Biology subjects

Stallaert, W.

Publications and source records attributed to Stallaert, W..

12 recordsLinked to original sources

bioRxiv2026

Overcoming segmentation bottlenecks in brain tissue for spatial proteomic inference at population scale

In spatial proteomics across large cohorts, downstream estimates from tens of thousands of images depend on accurate cell segmentation. Yet pretrained segmentation models struggle with morphologically complex cell bodies in human brain tissue, and how domain adaptation affects downstream discovery remains unclear. Here, we introduce SPInfer, a workflow for spatial proteomic inference developed using 5,832 manually annotated cell bodies from 120 immunofluorescence images of the human prefrontal cortex. After benchmarking eight segmentation methods spanning classical, convolutional, and foundation models, we adapted Cellpose-SAM, raising cell segmentation F1 from 0.37 to 0.84 and recovering cell compositions concordant with matched single-nucleus RNA-seq and spatial transcriptomics. Across 14,765 images from 69 postmortem donors, identical Alzheimer's disease pathology models found no significant associations after false discovery rate correction using zero-shot masks, versus four using fine-tuned masks; three linked higher OLIG2-positive fractions to greater neurofibrillary tangle and plaque burden. Using the fine-tuned masks, a graph attention network over nuclear neighborhoods classified four cell types without marker information, and differential expression analysis linked cell morphology to gene expression. This provides a pipeline for fine-tuning foundation models to segment complex tissues, enabling biological discovery in spatial proteomics at the population scale.

bioinformatics↗

bioRxiv2026

Distinct p21 dynamics drive alternative routes to whole-genome duplication through a common CDK4/6-dependent polyploid G0 state

Whole-genome duplication (WGD) fuels tumor evolution and therapy resistance, yet the molecular mechanisms governing the switch from the canonical mitotic cell cycle to the endoreplication cycle remain unclear. Here, we combine single-cell proteomics, manifold learning, and live-cell imaging to map the intersection of the mitotic and endoreplication cycles in breast cancer cells exposed to genotoxic agents. We identify two distinct routes to WGD driven by distinct p21 dynamics. High p21 induction induces G2 exit and endocycling, whereas insufficient p21 permits mitotic entry followed by slippage and endomitosis. This therapy-induced switch acts as a facultative stress response, generating drug-resistant polyploid populations that propagate genomic instability through replication stress and the generation of replication-competent micronuclei. Both paths to WGD converge on a common polyploid G0 state dependent on cyclin D1:CDK4/6 activity to complete the transition to the endoreplication cycle, revealing a shared vulnerability. Sequential treatment with genotoxic agents followed by CDK4/6 inhibitors preserves the cytotoxic efficacy of DNA-damaging drugs while simultaneously blocking entry into the endoreplication cycle and WGD-driven evolutionary rescue. These findings reveal the molecular rules governing the switch from the mitotic to endoreplication cycle and highlight the potential of WGD-blocking drugs as adjuvant therapies to inhibit drug resistance and suppress tumor evolution.

cell biology↗

bioRxiv2025

Cell cycle-coupled transcriptional network orchestrates human B cell fate bifurcation

Bifurcation of activated human B cells into plasmablast (PB) and germinal center precursor (preGC) fates underlies protective and autoimmune antibody responses, yet gene regulatory networks (GRNs) governing the alternative trajectories remain poorly defined. Using temporal single-cell multiomics, we assembled state-specific human B cell GRNs spanning four scales: transcription factor (TF)-to-fate, TF-to-gene, cis-regulatory element (CRE)-to-gene and nucleotide-to-CRE. Applying the framework to in vitro differentiated and tonsil B cells revealed concordant regulatory architectures and impacts of in silico TF perturbations. CRISPR perturbations validated many TF-to-fate and TF-to-gene predictions and revealed a mutually repressive BATF-IRF4/PRDM1 network module. The GRNs were used to predict and interpret effects of autoimmune disease variants, uncovering partitioning of disease risk at distinct TF motifs and B cell states. Predicted functional variants were independently supported by chromatin and expression QTLs and reporter assays. A web application enables exploration of B cell regulatory determinants of vaccine responses and autoimmune diseases.

immunology↗

bioRxiv2025

Role of the NuRD complex and altered proteostasis in cancer cell quiescence

Cytotoxic chemotherapy remains the primary treatment for ovarian cancer (OvCa). Development of chemoresistance typically results in patient death within two years. As such, understanding chemoresistance is critical. One underexplored mechanism of chemotherapy resistance is quiescence. Quiescent cells, which have reversibly exited the cell cycle, are refractory to most chemotherapies which primarily target rapidly proliferating cells. Here, we report that CHD4 and MBD3, components of the nucleosome remodeling and deacetylase (NuRD) complex, are downregulated in quiescent OvCa cells (qOvCa). Indicating a direct role for NuRD complex downregulation in the induction of quiescence, either CHD4 or MBD3 knockdown or histone deacetylase inhibitors (HDACi), such as vorinostat, induce quiescence in OvCa cells. RNA-Seq analysis of HDACi-treated cells confirmed expression changes consistent with induction of quiescence. We also find that both primary qOvCa and vorinostat-induced qOvCa demonstrate altered proteostasis, including increased proteasome activity and autophagy, and combination therapy of HDACi and proteasome inhibitors or autophagy inhibitors demonstrated profound synergistic death of OvCa cells. Finally, we overlapped RNA-Seq signatures from quiescent ovarian cancer cells with genes essential for quiescence in yeast to identify a "quiescent cell core signature." This core quiescent cell signature appeared to be conserved across multiple cancer types, suggesting new therapeutic targets.

cancer biology↗

bioRxiv2024

αKG-mediated carnitine synthesis promotes homologous recombination via histone acetylation

Homologous recombination (HR) deficiency enhances sensitivity to DNA damaging agents commonly used to treat cancer. In HR-proficient cancers, metabolic mechanisms driving response or resistance to DNA damaging agents remain unclear. Here we identified that depletion of alpha-ketoglutarate (KG) sensitizes HR-proficient cells to DNA damaging agents by metabolic regulation of histone acetylation. KG is required for the activity of KG-dependent dioxygenases (KGDDs), and prior work has shown that changes in KGDD affect demethylases. Using a targeted CRISPR knockout library consisting of 64 KGDDs, we discovered that Trimethyllysine Hydroxylase Epsilon (TMLHE), the first and rate-limiting enzyme in de novo carnitine synthesis, is necessary for proliferation of HR-proficient cells in the presence of DNA damaging agents. Unexpectedly, KG-mediated TMLHE-dependent carnitine synthesis was required for histone acetylation, while histone methylation was affected but dispensable. The increase in histone acetylation via KG-dependent carnitine synthesis promoted HR-mediated DNA repair through site- and substrate-specific histone acetylation. These data demonstrate for the first time that HR-proficiency is mediated through KG directly influencing histone acetylation via carnitine synthesis and provide a metabolic avenue to induce HR-deficiency and sensitivity to DNA damaging agents.

cancer biology↗

bioRxiv2023

Paracrine effects of the senescence-associated secretory phenotype decrease cancer cell adhesion

Cellular senescence, characterized by a stable cell cycle arrest, is a well-documented consequence of several widely used chemotherapeutics that has context-dependent roles in cancer. Although senescent cells are non-proliferative, they remain biologically active and secrete a complex and diverse array of factors collectively known as the se-nescence-associated secretome (SAS), which exerts pro-tumorigenic effects. Here, we aimed to mechanistically investigate how the SAS contributes to metastatic dissemination of high grade serous ovarian cancer (HGSOC) using standard-of-care cisplatin as a se-nescence inducer. Our findings demonstrate that the cisplatin-induced SAS enhances the dissemination of HGSOC in vivo without affecting cell proliferation or viability. We found that the SAS facilitates cell detachment, an effect that is mediated by a metabolic com-ponent. Using a metabolically focused CRISPR knockout screen, we identified complex I as the key driver of SAS-mediated cell detachment in bystander cells and validated that inhibition of complex I activity decreases HGSOC dissemination in vivo. Mechanistically, this effect was driven by SAS-mediated inhibition of an NAD+-SIRT-SREBP axis, leading to decreased plasma membrane cholesterol that increased cell detachment. Excitingly, we found that fructose is the key SAS component upstream of the NAD+-SIRT-SREBP-cholesterol axis mediating increased detachment of bystander cells, and a high fructose diet increases HGSOC dissemination in vivo. These findings reveal that the cisplatin-induced SAS reprograms the metabolic microenvironment in HGSOC, driving cancer cell detachment and promoting metastatic dissemination in a paracrine fashion. They also point to a previously unrecognized pro-tumorigenic effect of the SAS that may contribute to the high recurrence rate of HGSOC patients.

cancer biology↗

bioRxiv2023

Feature selection for preserving biological trajectories in single-cell data

Single-cell technologies can readily measure the expression of thousands of molecular features from individual cells undergoing dynamic biological processes, such as cellular differentiation, immune response, and disease progression. While examining cells along a computationally ordered pseudotime offers the potential to study how subtle changes in gene or protein expression impact cell fate decision-making, identifying characteristic features that drive continuous biological processes remains difficult to detect from unenriched and noisy single-cell data. Given that all profiled sources of feature variation contribute to the cell-to-cell distances that define an inferred cellular trajectory, including confounding sources of biological variation (e.g. cell cycle or metabolic state) or noisy and irrelevant features (e.g. measurements with low signal-to-noise ratio) can mask the underlying trajectory of study and hinder inference. Here, we present DELVE (dynamic selection of locally covarying features), an unsupervised feature selection method for identifying a representative subset of dynamically-expressed molecular features that recapitulates cellular trajectories. In contrast to previous work, DELVE uses a bottom-up approach to mitigate the effect of unwanted sources of variation confounding inference, and instead models cell states from dynamic feature modules that constitute core regulatory complexes. Using simulations, single-cell RNA sequencing data, and iterative immunofluorescence imaging data in the context of the cell cycle and cellular differentiation, we demonstrate that DELVE selects features that more accurately characterize cell populations and improve the recovery of cell type transitions. This feature selection framework provides an alternative approach for improving trajectory inference and uncovering co-variation amongst features along a biological trajectory. DELVE is implemented as an open-source python package and is publicly available at: https://github.com/jranek/delve.

bioinformatics↗

bioRxiv2022

The molecular architecture of cell cycle arrest

The cellular decision governing the transition between proliferative and arrested states is crucial to the development and function of every tissue. While the molecular mechanisms that regulate the proliferative cell cycle are well established, we know comparatively little about what happens to cells as they diverge into cell cycle arrest. We performed hyperplexed imaging of 49 cell cycle effectors to obtain a map of the molecular architecture that governs cell cycle exit and progression into reversible ("quiescent") and irreversible ("senescent") arrest states. Using this map, we found multiple points of divergence from the proliferative cell cycle; identified stress-specific states of arrest; and resolved the molecular mechanisms governing these fate decisions, which we validated by single-cell, time-lapse imaging. Notably, we found that cells can exit into senescence from either G1 or G2; however, both subpopulations converge onto a single senescent state with a G1-like molecular signature. Cells can escape from this "irreversible" arrest state through the upregulation of G1 cyclins. This comprehensive map provides a first glimpse of the overall organization of cell proliferation and arrest.

cell biology↗

bioRxiv2021

Cyclin F drives proliferation through SCF-dependent degradation of the retinoblastoma-like tumor suppressor p130/RBL2

Cell cycle gene expression programs fuel proliferation and are dysregulated in many cancers. The retinoblastoma-family proteins, RB, p130/RBL2 and p107/RBL1, coordinately repress cell cycle gene expression, inhibiting proliferation and suppressing tumorigenesis. Ubiquitin-dependent protein degradation is essential to cell cycle control, and numerous proliferative regulators, tumor suppressors, and oncoproteins are ubiquitinated. However, little is known about the role of ubiquitin signaling in controlling RB-family proteins. A systems genetics analysis of several hundred CRISPR/Cas9 loss-of-function screens suggested the potential regulation of the RB-network by cyclin F, a substrate recognition receptor for the SCF family of E3 ligases. We demonstrate that RBL2/p130 is a direct substrate of SCFcyclin F. We map a cyclin F regulatory site to a flexible linker in the p130 pocket domain, and show that this site mediates binding, stability, and ubiquitination. Expression of a non-degradable p130 represses cell cycle gene expression and strongly reduces proliferation. These data suggest that SCFcyclin F plays a key role in the CDK-RB network and raises the possibility that aberrant p130 degradation could dysregulate the cell cycle in human cancers.

cell biology↗

bioRxiv2021

The structure of the human cell cycle

The human cell cycle is conventionally depicted as a five-phase model consisting of four proliferative phases (G1, S, G2, M) and a single state of arrest (G0). However, recent studies show that individual cells can take different paths through the cell cycle and exit into distinct arrest states, thus necessitating an update to the canonical model. We combined time lapse microscopy, highly multiplexed single cell imaging and manifold learning to determine the underlying "structure" of the human cell cycle under multiple growth and arrest conditions. By visualizing the cell cycle as a complete biological process, we identified multiple points of divergence from the proliferative cell cycle into distinct states of arrest, revealing multiple mechanisms of cell cycle exit and re-entry and the molecular routes to senescence, endoreduplication and polyploidy. These findings enable the visualization and comparison of alternative cell cycles in development and disease. One-sentence summaryA systems-level view of single-cell states reveals the underlying architecture of the human cell cycle

cell biology↗

bioRxiv2018

Interdependence of EGFR with PTPs on juxtaposed membranes generates a growth factor sensing and responding network

The proto-oncogenic epidermal growth factor receptor (EGFR) is a tyrosine kinase whose sensitivity to growth factors (GFs) and signal duration determines cellular behavior. We resolve how EGFRs response to epidermal growth factor (EGF) originates from dynamically established recursive interactions with spatially organized protein tyrosine phosphatases (PTPs). Opposed genetic PTP perturbations enabled identification of receptor-like PTPRG/J at the plasma membrane (PM) and endoplasmic reticulum (ER) associated PTPN2 as the major EGFR dephosphorylating activities. Imaging spatial-temporal PTP reactivity then revealed that vesicular trafficking establishes a spatially-distributed negative feedback with PTPN2 that determines signal duration, whereas single cell dose-response analysis uncovered a ROS-mediated toggle switch between autocatalytically activated monomeric EGFR and the tumor suppressor PTPRG that governs EGFRs sensitivity to EGF. Vesicular recycling of monomeric EGFR unifies the interactions with these PTPs on juxtaposed membranes, dynamically generating a network architecture that can sense and respond to time varying growth factor signals.

systems biology↗

bioRxiv2017

Contact inhibitory Eph signalling decouples EGFR activity from vesicular recycling to generate contextual plasticity

The ability of cells to adapt their behavior to growth factors in relation to their environment is an essential aspect of tissue development and homeostasis. Here we show that Eph receptor signaling from cell-cell contacts changes the cellular response to EGFR activation by altering its vesicular trafficking. Eph receptor activation traps EGFR in Rab5-positive early endosomes through an inhibition of Akt-dependent vesicular recycling. By altering the spatial distribution of EGFR activity during EGF stimulation, Eph receptor activation selectively suppresses migratory Akt signaling from the plasma membrane, while preserving proliferative ERK signaling from endosomes. We also show that soluble extracellular signals engaging the G-protein coupled receptor Kiss1 similarly suppress vesicular recycling to alter EGFR signaling. The cellular environment can thus modulate EGFR vesicular trafficking dynamics to generate context-dependent responses to EGF stimulation.\n\nSummaryEph receptor activation generates context-dependent cellular responses to EGFR activation by altering its vesicular trafficking dynamics.

cell biology↗