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Results for “Single-cell lineage tracing”

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PubMed2026

Bayesian inference of lineage trees by joint analysis of single-cell multimodal lineage-tracing data with BiLinT.

The advent of single-cell lineage-tracing technologies has enabled the simultaneous profiling of gene expression and lineage barcodes. However, accurate, high-resolution reconstruction of cell lineage trees remains challenging because most existing approaches treat these modalities separately and therefore fail to fully exploit their complementary information. Here we present BiLinT, a Bayesian framework that jointly models multimodal single-cell lineage-tracing data for lineage tree reconstruction. BiLinT integrates barcode evolution (a continuous-time Markov chain) with gene expression dynamics (an Ornstein-Uhlenbeck process) within a unified probabilistic model. Across synthetic and real data sets, BiLinT provides accurate lineage-tree reconstruction and reveals differentiation-associated clonal structure and developmental fate biases.

Journal Article↗

PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗

PubMed2026

Generation and validation of a Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of disease-associated smooth muscle cell states.

BACKGROUND: Phenotypic modulation of vascular smooth muscle cells (VSMCs) is a hallmark of vascular remodeling and cardiovascular disease. Recent lineage-tracing and single-cell transcriptomic studies have identified secreted phosphoprotein 1 (SPP1) as a prominent marker associated with disease-associated VSMC states, particularly those linked to fibrotic remodeling and vascular calcification. However, the cellular origins and fate of SPP1-associated VSMC populations remain incompletely understood. METHODS AND RESULTS: We generated a novel Spp1-rSTOPr-Cre (Spp1Cre) knock-in mouse line in which Cre recombinase is expressed from the endogenous Spp1 locus following Dre-mediated excision of a rox-flanked transcriptional STOP cassette. Correct targeting of the knock-in allele was validated by internal, 5' junction, 3' junction, and long-range PCR analyses, as well as Sanger sequencing. To establish an intersectional lineage-tracing strategy, Spp1Cre mice were crossed with Myh11DreERT2 and Rosa26-RSR-LSL-tdTomato-LSL-eGFP reporter mice, enabling permanent labeling of VSMC-derived populations following activation of the endogenous Spp1 locus. Under physiological conditions, eGFP-positive cells were detected at low frequency within the vascular wall and were predominantly negative for the contractile markers ACTA2 and MYH11. As a proof-of-principle application, eGFP-positive cells markedly expanded within atherosclerotic lesions induced by AAV-PCSK9D377Y and high-fat diet feeding. These lineage-traced cells remained largely ACTA2- and MYH11-negative, consistent with a modulated phenotype. Notably, only a minority of eGFP-positive cells expressed SPP1 or fibronectin at the time of analysis, demonstrating the utility of permanent lineage tracing for tracking cells with a history of endogenous Spp1 activation during vascular remodeling. CONCLUSION: We report the generation and validation of a novel Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of VSMC-derived populations that have activated the endogenous Spp1 locus. This genetic resource provides a valuable platform for investigating the origin, fate, and phenotypic evolution of Spp1-associated VSMC populations during vascular remodeling and cardiovascular disease.

Animals↗

PubMed2025

Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.

The human cerebral cortex is specialized into regions, but little is known about how human cellular lineages shape cortical regional variation and neuronal cell-type distribution during development. Here, we map single-cell lineages of human cortical regions and neuronal subtypes using >1,000 somatic single-nucleotide variants (sSNVs) identified from deep bulk whole-genome sequencing and analyzed over 25 regions and >72,000 single cells. In the fronto-parietal cortex, sSNVs are rarely restricted, marking neuron-generating clones that disperse into neighboring regions. In contrast, the primary visual cortex harbors 30%-70% more sSNVs than the neighboring secondary visual cortex. Clones at this border exhibit more restricted dispersion, suggesting late developmental lineage segregation. Single-nucleus sSNV and whole-transcriptome analysis reveal glutamatergic neuron clones with modest regional restrictions that share low-mosaic sSNVs with some GABAergic neurons, suggesting a recent dorsal cortical progenitor. Our analysis reveals human-specific cortical lineage patterns, regional differences in clonal patterns, and late divergence of some glutamatergic/GABAergic lineages.

Humans↗

PubMed2026

Atherosclerotic plaque fibroblasts derive from adventitial and medial Pdgfra-lineage-positive cells and predominantly maintain fibroblast identity.

AIMS: Fibroblasts are mesenchymal cells in the healthy vascular adventitia. In atherosclerosis, single-cell sequencing datasets suggest fibroblasts are abundant in plaques. However, their identity, origin, and fate during plaque progression remain unclear, which we aim to unravel here. APPROACH AND RESULTS: To robustly define fibroblast identity, origin, and fate, we employed meta-analyses of 54 single-cell RNA sequencing libraries, including murine smooth muscle cell (Myh11) and endothelial cell (EC) (Cdh5) lineage reporter mice with and without atherosclerosis; human control and atherosclerotic arteries; and murine adventitia and atherosclerotic plaques processed separately from low-density lipoprotein (LDL) receptor knockout (Ldlr-/-) mice. These meta-analyses showed that murine and human plaque fibroblast identity was robustly defined by Pdgfra, Pi16, Cygb, and Serpinf1 mRNA. Ninety-five percent of plaque fibroblasts do not derive from the Myh11 lineage, while no Cdh5-lineage-positive cells were present in the fibroblast cluster. We identified five murine arterial fibroblast subsets in atherosclerotic murine aorta: progenitor fibroblasts, matrix fibroblasts, inflammatory fibroblasts, an EC-like fibroblast subset, detected in both adventitia and plaques, and Col5a3+ fibroblasts, unique to the adventitia. We next studied fibroblast identity, origin, and fate using pseudotime analysis and Pdgfra-CreERT2/tdTomato lineage reporter mice (Pdgfra Lin+). Healthy Pdgfra Lin+ reporter mice showed predominant adventitial tdTomato expression, and infrequent medial and intimal Pdgfra Lin+ cells co-expressing MYH11 and PECAM1, respectively. The Pdgfra Lin+ plaque area increased with diet duration. Pdgfra Lin+ cells largely maintain fibroblast identity in the plaque, while <10% co-express SMC markers (MYH11, SM22α), or contribute to ACTA2+ cap cells. ECs gaining mesenchymal markers are transcriptionally distinct from Cdh5-lineage-negative fibroblasts gaining EC markers. Plaque-resident EC-like fibroblasts displayed a mesenchymal-to-endothelial transition transcriptome, which was induced in human primary fibroblasts in vitro by starvation, and dampened or reversed by IL1B, TGFB1, TGFB3, and oxidized LDL. Cross-species integration showed that all murine plaque fibroblasts were conserved in human atherosclerosis, with one additional subset partially resembling murine subsets, and three human-specific subsets. Importantly, human fibroblast subsets differentially correlated to human plaque traits, with EC-like fibroblasts correlating to plaque instability. CONCLUSION: Our results indicate that 95% of plaque-residing fibroblasts are Myh11 Lin- Plaque fibroblasts have a dual origin, predominantly adventitial Pdgfra Lin+ progenitor fibroblasts, with a minor contribution from medial Pdgfra Lin+  Myh11+ SMCs. Most plaque fibroblasts maintain fibroblast identity. Murine plaque fibroblast subsets were conserved in human atherosclerosis. EC-like fibroblasts are linked to human plaque instability. Intervening in progenitor-to-specific fibroblast transitions could present a new avenue to promote plaque stability in atherosclerosis.

Atherosclerosis↗

PubMed2026

Hypoxia-activated scleraxis a mediates epicardial progenitor differentiation into a unique cardiac perivascular cell type.

The epicardium provides progenitor cells and paracrine signals essential for heart development and regeneration, yet the mechanisms regulating epicardial cell fate remain poorly understood. Here, we identify the transcription factor Scleraxis a (scxa) as a key regulator of epicardial progenitor differentiation in zebrafish. Single-cell transcriptomics, genetic lineage tracing, and cardiac injury models reveal transient scxa expression in activated epicardial progenitor cells (aEPCs) during developmental coronary angiogenesis and heart regeneration. scxa+ epicardial cells predominantly differentiate into a previously uncharacterized col18a1a+ perivascular population, termed epicardial-derived perivascular mesenchymal cells (Epi-PMCs), which is distinct from pericytes, vascular smooth muscle cells, and mammalian adventitial fibroblasts. Epi-PMCs closely associate with coronary vessels and may contribute to vascular stabilization and remodeling, potentially through collagen XVIII. Loss of scxa increases coronary vessel density. Hypoxia and Hif signaling induce scxa expression, identifying a hypoxia-responsive mechanism that promotes epicardial differentiation toward a vascular-supportive fate during heart development and regeneration.

Animals↗

PubMed2026

Athero-oncology: Vascular smooth muscle cell tumor-like transformation in atherosclerosis and therapeutic opportunities.

Atherosclerosis (AS) is the main pathological basis of cardiovascular diseases, and its pathogenesis and treatment strategies remain major challenges. Recent advances in single-cell RNA sequencing and lineage tracing have revealed that vascular smooth muscle cells (VSMCs) are not merely passive structural components of atherosclerotic plaques, but highly plastic participants that undergo clonal expansion, phenotypic modulation, and transdifferentiation into functionally diverse cell states. These findings have prompted the emergence of an "athero-oncology" framework, which explores selected tumor-like cellular programs in VSMCs during AS without equating atherosclerosis with cancer. In this review, we summarize the evidence supporting VSMC-derived clonal expansion and phenotypic diversification in atherosclerotic lesions and discuss key mechanisms involved in this process, including proliferative expansion and survival programs, metabolic reprogramming, epigenetic regulation, DNA damage and genomic stress, VSMC senescence, pathological angiogenesis, and remodeling of the inflammatory and immune microenvironment. We further highlight shared signaling pathways between VSMC-driven plaque remodeling and tumor biology, while emphasizing fundamental differences between AS and malignant disease in growth limitation, mutational burden, metastatic potential, and clinical behavior. Finally, we discuss oncology-inspired therapeutic opportunities and boundaries, including pathway-level targeting of proliferative, metabolic, epigenetic, and inflammatory programs, as well as the risks of directly repurposing anticancer therapies for chronic vascular disease. This framework may provide new insights into vascular biology and therapeutic development.

atherosclerosis↗

PubMed2026

The role of stem cells in pituitary tumour formation.

Pituitary tumours are intracranial neoplasms that pose significant clinical challenges due to their potential for recurrence, therapeutic resistance and resultant endocrine dysfunction and mass effects. In the normal anterior pituitary, resident pituitary stem cells (PSCs) contribute to tissue homeostasis and cellular turnover. The extent to which PSCs contribute to tumourigenesis is not known, but an increasing number of studies have been aiming to address this. In this review, we summarise current evidence implicating PSCs and tumour stem-like populations in pituitary tumour biology, including potential roles in tumour initiation, maintenance and progression. We outline practical criteria for defining tumour stem cells and evaluate findings from functional studies of human tumours, emerging single-cell and spatial transcriptomic datasets and murine lineage-tracing models. We also provide a curated overview of published single-cell RNA sequencing studies of pituitary tumours, highlighting reported stem/progenitor populations and transcriptional signatures across tumour subtypes and propose a framework for future genomic analyses. Finally, we discuss the translational implications of these findings, including the potential for targeting stem-like populations and their associated signalling pathways.

Humans↗

PubMed2026

Stress-driven strategic games in cancer.

Tumor cells face chronic genotoxic, metabolic, hypoxic, and immune stress that shapes their evolution. While stress-response molecular pathways are well characterized, cancer biology lacks a predictive framework for how cells select among alternative adaptive strategies and how these selections interact to produce tumor-level behavior. We propose that evolutionary game theory, previously applied to cooperation in cancer, should be extended to position stress adaptation itself as the organizing principle of tumor evolution. In this framework, stress-adaptive strategies constitute frequency-dependent games whose payoffs depend on population composition. We introduce a three-level distinction between cell states (transcriptional snapshots), game states (local configurations of stress and neighbor composition that define the active payoff structure), and cell strategies (conditional behavioral policies mapping game states to fitness-relevant outputs). This perspective explains the maintenance of intratumor heterogeneity through frequency-dependent selection, the reversibility of resistance through bet-hedging dynamics, and therapy resistance as an equilibrium outcome rather than genetic inevitability. Integrating insights from single-cell genomics, spatial profiling, and lineage tracing, we outline testable predictions and experimental approaches for measuring payoff structures. Therapeutically, the framework suggests exploiting adaptive trade-offs, restricting phenotypic plasticity, and reshaping competitive landscapes. Re-framing cancer as an evolving game of stress adaptation provides a unifying structure for predictive oncology.

Animals↗

PubMed2024

Synthetic DNA barcodes identify singlets in scRNA-seq datasets and evaluate doublet algorithms.

Single-cell RNA sequencing (scRNA-seq) datasets contain true single cells, or singlets, in addition to cells that coalesce during the protocol, or doublets. Identifying singlets with high fidelity in scRNA-seq is necessary to avoid false negative and false positive discoveries. Although several methodologies have been proposed, they are typically tested on highly heterogeneous datasets and lack a priori knowledge of true singlets. Here, we leveraged datasets with synthetically introduced DNA barcodes for a hitherto unexplored application: to extract ground-truth singlets. We demonstrated the feasibility of our framework, "singletCode," to evaluate existing doublet detection methods across a range of contexts. We also leveraged our ground-truth singlets to train a proof-of-concept machine learning classifier, which outperformed other doublet detection algorithms. Our integrative framework can identify ground-truth singlets and enable robust doublet detection in non-barcoded datasets.

Algorithms↗

PubMed2024

Whole-genome sequences reveal zygotic composition in chimeric twins.

While most dizygotic twins have a dichorionic placenta, rare cases of dizygotic twins with a monochorionic placenta have been reported. The monochorionic placenta in dizygotic twins allows in utero exchange of embryonic cells, resulting in chimerism in the twins. In practice, this chimerism is incidentally identified in mixed ABO blood types or in the presence of cells with a discordant sex chromosome. Here, we applied whole-genome sequencing to one triplet and one twin family to precisely understand their zygotic compositions, using millions of genomic variants as barcodes of zygotic origins. Peripheral blood showed asymmetrical contributions from two sister zygotes, where one of the zygotes was the major clone in both twins. Single-cell RNA sequencing of peripheral blood tissues further showed differential contributions from the two sister zygotes across blood cell types. In contrast, buccal tissues were pure in genetic composition, suggesting that in utero cellular exchanges were confined to the blood tissues. Our study illustrates the cellular history of twinning during human development, which is critical for managing the health of chimeric individuals in the era of genomic medicine.

Humans↗

PubMed2026

Beta cell-derived cholecystokinin drives obesity-associated pancreatic adenocarcinoma development.

Pancreatic endocrine-exocrine crosstalk plays a key role in normal physiology and disease and can be altered by host metabolic states, such as obesity. Classically, endocrine islet beta (β) cell secretion of insulin is thought to promote the development of obesity-associated pancreatic adenocarcinoma (PDAC), an exocrine cell-derived tumor. Here, we show that β cell expression of the peptide hormone cholecystokinin (CCK) is necessary and sufficient for obesity-associated PDAC progression in mice and that CCK expression - rather than insulin - correlates strongly with enhanced tumorigenesis. Single-cell RNA-sequencing, in silico latent-space archetypal and trajectory analysis, and experimental lineage tracing in vivo reveal that obesity induces the expansion of postnatal immature β cells, which adapt to express CCK via stress-responsive JNK/cJun signaling. Finally, obesity perturbs CCK-dependent peri-islet exocrine cell transcriptional states and enhances islet-proximal tumor formation. These results define endocrine-exocrine CCK signaling as a bona fide driver of obesity-associated PDAC development and uncover avenues to target the endocrine pancreas to subvert exocrine tumorigenesis.

Animals↗

PubMed2025

Evolutionary fingerprints of epithelial-to-mesenchymal transition.

Mesenchymal plasticity has been extensively described in advanced epithelial cancers; however, its functional role in malignant progression is controversial1-5. The function of epithelial-to-mesenchymal transition (EMT) and cell plasticity in tumour heterogeneity and clonal evolution is poorly understood. Here we clarify the contribution of EMT to malignant progression in pancreatic cancer. We used somatic mosaic genome engineering technologies to trace and ablate malignant mesenchymal lineages along the EMT continuum. The experimental evidence clarifies the essential contribution of mesenchymal lineages to pancreatic cancer evolution. Spatial genomic analysis, single-cell transcriptomic and epigenomic profiling of EMT clarifies its contribution to the emergence of genomic instability, including events of chromothripsis. Genetic ablation of mesenchymal lineages robustly abolished these mutational processes and evolutionary patterns, as confirmed by cross-species analysis of pancreatic and other human solid tumours. Mechanistically, we identified that malignant cells with mesenchymal features display increased chromatin accessibility, particularly in the pericentromeric and centromeric regions, in turn resulting in delayed mitosis and catastrophic cell division. Thus, EMT favours the emergence of genomic-unstable, highly fit tumour cells, which strongly supports the concept of cell-state-restricted patterns of evolution, whereby cancer cell speciation is propagated to progeny within restricted functional compartments. Restraining the evolutionary routes through ablation of clones capable of mesenchymal plasticity, and extinction of the derived lineages, halts the malignant potential of one of the most aggressive forms of human cancer.

Animals↗

PubMed2026

A latent activated olfactory stem cell state revealed by single-cell transcriptomic and epigenomic profiling.

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration in response to injury. In this study, we used single-cell sequencing to identify transcriptional and epigenetic processes involved in determining olfactory epithelial stem cell fate during injury-induced regeneration. By combining gene expression and accessible chromatin profiles of individual lineage-traced olfactory stem cells, we identified transcriptional heterogeneity among activated stem cells at a stage when cell fates are being specified. We further identified a subset of resting cells that appears poised for activation, characterized by accessible chromatin around silent genes prior to their expression in response to injury. These results provide evidence for a latent activated stem cell state in which a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

Animals↗

PubMed2026

LAML-Pro: joint maximum likelihood inference of cell genotypes and cell lineage trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (i) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (ii) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (≈25%-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is implemented in C++ and is available as both a command-line interface and as a Python library at: github.com/raphael-group/LAML-Pro.

Cell Lineage↗

PubMed2025

Tracking HIV persistence across T cell lineages during early ART-treated HIV-1-infection using a reservoir-marking humanized mouse model.

Human immunodeficiency virus (HIV) infection depletes CD4 T-cells, and long-term persistence of latent virus prevents full clearance of HIV even in the presence of effective antiretroviral therapy (ART), Here we present the HIV-1-induced lineage tracing (HILT) system, a model that irreversibly marks infected cells within a humanized mouse model, which detects rare latently infected cells. Immunodeficient mice transplanted with genetically modified hematopoietic stem cells develop a human immune system, in which CD4 T-cells contain a genetic switch that permanently labels cells infected by HIV-1 expressing cre-recombinase. Through single-cell RNA sequencing of HILT-marked cells during acute infection and post-ART treatment, we identify distinct CD4+ T-cell transcriptional lineages enriched in either active or latent infections. Comparative gene expression analysis highlights common pathways modulated in both states, including EIF2, Sirtuin, and protein ubiquitination. Critical regulators of these pathways, including JUN, BCL2, and MDM2, change to opposite directions in the two states, highlighting gene expression programs that may support HIV persistence across T-cell lineages and states.

Animals↗

PubMed2025

Hypoxia-inducible factor 2 regulates alveolar regeneration after repetitive injury in three-dimensional cellular and in vivo models.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease in which repetitive epithelial injury and incomplete alveolar repair result in accumulation of profibrotic intermediate/transitional "aberrant" epithelial cell states. The mechanisms leading to the emergence and persistence of aberrant epithelial populations in the distal lung remain incompletely understood. By interrogating single-cell RNA sequencing (scRNA-seq) data from patients with IPF and a mouse model of repeated lung epithelial injury, we identified persistent activation of hypoxia-inducible factor (HIF) signaling in these aberrant epithelial cells. Using mouse genetic lineage-tracing strategies together with scRNA-seq, we found that these disease-emergent aberrant epithelial cells predominantly arose from airway-derived (Scgb1a1-CreER-traced) progenitors and exhibited transcriptional programs of Hif2a activation. In mice treated with repetitive intratracheal bleomycin, deletion of Epas1 (Hif2a) but not Hif1a, from airway-derived progenitors, or administration of the small-molecule HIF2 inhibitor PT-2385, using both prevention and rescue approaches, attenuated experimental lung fibrosis, reduced the appearance of aberrant epithelial cells, and promoted alveolar repair. In mouse alveolar organoids, genetic or pharmacologic inhibition of Hif2 promoted alveolar differentiation of airway-derived epithelial progenitors. In addition, treatment of human distal lung organoids with PT-2385 increased colony-forming efficiency, enhanced protein and transcriptional markers of alveolar type 2 epithelial cell maturation, and prevented the emergence of aberrant epithelial cells. Together, these studies showed that HIF2 activation drives the emergence of aberrant epithelial populations after repetitive injury and that targeted HIF2 inhibition may represent an effective therapeutic strategy to promote functional alveolar repair in IPF and other interstitial lung diseases.

Animals↗

PubMed2025

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction.

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells.

Humans↗