Biology subjects

Peirce, S. M.

Publications and source records attributed to Peirce, S. M..

18 recordsLinked to original sources

bioRxiv2026

A novel in vitro assay for quantifying endothelial cell and pericyte interactions

ObjectiveStructural adaptations of capillary networks, through angiogenesis, arterialization, and regression, are implicated in many diseases, and gaining a better understanding of the cell-cell interactions that underpin these adaptations may lead to novel therapeutic discoveries for disease management. Endothelial cells and pericytes are the two cell types that comprise capillary networks. Experimental model systems have been developed to study the dynamic interactions between endothelial cells and pericytes, providing valuable insights into capillary development, cell-to-cell communication, and responses to growth factors and therapeutic agents. MethodsIn this study, we present a novel and simple co-culture system that uses commercially available primary human endothelial cells and pericytes, does not require microfluidic perfusion, and allows simultaneous observation of cell morphologies and interactions over time in 60 samples, enabling high-throughput analysis of multiple culture conditions with replicates. ResultsImage analysis pipelines were created to quantify microvascular adaptations, including one to measure colocalization between endothelial cells and pericytes, capturing dynamic coupling and uncoupling associated with capillary stability, angiogenesis, and regression. We validated the ability of our co-culture system to reproducibly represent the effects of fibrotic and angiogenic activation signals, including an FDA-approved drug, on endothelial cells, pericytes, and their coupling. ConclusionThis novel, high-throughput microvascular screening assay enables quantification of microvascular dynamics in response to disease-relevant stimuli and therapeutics in a repeatable, real-time manner.

bioengineering↗

bioRxiv2026

Computational Analysis of Fibroblast Subpopulation Dynamics as a Driver of Fibrotic Foci Formation

Fibroblasts maintain the extracellular matrix (ECM) to support tissue homeostasis and wound healing. In fibrotic diseases, fibroblasts are a primary driver of disease progression through excess collagen secretion and enhanced contractility. Replacing native tissue with a collagen rich fibrotic scar leads to a decline in tissue function. Recent research into idiopathic pulmonary fibrosis (IPF) has identified fibroblast subpopulations that may be primed for the hyper-activation that leads to increased progression of fibrotic disease. Understanding the contribution of these subpopulations to disease progression requires integrating experimental and computational techniques to understand their dynamic contributions to tissue phenotype. Herein, we introduce a framework for modeling subpopulations using a multiscale mechanistic computational model to understand differences within subpopulations, at the intracellular level and how these differences contribute to cell-and tissue-level pathology. We build and validate this framework using two well-defined subpopulations of fibroblasts in IPF. The subpopulations are defined by the presence or absence of Thy-1, a cell-surface protein that regulates fibroblast mechanosensing. We first developed a logic-based network model of a fibroblast. We then applied this model to identify sub-networks that regulate myofibroblast marker expression in the two subpopulations. Coupling this with an agent-based model (ABM) of the lung microenvironment, we observed how different rules regulating cell fate decisions in each subpopulation affected collagen content. Computational image outputs were analyzed with the open-source biological image analysis software QuPath to quantify how changes in subpopulation dynamics change model-predicted foci characteristics such as size and collagen density. We find that the ability for Thy-1+ fibroblasts to transition to Thy-1- fibroblasts significantly increases total collagen content, as well as influences fibrotic foci characteristics. Overall, we present a combined experimental and computational framework for studying how dynamic changes in fibroblast subpopulations lead to tissue-level disease phenotypes. Author SummaryIn wound healing fibroblasts are responsible for rebuilding the scaffolding, called the extracellular matrix (ECM), of the damaged tissue to aid in regeneration. In fibrosis, the normal wound healing processes are hijacked leading to overproduction of ECM proteins, such as collagen, by fibroblasts leading to fibrosis. In fibrotic diseases with no known cause, such as idiopathic pulmonary fibrosis (IPF), subpopulations of fibroblasts have been identified as possible drivers of disease. Herein, we use a multiscale computational model that represents intracellular, cellular, and tissue level signaling to study how the presence or absence of a single protein on a fibroblasts surface, Thy-1, affects the formation of fibrotic scar in IPF. Thy-1 regulates how a fibroblast senses the stiffness of the microenvironment. The absence of Thy-1 impacted intracellular signaling and when combined across many cells led to fibrosis at the tissue level. Additionally, if normal Thy-1+ fibroblasts could dynamically lose Thy-1 expression the amount of collagen they produced correlated with that in end stage IPF lungs. This model presents a framework for studying different fibroblast subpopulations using multiscale computational modeling to understand how changes in a single protein in one cell can, over an entire population, affect the dynamics of disease progression.

bioengineering↗

bioRxiv2026

Multimodal PET Defines a Goldilocks Thermal Window for Focused Ultrasound Ablation and Immunotherapy Combinations

BackgroundThermally ablative focused ultrasound (T-FUS) offers a noninvasive, spatially precise strategy for local tumor destruction, with the added potential to remodel tumor architecture and immune dynamics in ways that influence downstream therapeutic delivery and efficacy. Despite promising preclinical and clinical findings, the T-FUS parameters that best balance tumor debulking with preservation of local biologic, e.g. immunotherapy, penetrance remain unclear. Thermal dose, defined by the relationship between tissue heating, exposure duration, and biological effect, is likely a critical determinant of this balance. Excessive thermal dose may eliminate the vascular and stromal features needed to support immunotherapy access, whereas insufficient thermal dose may fail to achieve meaningful cytoreduction. Here, we deploy multimodal PET, contrast-enhanced ultrasound, and tissue profiling to define a "Goldilocks Zone" for T-FUS that balances bulk tumor destruction with immunotherapy delivery. MethodSubtotal T-FUS was applied to 4T1 tumors using three thermal dose regimens resolved by in silico modeling. Ablation was quantified by H&E and TTC staining. Post-ablative perfusion and microvascular coverage were assessed by contrast-enhanced ultrasound and immunofluorescence, respectively. Tumor oxygenation was measured by intravenous hypoxyprobe labeling. After T-FUS, mice underwent dynamic [18F]-FDG PET and immunoPET with a model tumor-targeted antibody, [89Zr]-CD47, to relate cytoreduction to antibody penetrance. ImmunoPET findings were further evaluated by ex vivo biodistribution analysis. ResultsIn silico modeling established three T-FUS regimens that generated distinct thermal dose profiles and were deployed in vivo in a solid breast tumor model. Histopathology, perfusion imaging, and hypoxia analysis revealed dose-dependent and dose-divergent biological effects that informed a candidate Goldilocks thermal window. Low thermal dose produced measurable but limited tumor debulking, whereas high thermal dose caused disproportionate functional perfusion collapse. An intermediate thermal dose achieved robust partial ablation, broad hypoxia relief, and preservation of residual tumor physiology sufficient to support antibody access. Dynamic [18F]-FDG PET confirmed a marked reduction in metabolically active tumor burden after Goldilocks T-FUS. Serial [89Zr]-CD47 immunoPET showed that bulk antibody signal was maintained after ablation, and integration of immunoPET with matched [18F]-FDG PET revealed approximately 3-fold enrichment of antibody exposure within the residual viable tumor compartment of ablated tumors. These findings demonstrate that appropriately tuned thermal ablation can debulk tumor while preserving, and potentially concentrating, immunotherapy access within the remaining targetable tumor niche. ConclusionThis study identifies thermal dose as a critical consideration for T-FUS immunotherapy combinations and establishes a PET-informed framework for balancing cytoreduction with therapeutic delivery. Rather than functioning solely as a local debulking modality, we demonstrate that T-FUS can be tuned to yield a post-ablation tumor state that remains accessible to large biologics. These findings provide timely, translationally relevant guidance for tailoring T-FUS regimens to achieve local tumor destruction while preserving an immunotherapy-permissive niche for combination treatment.

bioengineering↗

bioRxiv2026

An agent-based model suggests how senescent cell behavior and matrix mechanics drive pulmonary fibrosis in aged mice

Idiopathic pulmonary fibrosis (IPF) is a progressive and ultimately fatal disease of aging, driven by dysregulated fibroblast activation and accompanied by collagen accumulation in the lung interstitium, resulting in tissue stiffening. While the accumulation of senescent cells has been increasingly implicated in IPF pathogenesis, understanding the reciprocal dynamics of senescent fibroblast levels and evolving tissue mechanics is difficult to achieve with experimental approaches alone. To address this limitation, we developed an agent-based model (ABM) of fibroblast activation in the lung that couples cell behavior to the dynamic mechanical changes accompanying fibrosis. This model was parameterized entirely from experimental data in young mice to enable robust validation and then adapted to fit aged mouse biology for additional validation. Both young and aged models accurately reflected changes in collagen accumulation and stiffness burden of experimental systems. We then incorporated senescent cell behavior into the aged model to investigate how senescent cell burden influences fibrosis progression and how cell-cell interactions drive senescent cell accumulation. These simulations identified a unique role for juxtacrine-mediated contact between non-senescent and senescent fibroblasts in expanding the total senescent cell burden. Our ABM also revealed that the timing of immune-mediated senescent cell clearance critically regulates fibrotic outcomes. Together, this ABM provides useful insights into how the interrelated dynamics of tissue mechanics and senescent fibroblasts drive fibrosis progression.

bioengineering↗

bioRxiv2026

Agent-Based Modeling of Idiopathic Lung Fibrosis and Mechanistic Treatments

Agent-based modeling (ABM) is a computational method for predicting the emergent outcomes of interacting, autonomous individuals in a complex system. Here, ABM is used to simulate interactions between fibroblast and myofibroblast cells during idiopathic pulmonary fibrosis (IPF) in alveolar tissue microenvironments. These microenvironments are derived from histology of a healthy human lung sample and moderate- and severe-IPF lung samples. Fibroblast differentiation, cell migration, and collagen secretion in response to the spatial distribution of the cytokine transforming growth factor-beta are captured in the ABM using NetLogo software. Results are presented from one simulated year without treatment and with mechanisms representing treatment by pirfenidone and pentoxifylline, alone and in combination. A total of 180 in silico experiments are run, analyzed, and compared in a high-throughput workflow. The effects of the initial number of fibroblasts and treatment scenarios on various metrics related to collagen accumulation and collagen invasion into alveolar regions are determined. The ABM and the analysis files are shared to facilitate model reuse. By integrating computational modeling of IPF and therapeutics, this research aims to improve understanding of fibrosis progression and assess the efficacy of novel and existing treatments targeting different mechanisms to inform decision-making for IPF treatment.

systems biology↗

bioRxiv2025

Multimodal analysis identifies pericyte-centered signaling programs altered by sex and brain region in Alzheimer's Disease

Pericytes are critical components of the neurovascular unit (NVU), regulating endothelial cell (EC) stability, blood-brain barrier (BBB) integrity, and neuroimmune signaling. However, their role in Alzheimers Disease (AD), particularly in the context of sex differences and brain region specificity, remains poorly defined. Here, we use single-nucleus RNA sequencing (snRNA-seq) to characterize transcriptional and intercellular signaling changes in pericytes across the middle temporal gyrus (MTG) and dorsolateral prefrontal cortex (DLPFC) of the same AD and non-AD donors, stratified by sex. Using LIANA and Tensor-cell2cell, we identify latent communication programs altered in female AD donors, including a pericyte-EC signaling pattern that activates TGF{beta} via extracellular matrix ligands and is upregulated in the MTG but not the DLPFC. A second communication pattern, downregulated in female AD donors, reveals impaired estrogen pathway signaling through ligand-receptor interactions between pericytes and astrocytes. Supporting this, we observe reduced expression of pericyte-derived neuroligins and increased pericyte-astrocyte separation in a spatial transcriptomic subset. Additionally, we identify a microglia-to-pericyte signaling program conserved across brain regions, enriched for inflammatory pathways including hypoxia and p53, and elevated in both male and female AD donors with regional specificity. This result contrasts with the more sex-and region-specific pericyte signaling programs and suggests parallel mechanisms of NVU disruption between brain regions in AD. Our findings reveal brain region-specific and sex-specific pericyte signaling changes in AD and implicate vascular-, immune-, and synapse-associated pathways in NVU dysfunction. Altogether, the data suggest pericyte-driven communication as a mechanistic contributor to female-biased vulnerability in AD and support the need for sex-aware and region-specific approaches in neurodegeneration research.

bioinformatics↗

bioRxiv2024

Injury-Specific Muscle Regeneration: A Computational Blueprint for Cellular and Cytokine Drivers

Skeletal muscle regeneration is crucial for maintaining muscle health and mobility, making it a key research focus. Common experimental models of muscle injury used to study this process in vivo include cardiotoxin injury (CTX), freeze-induced (FI) injury, and eccentric contraction (EC) injury. While the response to injury varies across these models, these variations are often overlooked in experimental designs. The cellular dynamics throughout the time course of muscle regeneration differ significantly between these injury types, presenting challenges for both experimental investigation and literature analysis. To enhance understanding of how regeneration responses differ across injury types, we extend our previously validated computational model of skeletal muscle regeneration to simulate muscle fiber remodeling during regeneration following CTX, FI, and EC injuries. We further validate our model against multiple literature-derived metrics of regeneration for each injury type. Analysis of model outcomes reveals that recovery from each injury type is sensitive to unique combinations of cells and cytokines acting at different critical time points, exerting the greatest influence on regeneration at 28 days post-injury. Notably, the cytokines responsible for satellite cell (SSC) recruitment, proliferation, and differentiation required for regeneration vary across injury types, driven by biological redundancy and feedback mechanisms. Specifically, for EC injuries, cross-sectional area (CSA) recovery was predominantly associated with hepatocyte growth factor (HGF) and vascular endothelial growth factor A (VEGF-A) during the early stages of regeneration, with SSC dynamics playing a critical role throughout. FI injuries demonstrated a consistent reliance on HGF across all phases, with additional influences from transforming growth factor beta (TGF-{beta}), tumor necrosis factor-alpha (TNF-), monocyte chemoattractant protein-1 (MCP-1), and SSC dynamics in later stages. CTX injuries showed early dependence on TGF-{beta}, with significant contributions from SSC, TNF-, VEGF-A, and fibroblast dynamics over time. Our findings emphasize the importance of considering the molecular and cellular mechanisms relevant to each injury type used in pre-clinical in vivo studies, and motivates the development of therapeutic strategies that are designed for specific injury types to optimize recovery outcomes.

systems biology↗

bioRxiv2024

Multi-Scale Computational Model of Microvascular Remodeling in Idiopathic Pulmonary Fibrosis

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired due to loss of alveolar structures and lung function declines. Here, we integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (ECs) and pericytes, the cells that comprise microvessels. Nintedanib, an FDA-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition (PMT) in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can explain how cell decisions affect tissue changes during disease and in response to treatments.

bioengineering↗

bioRxiv2023

Modeling the roles of cohesotaxis, cell-intercalation, and tissue geometry in collective cell migration of Xenopus mesendoderm

Collectively migrating Xenopus mesendoderm cells are arranged into leader and follower rows with distinct adhesive properties and protrusive behaviors. In vivo, leading row mesendoderm cells extend polarized protrusions and migrate along a fibronectin matrix assembled by blastocoel roof cells. Traction stresses generated at the leading row result in the pulling forward of attached follower row cells. Mesendoderm explants removed from embryos provide an experimentally tractable system for characterizing collective cell movements and behaviors, yet the cellular mechanisms responsible for this mode of migration remain elusive. We introduce an agent-based computational model of migrating mesendoderm in the Cellular-Potts computational framework to investigate the relative contributions of multiple parameters specific to the behaviors of leader and follower row cells. Sensitivity analyses identify cohesotaxis, tissue geometry, and cell intercalation as key parameters affecting the migration velocity of collectively migrating cells. The model predicts that cohesotaxis and tissue geometry in combination promote cooperative migration of leader cells resulting in increased migration velocity of the collective. Radial intercalation of cells towards the substrate is an additional mechanism to increase migratory speed of the tissue. Summary StatementWe present a novel Cellular-Potts model of collective cell migration to investigate the relative roles of cohesotaxis, tissue geometry, and cell intercalation on migration velocity of Xenopus mesendoderm

developmental biology↗

bioRxiv2023

Agent-based model demonstrates the impact of nonlinear, complex interactions between cytokines on muscle regeneration

Muscle regeneration is a complex process due to dynamic and multiscale biochemical and cellular interactions, making it difficult to identify microenvironmental conditions that are beneficial to muscle recovery from injury using experimental approaches alone. To understand the degree to which individual cellular behaviors impact endogenous mechanisms of muscle recovery, we developed an agent-based model (ABM) using the Cellular Potts framework to simulate the dynamic microenvironment of a cross-section of murine skeletal muscle tissue. We referenced more than 100 published studies to define over 100 parameters and rules that dictate the behavior of muscle fibers, satellite stem cells (SSC), fibroblasts, neutrophils, macrophages, microvessels, and lymphatic vessels, as well as their interactions with each other and the microenvironment. We utilized parameter density estimation to calibrate the model to temporal biological datasets describing cross-sectional area (CSA) recovery, SSC, and fibroblast cell counts at multiple time points following injury. The calibrated model was validated by comparison of other model outputs (macrophage, neutrophil, and capillaries counts) to experimental observations. Predictions for eight model perturbations that varied cell or cytokine input conditions were compared to published experimental studies to validate model predictive capabilities. We used Latin hypercube sampling and partial rank correlation coefficient to identify in silico perturbations of cytokine diffusion coefficients and decay rates to enhance CSA recovery. This analysis suggests that combined alterations of specific cytokine decay and diffusion parameters result in greater fibroblast and SSC proliferation compared to individual perturbations with a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. These results enable guided development of therapeutic strategies that similarly alter muscle physiology (i.e. converting ECM-bound cytokines into freely diffusible forms as studied in cancer therapeutics or delivery of exogenous cytokines) during regeneration to enhance muscle recovery after injury.

systems biology↗

bioRxiv2022

Polarized localization of phosphatidylserine in endothelium regulates Kir2.1

In the resistance artery endothelium, we show phosphatidylserine (PS) localizes to a specific subpopulation of myoendothelial junctions (MEJs), signaling microdomains that regulate vasodilation. In silico data has implied PS may compete with PIP2 binding on Kir2.1, a channel involved in vasodilatory signaling. We found 83.33% of Kir2.1-MEJs also contained PS, possibly indicating an interaction where PS regulates Kir2.1. Electrophysiology experiments on HEK cells demonstrate PS blocks PIP2 activation of Kir2.1, and addition of exogenous PS blocks PIP2-mediated Kir2.1 vasodilation in resistance arteries. Using a mouse model lacking canonical MEJs in resistance arteries (Elnfl/fl/Cdh5-Cre), PS localization in endothelium was disrupted and PIP2 activation of Kir2.1 was significantly increased. Taken together, our data suggests PS enrichment to MEJs inhibits PIP2-mediated activation of Kir2.1 to tightly regulate changes in arterial diameter, and demonstrates the intracellular lipid localization within endothelium is an important determinant of vascular function.

physiology↗

bioRxiv2021

Agent-Based Model of Multicellular Spheroid Pattern Formation Driven by Synthetic Cell Adhesion Signaling Circuits

Differential adhesion within cell populations enables the emergence of unique patterns in heterogeneous multicellular systems. This process has been previously explored using synthetically engineered heterogenous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models may be leveraged to more systematically explore the key parameters that drive the emergence of different patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. The model was used to predict how varying initial cell seedings, cadherin induction probabilities, or homotypic adhesion strengths between cells impact spheroid patterning, and unsupervised machine learning techniques were used to map system parameters to unique spheroid patterns. The model was then deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern.

systems biology↗

bioRxiv2021

Vivarium: an interface and engine for integrative multiscale modeling in computational biology

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSThis paper introduces Vivarium - software born of the idea that it should be as easy as possible for computational biologists to define any imaginable mechanistic model, combine it with existing models, and execute them together as an integrated multiscale model. Integrative multiscale modeling confronts the complexity of biology by combining heterogeneous datasets and diverse modeling strategies into unified representations. These integrated models are then run to simulate how the hypothesized mechanisms operate as a whole. But building such models has been a labor-intensive process that requires many contributors, and they are still primarily developed on a case-by-case basis with each project starting anew. New software tools that streamline the integrative modeling effort and facilitate collaboration are therefore essential for future computational biologists. ResultsVivarium is a Pythonic software for building integrative multiscale models. It provides an interface that makes individual models into modules that can be wired together in large composite models, parallelized across multiple CPUs, and run with Vivariums simulation engine. Vivariums utility is demonstrated by building composite models that combine several modeling frameworks: agent based models, ordinary differential equations, stochastic reaction systems, constraint-based models, solid-body physics, and spatial diffusion. This demonstrates just the beginning of what is possible - future efforts can integrate many more types of models and at many more biological scales. AvailabilityThe models, simulation pipelines, and notebooks developed for this paper are available at the vivarium-notebooks repository: https://github.com/vivarium-collective/vivarium-notebooks. Vivarium-core is available at https://github.com/vivarium-collective/vivarium-core, and has been released on PyPI. The Vivarium Collective (https://vivarium-collective.github.io) is a repository of freely-available Vivarium processes and composites, including the processes used in Section 3. Supplementary materials provide with an extensive methodology section, with several code listings that demonstrate the basic interfaces.

systems biology↗

bioRxiv2021

Whole-Colony Modeling of Escherichia coli

Bacterial behavior is the outcome of both molecular mechanisms within each cell and interactions between cells in the context of their environment. Whereas whole-cell models simulate a single cells behavior using molecular mechanisms, agent-based models simulate many agents independently acting and interacting to generate complex collective phenomena. To synthesize agent-based and whole-cell modeling, we used a novel model integration software, called Vivarium, to construct an agent-based model of E. coli colonies where each agent is represented by a current source code snapshot from the E. coli Whole-Cell Modeling Project and interacts with other cells in a shared spatial environment. The result is the first "whole-colony" computational model that mechanistically links expression of individual proteins to a population-level phenotype. Simulated colonies exhibit heterogeneous effects on their environments, heterogeneous gene expression, and media-dependent growth. Extending the cellular model with mechanisms of antibiotic susceptibility and resistance, our model also suggested that variation in the expression level of the betalactamase AmpC, and not of the multi-drug efflux pump AcrAB-TolC, was the key mechanistic driver of survival in the presence of nitrocefin. We see this as a significant step forward in the creation of more comprehensive multi-scale models, and it broadens the range of phenomena that can be modeled in mechanistic terms. Author summaryThis work combines several models of molecular and physical processes that impact the physiology and behavior of the common microbe Escherichia coli into a multiscale model. Colonies comprised of multiple individual cells are simulated as they grow and divide--each with complex internal mechanisms, and with physical interactions and molecular diffusion in their environments. The integrative modeling methodology supports the addition of new submodels. The flexibility of this methodology is demonstrated by adding models of antibiotic resistance and simulating the colonys response to antibiotic treatment.

systems biology↗

bioRxiv2020

Extracellular Matrix Remodeling Associated With Bleomycin-Induced Lung Injury Supports Pericyte-To-Myofibroblast Transition

Of the many origins of pulmonary myofibroblasts, microvascular pericytes are a known source. Prior literature has established the ability of pericytes to transition into myofibroblasts, but provide limited insight into molecular cues that drive this process during lung injury repair and fibrosis. Fibronectin and RGD-binding integrins have long been considered pro-fibrotic factors in myofibroblast biology, and here we test the hypothesis that these known myofibroblast cues coordinate pericyte-to-myofibroblast transitions. Specifically, we hypothesized that v{beta}3 integrin engagement on fibronectin induces pericyte transition into myofibroblastic phenotypes in the murine bleomycin lung injury model. Myosin Heavy Chain 11 (Myh11)-CreERT2 lineage tracing in transgenic mice allows identification of cells of pericyte origin and provides a robust tool for isolating pericytes from tissues for further evaluation. We used this murine model to track and characterize pericyte behaviors during tissue repair. The majority of Myh11 lineage-positive cells are positive for the pericyte surface markers, PDGFR{beta} (55%) and CD146 (69%), and display typical pericyte morphology with spatial apposition to microvascular networks. After intratracheal bleomycin treatment of mice, Myh11 lineage-positive cells showed significantly increased contractile and secretory markers, as well as v integrin expression. According to RNASeq measurements, many disease and tissue-remodeling genesets were upregulated in Myh11 lineage-positive cells in response to bleomycin-induced lung injury. In vitro, blocking v{beta}3 binding through cyclo-RGDfK prevented expression of the myofibroblastic marker SMA relative to controls. In response to RGD-containing provisional matrix proteins present in lung injury, pericytes may alter their integrin profile. This altered matrix-integrin axis contributes to pericyte-to-myofibroblastic transition and represents a possible therapeutic target for limiting the myofibroblastic burden in lung fibrosis. HighlightsO_LIPericyte lineage model enables study of transdifferentiating pericytes C_LIO_LIHigh dimensional flow cytometry used to characterize pulmonary stromal cells C_LIO_LIPulmonary pericytes express matrix-remodeling genes and proteins in lung injury C_LIO_LIMyofibroblasts derived from pericytes have active v{beta}3 integrin C_LIO_LIIn vitro assay reveals necessity of RGD for pericyte transdifferentiation C_LI

cell biology↗

bioRxiv2019

Vascular Expression of Hemoglobin Alpha in Antarctic Icefish Supports Iron Limitation as Novel Evolutionary Driver

Frigid temperatures of the Southern Ocean are known to be an evolutionary driver in Antarctic fish. For example, many fish have reduced red blood cell (RBC) concentration to minimize vascular resistance. Via the oxygen-carrying protein hemoglobin, RBCs contain the vast majority of the bodys iron, which is known to be a limiting nutrient in marine ecosystems. Since lower RBC levels also lead to reduced iron requirements, we hypothesized that low iron availability was an additional evolutionary driver of Antarctic fish speciation. Antarctic Icefish of the family Channichthyidae are known to have extreme alteration of iron metabolism due to loss of two iron-binding proteins, hemoglobin and myoglobin, and no RBCs. Loss of hemoglobin is considered a maladaptive trait allowed by relaxation of predator selection, since extreme adaptations are required to compensate for the loss of oxygen-carrying capacity. However, iron dependency minimization may have driven hemoglobin loss instead of a random evolutionary event. Given the variety of functions that hemoglobin serves in the endothelium, we suspected the protein corresponding to the 3 truncated Hb fragment (Hb-3f) that was not genetically excluded by icefish, may still be expressed as a protein. Using whole mount confocal microscopy, we show that Hb-3f is expressed in the vascular endothelium of icefish retina, suggesting this Hb fragment may still serve an important role in the endothelium. These observations support a novel hypothesis that iron minimization could have influenced icefish speciation with the loss of the iron-binding portion of Hb in Hb-3f, as well as hemoglobin {beta} and myoglobin.

physiology↗

bioRxiv2019

REAVER: Improved Analysis of High-resolution Vascular Network Images Revealed Through Round-robin Rankings of Accuracy and Precision

Alterations in vascular networks, including angiogenesis and capillary regression, play key roles in disease, wound healing, and development. Imaging of microvascular networks can reveal their spatial structures, but effective study of network architecture requires methods to accurately quantify them using a variety of metrics. We present REAVER (Rapid Editable Analysis of Vessel Elements Routine), a freely available open source tool that researchers can use to analyze and quantify high resolution fluorescent images of blood vessel networks, and assess its performance compared to alternative state-of-the-art image analysis software programs. Top performing programs for each metric are identified by assigning a rank based on statistical multiple comparisons of accuracy and precision, modeled as matches in a round-robin style tournament. This comparison method yields a clearly defined and consistent standard for characterizing program performance, avoiding the use of non-standard ad hoc interpretations of multiple comparisons between programs. Using this comparison method and a dataset of manually analyzed images as a ground-truth, we show that REAVER was the top ranked program for both accuracy and precision for all metrics quantified, including vessel length density, vessel area fraction, mean vessel diameter, and branchpoint count. REAVER can be used to quantify differences in blood vessel architectures between study groups, which makes it particularly useful in experiments designed to evaluate the effects of different external perturbations (e.g. drugs or disease states).

bioinformatics↗

bioRxiv2019

Pericyte Bridges in Homeostasis and Hyperglycemia: Reconsidering Pericyte Dropout and Microvascular Structures

Diabetic retinopathy threatens the vision of a third of diabetic patients. Progression of the disease is attributed to the dropout of pericytes, a cell type that enwraps and stabilizes the microvasculature. In tandem with this presumptive pericyte dropout, there is enriched formation of structures assumed to be remnants of collapsed or regressed vessels, previously classified as acellular capillaries, string vessels, and basement membrane bridges. Instead of endothelial cells, we show that pericytes colocalize with basement membrane bridges, and both bridging structures are enriched by cell-specific knockout of KLF4 and reversibly enriched with elevation of Ang-2, PDGF-BB, and blood sugar. Our data suggests that pericyte counts from retinal digests have misclassified pericyte bridges as endothelial structures and have exaggerated the role of pericyte loss in DR progression. In vivo imaging of corneal limbal vessels demonstrates pericyte migration off-vessel, implicating pericyte movement in formation of pericyte bridges and pathogenesis of diabetic retinopathy.

cell biology↗