secretion requires clathrin at or near the Golgi. Perturbations that affect sFLT1 trafficking blunted endothelial cell secretion and promoted intracellular mis-localization in cells and zebrafish embryos. siRNA-mediated depletion of specific trafficking components revealed requirements for RAB27A, VAMP3, and STX3 for post-Golgi vesicle trafficking and sFLT1 secretion, while STX6, ARF1, and AP1 were required at the Golgi. Depletion of STX6 altered vessel sprouting in a 3D angiogenesis model, indicating that endothelial cell sFLT1 secretion is important for proper vessel sprouting. Thus, specific trafficking components provide a secretory path from the Golgi to the plasma membrane for sFLT1 in endothelial cells that utilizes a specialized clathrin-dependent intermediate, suggesting novel therapeutic targets.

cell biology↗

bioRxiv2022

Trafficking dynamics of VEGFR1, VEGFR2, and NRP1 in human endothelial cells

The vascular endothelial growth factor (VEGF) family of cytokines are key drivers of blood vessel growth and remodeling. These ligands act via multiple VEGF receptors (VEGFR) and co-receptors such as Neuropilin (NRP) expressed on endothelial cells. These membrane-associated receptors are not solely expressed on the cell surface, they move between the surface and intracellular locations, where they can function differently. The location of the receptor alters its ability to see (access and bind to) its ligands, which regulates receptor activation; location also alters receptor exposure to subcellularly localized phosphatases, which regulates its deactivation. Thus, receptors in different subcellular locations initiate different signaling, both in terms of quantity and quality. Similarly, the local levels of co-expression of other receptors alters competition for ligands. Subcellular localization is controlled by intracellular trafficking processes, which thus control VEGFR activity; therefore, to understand VEGFR activity, we must understand receptor trafficking. Here, for the first time, we simultaneously quantify the trafficking of VEGFR1, VEGFR2, and NRP1 on the same cells - specifically human umbilical vein endothelial cells (HUVECs). We build a computational model describing the expression, interaction, and trafficking of these receptors, and use it to simulate cell culture experiments. We use new quantitative experimental data to parameterize the model, which then provides mechanistic insight into the trafficking and localization of this receptor network. We show that VEGFR2 and NRP1 trafficking is not the same on HUVECs as on non-human ECs; and we show that VEGFR1 trafficking is not the same as VEGFR2 trafficking, but rather is faster in both internalization and recycling. As a consequence, the VEGF receptors are not evenly distributed between the cell surface and intracellular locations, with a very low percentage of VEGFR1 being on the cell surface, and high levels of NRP1 on the cell surface. Our findings have implications both for the sensing of extracellular ligands and for the composition of signaling complexes at the cell surface versus inside the cell.

systems biology↗