Biology subjects

Burgess, J.

Publications and source records attributed to Burgess, J..

6 recordsLinked to original sources

bioRxiv2026

CellFluxV2: An Image Generative Foundation Model for Virtual Cell Modeling

Building a virtual cell that simulates cellular behavior in silico is a central goal of computational biology. We introduce CellFluxV2, an image-generative model that predicts how cell morphologies change in response to chemical and genetic perturbations. A core innovation of CellFluxV2 is to learn distribution-level transformations from unperturbed to perturbed cells within the same experimental batch using flow matching, enabling it to disentangle true perturbation effects from confounding batch effects. Incorporating three methodological advances, CellFluxV2 achieves up to a 77% improvement in image fidelity over diffusion- and GAN-based baselines, while maintaining biological fidelity comparable to ground-truth images. Scaling up CellFluxV2, we establish the first scaling laws in image-based virtual cell modeling, demonstrating that performance improves consistently with both dataset size and model capacity. Furthermore, the scaled-up model generalizes well to out-of-distribution perturbations and exhibits two novel capabilities: batch-effect correction and cell-state interpolation. Together, these results position CellFluxV2 as a powerful foundation model advancing the vision of a virtual cell, unlocking novel opportunities for in silico drug screening.

bioinformatics↗

bioRxiv2023

Global organelle profiling reveals subcellular localization and remodeling at proteome scale

Defining the subcellular distribution of all human proteins and its remodeling across cellular states remains a central goal in cell biology. Here, we present a high-resolution strategy to map subcellular organization using organelle immuno-capture coupled to mass spectrometry. We apply this proteomics workflow to a cell-wide collection of membranous and membrane-less compartments. A graph-based representation of our data reveals the subcellular localization of over 7,600 proteins, defines spatial protein networks, and uncovers interconnections between cellular compartments. We demonstrate that our approach can be deployed to comprehensively profile proteome remodeling during cellular perturbation. By characterizing the cellular landscape following hCoV-OC43 viral infection, we discover that many proteins are regulated by changes in their spatial distribution rather than by changes in their total abundance. Our results establish that proteome-wide analysis of subcellular remodeling provides essential insights for the elucidation of cellular responses. Our dataset can be explored at organelles.czbiohub.org.

cell biology↗

bioRxiv2023

Role of RANKL in Alveolar Epithelial Cell Regeneration: Potential Novel Contributor to Lung Tissue Repair

Receptor activator for NF-{kappa}{beta} (RANK) ligand (RANKL) is found in lung tissue and elevated in lung diseases like chronic obstructive pulmonary disease (COPD), cystic fibrosis and silica-induced pulmonary fibrosis. RANKL is a well-known stimulator of bone tissue degradation, which may explain the association between these lung diseases and osteoporosis. However, RANKL is also reported to be involved in epithelial cell regeneration in breast and thymus. We hypothesized that RANKL, which is produced directly in lung tissue, is involved in the regeneration of lung epithelial cells. Therefore, we aimed to clarify the specific role of RANKL in this process. Using an organoid model of lung epithelial development by co-culturing primary EpCAM+ lung epithelial cells with fibroblasts, we found higher numbers of alveolar organoids after soluble RANKL treatment compared to control. Importantly, this effect was similar in human RANKL-treated organoids derived from epithelial cells isolated from lung tissue of COPD patients. The effect of RANKL was abrogated upon addition of osteoprotegerin, the soluble inhibitor of RANKL. We also found that RANKL stimulated phosphorylation of Akt suggesting involvement of its receptor RANK in the signaling pathway. Moreover, in vivo RANKL administration resulted in more type II alveolar epithelial cells in lungs of mice with silica-induced pulmonary fibrosis. In conclusion, we found that RANKL promotes type II alveolar epithelial cell regeneration and may therefore be a novel contributor to lung tissue repair. New and NoteworthyOur study provides compelling evidence demonstrating an as of yet unknown function of receptor activator for NF-{kappa}{beta} ligand (RANKL) in lung tissue regeneration. We found that RANKL plays a role in the regeneration of lung epithelial cells, particularly type II alveolar epithelial cells. This may also have clinical implications as promotion of alveolar epithelial cell regeneration may enhance lung tissue repair, an important target in patients with lung diseases like COPD and fibrosis.

cell biology↗

bioRxiv2022

Learning orientation-invariant representations enables accurate and robust morphologic profiling of cells and organelles

Cell and organelle morphology are driven by diverse genetic and environmental factors and thus accurate quantification of cellular phenotypes is essential to experimental cell biology. Representation learning methods for phenotypic profiling map images to feature vectors that form an embedding space of morphological variation useful for clustering, dimensionality reduction, outlier detection, and supervised learning problems. Morphology properties do not change with orientation, and thus we argue that representation learning methods should encode this orientation invariance. We show that prior methods are sensitive to orientation, which can lead to suboptimal clustering. To address this issue, we develop O2-VAE, an unsupervised learning method that learns robust, orientation-invariant representations. We use O2-VAE to discover novel morphology subgroups in segmented cells and mitochondria, detect outlier cells, and rapidly characterise cellular shape and texture in large datasets, including in a newly generated synthetic benchmark.

bioinformatics↗

bioRxiv2022

Age-associated Differences in the Human Lung Extracellular Matrix

IntroductionExtracellular matrix (ECM) remodelling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study we aimed to identify and localize age-associated ECM differences in human lung using comprehensive transcriptomic, proteomic and immunohistochemical analyses. MethodsOur previously identified age-associated gene expression signature of the lung was re-analysed limiting it to an aging signature based on 270 control patients (37-80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (F <0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from 9 control patients (49-76 years) (FDR<0.05). Extensive immunohistochemical analysis was used to localize the age-associated ECM differences in lung tissues from control patients (9-82 years). ResultsComparative analysis of transcriptomic and proteomic data identified 7 ECM proteins with higher expression with age at both gene and protein level: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4 and LUM. With immunohistochemistry we demonstrated higher protein expression with age for COL6A2 in whole tissue, parenchyma, airway wall and blood vessel, for COL14A1 in bronchial epithelium and blood vessel, and for FBLN2 and COL1A1 in lung parenchyma. ConclusionOur study revealed that higher age is associated with lung ECM remodelling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility for developing chronic lung diseases. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSsummarise the state of scientific knowledge on this subject before you did your study and why this study needed to be done. In animal models, it has been demonstrated that aging alters the composition of the lung ECM, with more deposition of collagen and degradation of elastin. Similar ECM differences have been observed in age-associated chronic lung diseases, including COPD; moreover, we observed in lung tissue that several ECM genes associate differently with age in COPD patients compared to non-COPD controls(1). Detailed knowledge on age-associated changes in specific ECM proteins as well as regional differences within the lung is lacking. What this study addssummarise what we now know as a result of this study that we did not know before. We identified 7 age-associated ECM proteins i.e. COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4 and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for 3 of these ECM proteins in specific compartments of the lung, with the most notable differences in the blood vessels and parenchyma. How this study might affect research, practice, or policysummarise the implications of this study. The identification of age-associated differences in specific human lung ECM proteins lays a new foundation for the investigation of ECM differences in age-associated chronic lung diseases. Additionally, examining the function of these age-associated ECM proteins and their cellular interactions in lung injury and repair responses may provide novel insight in mechanisms underlying chronic lung diseases.

molecular biology↗

bioRxiv2020

Osteoprotegerin is elevated in pulmonary fibrosis and associates with IPF progression

Osteoprotegerin (OPG), a decoy receptor for receptor activator of NF-kB ligand (RANKL), is used as a biomarker for assessing severity of liver fibrosis. However, its expression and role in pulmonary fibrosis are unknown. We hypothesized that OPG also has a role in pulmonary fibrosis. Human and mouse control and fibrotic lung tissue were used to examine OPG expression, and mouse precision-cut lung slices to study OPG regulation in pulmonary fibrosis. Serum from idiopathic pulmonary fibrosis (IPF) patients and controls was analysed to investigate whether OPG levels correlate with disease status as measured by lung function. OPG-protein levels were significantly higher in mouse and human fibrotic lung tissue compared to control. OPG-mRNA and protein production were induced in mouse precision-cut-lung slices upon TGF{beta} stimulation and could be inhibited with galunisertib, a TGF{beta} receptor kinase inhibitor. OPG-protein levels in fibrotic mouse lung tissue correlated with degree of fibrosis. Isolated lung fibroblasts from IPF patients had higher OPG-protein levels than control fibroblasts. Serum OPG levels in IPF patients, at first presentation, negatively correlated with diffusing capacity to carbon monoxide. Finally, serum OPG levels higher than 1234 pg/ml at first presentation were associated with progression of disease in IPF patients. In conclusion, OPG is produced in lung tissue, associates with fibrosis, and may be a potential prognostic biomarker for IPF disease progression. Validation in a larger cohort is warranted to further explore the role of OPG in pulmonary fibrosis and its potential for assessing the prognosis of fibrotic lung disease in individual patients. Take home messageOsteoprotegerin is present in fibrotic lung tissue and high serum levels correlate with low lung function and IPF disease progression in this small study, indicating osteoprotegerin may have value as a biomarker to predict IPF progression

pathology↗