Biology subjects

Nguyen, L. T.

Publications and source records attributed to Nguyen, L. T..

At least 19 recordsLinked to original sources

bioRxiv2026

Origins Anywhere and Everywhere: Genome replication requires cooperative activation of thousands of origins in each cell

Our model of replication dynamics in a single eukaryotic cell supplants current population-based models. Long-read sequencing reveals cooperative activation of ~8400 closely spaced origins in every S.cerevisiae cell. Origins with bidirectional forks of comparable velocities are evenly distributed across the genome. The probability of early origin activation directly correlates with the average density of ORC (Origin Recognition Complex) binding motifs in a 10-20kbp region. We propose that 3D chromosome folding creates genomic pockets that act as ORC traps to increase local concentrations of pre-RC (Replication Complexes) and favor origin activation. Our results indicate that efficient replication through chromatin requires the activation of thousands of origins spanning the entire genome. This is consistent with genome instability being caused by insufficient origin activation rather than by perturbations in the replication timing program.

genomics↗

bioRxiv2026

Metagenomic prediction of methane emissions in sheep using single- and multi-matrix BLUP models with taxonomic and functional microbial features

BackgroundEnteric methane emissions from ruminant livestock represent a major greenhouse gas contributor, yet identification of high- and low-emitting ruminants remains expensive and logistically challenging for agricultural methane mitigation strategies. Ruminal microbial profiles derived from long-read sequencing technology provide a potential proxy to predict methane production. The optimal bioinformatic pipelines for processing long-read metagenomic data to perform methane predictions have yet to be determined. Here we evaluated how different metagenomic analysis pipelines affect methane predictive model accuracy in grazing sheep. ResultsWe applied three bioinformatic pipelines to characterize the taxonomic and functional features of rumen microbiomes from 396 sheep. Functional abundance features were annotated from Clusters of Orthologous Genes (COG) or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The single-matrix model using COG features achieved the highest microbiability (m2 = 0.942: proportion of variance component explained by microbial features) and predictive accuracy (5-fold cross validation r = 0.609: Pearsons correlation between predicted and observed values). Both functional features outperformed all taxonomic features across all three pipelines in predictive accuracy. The multi-matrix models combined functional and taxonomic features slightly improved methane predictive accuracy across both 5-fold cross-validation and leave-one-day-out validation compared to the models using functional features alone. ConclusionsThese findings demonstrate the potential advantages of using long-read metagenomic data to predict enteric methane emissions in ruminants. COG-based functional features achieved the highest predictive accuracy among all feature types, suggesting that functional annotation of existing long-read sequences is sufficient for accurate methane prediction without requiring complementary taxonomic data.

genomics↗

bioRxiv2026

Structure-Property-Performance Engineering of Hydrogel Depots for Long-Acting Peptide Delivery

Controlled release systems for subcutaneous peptide delivery often exhibit a pronounced initial burst release followed by inadequate maintenance of therapeutic exposure, limiting depot lifetime and increasing pharmacokinetic variability. Here, we engineer a dynamic, injectable hydrogel depot technology for months-long delivery of lipidated peptides. Using semaglutide as a model, we establish a modular formulation framework integrating: (i) formulation-driven tuning of depot mechanics to control release kinetics, (ii) cargo complexation strategies leveraging hydrophobic and multivalent ion-mediated interactions, and (iii) oxidative stabilization through sacrificial antioxidant excipients. We evaluated depot performance by rheology, in vitro cargo release, and in vivo pharmacokinetic and pharmacodynamic studies in rodents. Optimized formulations sustained semaglutide exposure for over six weeks from a single administration with two-fold reduction in peak-to-trough exposure and comparable total bioavailability relative to daily dosing, resulting in improved glucose control, weight regulation, and preservation of pancreatic islet content. These results suggest potential for quarterly dosing in humans. Together, this work establishes integrated and generalizable structure-property-performance relationships that account for cargo-matrix and cargo-excipient interactions across burst, diffusion, and erosion regimes to inform a practical formulation framework for engineering long-acting depots for sustained peptide delivery.

bioengineering↗

bioRxiv2025

THE IMPACT OF ARTIFICIAL INTELLIGENCE ON UNIVERSITY STUDENTS PERCEPTIONS OF ENVIRONMENTAL CHALLENGES AND SUSTAINABLE SOLUTIONS

In the context of Vietnams higher education strongly transforming towards digitalization and sustainability, this study aims to analyze the impact of artificial intelligence (AI) on students awareness and intention to act for the environment. Based on the Extended Planned Behavior (TPB) model, the research model integrates two input factors: environmental awareness (EA) and the level of interaction with AI in environmental learning (AEEL), affecting three mediating factors: attitude (AT), subjective norm (SN) and perceived behavioral control (PBC), thereby predicting students green action intention (GAI). Data collected from 521 students at private university in Vietnam were processed using EFA, CFA and SEM. The results showed that both EA and AEEL had positive effects on AT, SN and PBC (p < 0.001). Among them, AEEL had the strongest influence on SN ({beta} = 0.281) and PBC ({beta} = 0.252). PBC had the strongest influence on GAI ({beta} = 0.312), followed by AT ({beta} = 0.274) and SN ({beta} = 0.267). Bootstrapping mediation analysis confirmed that the mediating variables (AT, SN, PBC) played an important role in linking EA and AEEL with GAI. In addition, cluster analysis showed that female students and senior students had significantly higher levels of AI engagement and action intention. These results suggest that AI not only serves as a learning support tool but also as a catalyst for sustainable behavior in higher education.

scientific communication and education↗

bioRxiv2025

Long-acting hydrogel-based depot formulations of tirzepatide and semaglutide for the management of type 2 diabetes and weight

Several incretin hormone therapies have been clinically approved and have revolutionized the treatment of diabetes and obesity. Promising therapeutics include semaglutide (Ozempic(R) and Wegovy(R)), an agonist for glucagon-like peptide-1 (GLP-1) receptor, and tirzepatide (Mounjaro(R)), a dual agonist for GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptors. These molecules help to regulate blood glucose levels, enhance insulin secretion and sensitivity, and reduce appetite. Currently, these treatments require weekly injections, which can be challenging for patients to adhere to. We recently reported the development of an injectable hydrogel depot technology enabling months-long release of semaglutide (Sema). Here, we further develop this technology for improved prolonged release of both Sema and tirzepatide (TZP). In a rat model of diabetes, we show a single administration of hydrogel-based formulations of either Sema or TZP maintained relevant drug levels for over 6 weeks. In these studies, single administrations of long-acting hydrogel-based therapies of Sema or TZP were similarly effective at regulating blood glucose and weight compared to daily injections of either Sema or TZP in standard aqueous vehicles. This hydrogel depot technology is easy to manufacture, injectable, and exhibits excellent biocompatibility, enabling months-long-acting treatments with the potential to improve management of diabetes and weight.

bioengineering↗

bioRxiv2025

Engineering Sustained-Release Broadly Neutralizing Antibody Formulations

Sustained serum levels of broadly neutralizing antibodies (bnAbs) are crucial for effective passive immunization against infectious diseases as protection persists only while these bnAbs remain at adequate concentrations within the body. Current obstacles, such as poor pharmacokinetics (PK) and burdensome administration, must be overcome to make bnAbs a viable option for pre- and post-exposure prophylaxis. In this work, we explore how a polymer-nanoparticle (PNP) hydrogel depot technology can be engineered to prolong protein delivery. In-vivo studies in mice and rats demonstrate prolonged protein release, and modeling efforts predict the impact of both the elimination half-life of the active pharmaceutical ingredient and hydrogel depot volume on overall pharmacokinetics. Moreover, flow cytometry characterization reveals that immune cell infiltration into the hydrogel depot can result in faster-than-expected release of antibody cargo on account of active transport via cellular uptake. We then demonstrate that co-formulation of antibodies with an anti-inflammatory agent reduces cellular infiltration and resulting active transport, further extending delivery and pharmacokinetics. Finally, multicompartmental modeling predicts the human PK profiles of clinically relevant HIV bnAbs delivered via subcutaneous hydrogel injection. These findings aid in the development of next generation hydrogel materials that stabilize and slowly release bnAbs for long-term pre-exposure immunoprophylaxis.

bioengineering↗

bioRxiv2025

VN1K: a genome graph-based and function-driven multi-omics and phenomics resource for the Vietnamese population

Vietnam, the 16th most populated nation, remains profoundly underrepresented in global genomic databases. Here, we present VN1K, a first-ever comprehensive and well-curated resource of multi-omics data with a wide-range of phenotypic information of 1,011 unrelated Vietnamese individuals. High-depth short-read whole-genome sequencing data were generated for all samples along with various - omic data, including microarray, long-read whole-genome sequencing, and RNA sequencing. Using a high-sensitivity variant detection pipeline, which included a pangenome graph reference and a deep-learning framework, we identified nearly 40 million variants of which 8.5 million are novel with nearly 900 thousand short insertions/deletions and 39 thousand structural variants. Specifically, VN1K featured a first-ever whole-genome methylation profile based on long read sequencing. A genotype imputation panel was also created with the highest accuracy on the Vietnamese population. Variants with significantly different allele frequencies in the Vietnamese population compared to others were found to be functionally significant, especially in genes associated with immune diseases (HLA-B, KIR3DL3, KIR2DL1, KIR2DL4) or drug responses (CYP2C19, CYP2D6, VKORC1, CYP2B6). We were also able to map various loci related to hepatitis B virus infection as well as six disease traits, including triglyceride levels, LDL-C, serum glucose levels, HbA1c, and levels of two liver enzymes (ALT and AST). VN1K dataset is accessible via genome.vinbigdata.org, an integrated platform with both linear and graph-based genome browser for facilitating data exploration, research, and applications in precision medicine.

genomics↗

bioRxiv2025

Multimodal control of Cas13 activity through domain insertion at an allosteric hotspot

CRISPR-Cas13 RNA nucleases have emerged as powerful tools for programmable RNA targeting. A light-controlled RNA nuclease could be transformative by enabling researchers to selectively knock down transcripts at desired positions in a cell or tissue or at timepoints of interest. Here, we develop a set of multimodal RfxCas13d tools that can be controlled by either light or small molecule addition. Screening an RfxCas13d library containing insertions of the AsLOV2 photoswitchable domain revealed an OptoCas13d-off variant that induced target RNA cleavage in the dark and switched to an inactive state under blue light. Insertion at this same allosteric hotspot could be further exploited to generate an OptoCas13d-on with the opposite light dependence and a ChemoCas13d that is activated upon the addition of rapamycin analogs. Through biochemical assays, we showed that AsLOV2 domain switching did not substantially affect Cas13d-RNA complex formation, indicating allosteric control over Cas13d catalytic activity. We applied the OptoCas13d-on system to target several endogenous transcripts and showed that it exhibited efficient mRNA knockdown only upon blue light illumination. Overall, our results demonstrate that engineered OptoCas13d can achieve cellular RNA modulation with high spatial and temporal precision.

bioengineering↗

bioRxiv2025

Training Generalized Segmentation Networks with Real and Synthetic Cryo-ET data.

Deep learning excels at segmenting objects within noisy cryo-electron tomograms, but the approach is typically bottlenecked by access to ground truth training data. To address this issue we have developed CryoTomoSim (CTS), an open-source software package that builds coarse-grained models of macromolecular complexes embedded in vitreous ice and then simulates transmitted electron tilt series for tomographic reconstruction. Using CTS outputs, we demonstrate the effects of key microscope parameters (dose, defocus, and pixel size) on deep learning-based segmentation, and show that including both molecular crowding and diversity within synthetic datasets is key to training cellular segmentation networks from purely synthetic inputs. While very effective as initial models, the accuracy of these networks is currently limited, and real cellular data is necessary to train the most accurate and generalizable U-Nets. Using a co-training approach, we first segment over 100 tomograms from neuronal growth cones to quantify their cytoskeletal distributions and then we build a generalized cellular cryo-ET segmentation network called NeuralSeg that can segment a subset of cellular features in tomograms from all domains of life.

cell biology↗

bioRxiv2024

FAK activity exacerbates disturbed flow-mediated atherosclerosis via VEGFR2-Cbl-NF-κB signaling.

Atherosclerosis develops at predictable sites in the vasculature where branch points and curvatures create non-laminar disturbed flow. This disturbed flow causes vascular inflammation by increased endothelial cell (EC) barrier permeability and the expression of inflammatory genes such as vascular cell adhesion molecule-1 (VCAM-1). Vascular endothelial growth factor receptor 2 (VEGFR2) is important for flow-induced EC inflammation; however, there are still some gaps in the signaling pathway. Focal adhesion kinase (FAK) is a protein tyrosine kinase whose expression has been implicated in flow-mediated signaling in ECs. However, the link between FAK and VEGFR2 in flow-mediated inflammation signaling has remained unelucidated. Here we found that priming of VEGFR2 with VEGF was critical for flow-mediated activation of FAK and NF-kB. Mechanistically, FAK activation triggers tyrosine phosphorylation of Casitas B-lineage lymphoma (CBL; an E3 ubiquitin ligase) that interacts with VEGFR2 under flow conditions. Further, Apoe-/- mice fed a western diet (WD) exhibited increased FAK activity within the atheroprone disturbed flow region of the inner aortic arch compared to the outer arch. Disturbed flow-induced FAK activation is associated with elevated VEGFR2 on the surface of ECs of the inner aortic arch, but not in the outer arch. Taken together, these data suggest that suppression of augmented FAK activity under disturbed flow may prove beneficial in reducing pro-inflammatory signaling of the endothelial layer.

cell biology↗

bioRxiv2024

Unraveling lncRNA Diversity at a Single Cell Resolution and in a Spatial Context across Different Cancer Types

Long non-coding RNAs (lncRNAs) play pivotal roles in gene regulation and disease, including cancer. Overcoming the limitations of lncRNA analysis with bulk data, we analyzed single-cell and spatial transcriptomics data to uncover 354937 novel lncRNAs and their functions across 13 cancer types. LncRNA functions were assessed by identifying their cell-type specificity and distinct spatial distributions across different tissue regions. First, lncRNAs were computationally validated by comparing to existing databases, and experimentally validated using spatial long read sequencing methods. Further, genome-wide computation of spatial-autocorrelation identified coexpression of lncRNAs with cancer-associated protein coding genes across the tissue. Additionally, genomic co-localization of lncRNAs with regulatory features and disease-associated genetic variants suggest possible functional association. The identified lncRNAs were analyzed for responses to immunotherapy and prognostic value, revealing cancer-outcome associated lncRNAs. We have made this novel resource available as an open website SPanC-Lnc hosted on AWS cloud to serve as a pan-cancer atlas of single cell- and spatially-resolved lncRNAs. These can complement established biomarkers because they reflect the unique characteristics of specific cell populations within tumors, offering new insights into disease progression and treatment response.

cancer biology↗

bioRxiv2024

Efficient Genome Editing with Chimeric Oligonucleotide-Directed Editing

Prime editing has emerged as a precise and powerful genome editing tool, offering a favorable gene editing profile compared to other Cas9-based approaches. Here we report new nCas9-DNA polymerase fusion proteins to create chimeric oligonucleotide-directed editing (CODE) systems for search-and-replace genome editing. Through successive rounds of engineering, we developed CODEMax and CODEMax(exo+) editors that achieve efficient genome modifications in human cells with low unintended edits. CODEMax and CODEMax(exo+) contain an engineered Bst DNA polymerase derivative known for its robust strand displacement ability. Additionally, CODEMax(exo+) features a 5 to 3 exonuclease activity that promotes effective strand invasion and repair outcomes favoring the incorporation of the desired edit. We demonstrate CODEs can perform small insertions, deletions, and substitutions with improved efficiency compared to PEMax at many loci. Overall, CODEs complement existing prime editors to expand the toolbox for genome manipulations without double-stranded breaks.

bioengineering↗

bioRxiv2024

Elucidating structure-function relationships of amphiphilic copolymer excipients to enhance the stability of biopharmaceuticals

Biopharmaceuticals are the fastest growing class of drugs in the healthcare industry, but their global reach is severely limited by their propensity for rapid aggregation. Currently, surfactant excipients such as polysorbates and poloxamers are used to prevent protein aggregation, which significantly extends shelf-life. Unfortunately, these excipients are themselves unstable, oxidizing rapidly into 100s of distinct compounds, some of which cause severe adverse events in patients. Here, we leverage the highly stable, well-defined, and modular nature of amphiphilic polyacrylamide-derived excipients to isolate the key mechanisms responsible for excipient-mediated protein stabilization. With a library of compositionally identical but structurally distinct amphiphilic copolymers, we quantify multiple relationships between polymer properties and fundamental phenomena to rationally design new ultra-stable surfactant excipients, increasing the stability of a notoriously unstable biopharmaceutical, monomeric insulin, by an order of magnitude. This comprehensive and generalizable understanding of excipient structure-function relationships represents a paradigm shift for the formulation of biopharmaceuticals, moving away from trial-and-error screening approaches towards rational design. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/599313v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1d3a557org.highwire.dtl.DTLVardef@c1277org.highwire.dtl.DTLVardef@904be2org.highwire.dtl.DTLVardef@1660ed4_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

WHIRLY1 regulates aliphatic glucosinolate biosynthesis in early seedling development of Arabidopsis

WHIRLY1 belongs to a family of plant-specific transcription factors capable of binding DNA or RNA in all three plant cell compartments that contain genetic materials. In Arabidopsis thaliana, WHIRLY1 has been studied at the later stages of plant development, including flowering and leaf senescence, as well as in biotic and abiotic stress responses. In this study, WHIRLY1 knock-out mutants of A. thaliana were prepared by CRISPR/Cas9 to investigate the role of AtWHIRLY1 during early seedling development. The loss-of-function of WHIRLY1 in 5-day-old seedlings did not cause differences in the phenotype and the photosynthetic performance of the emerging cotyledons compared to the wild type. Nevertheless, comparative RNA sequencing analysis revealed that the knock-out of WHIRLY1 affected the expression of a small but specific set of genes during this critical phase of development. About 110 genes were found to be significantly deregulated in the knockout mutant, wherein several genes involved in the early steps of aliphatic glucosinolate (aGSL) biosynthesis were suppressed compared to wild type plants. The downregulation of these genes in WHIRLY1 knock-out line led to a decreased GSL contents in seedlings and in seeds. We also examined myrosinase activity during seed-seedling transition and showed that the reduction in aGSL biosynthesis is the main reason for lowering aGSL content in young seedlings. The results suggest that AtWHIRLY1 plays a role in regulating aliphatic glucosinolate biosynthesis during early seedling development. Significance statementWHIRLY1 functions in several aspects of plant development and stress responses, however little is known about its involvement in young seedling development. Here we show that in this stage, WHIRLY1 specifically regulates expression of genes encoding enzymes in the early steps of aliphatic glucosinolate biosynthesis pathway, leading to a reduction in glucosinolate content in the WHIRLY1 knock-out seedlings.

plant biology↗

bioRxiv2024

Arginine methylation of the p30 C/EBPα oncoprotein regulates progenitor proliferation and myeloid differentiation

The transcription factor CCAAT enhancer binding protein alpha (C/EBP) is a master regulator of myelopoiesis. CEBPA encodes a long (p42) and a truncated (p30) protein isoform from a single mRNA. Mutations that abnormally enhance expression of p30 are associated with acute myelogenous leukemia (AML). We show by mutational analysis that three highly conserved arginine residues (R140,147,154) located at the p30 C/EBP N-terminus, previously found to be methylated, are involved in myeloid lineage commitment, progenitor proliferation, and differentiation. Replacement with lysine that retains the amino acid side chain charge enhanced progenitor proliferation, while uncharged side chains (alanine or leucine) impaired proliferation and enhanced granulopoietic differentiation. Analysis of protein-protein interactions (PPI) suggested that arginine methylation of p30 C/EBP differentially determines its capacity to interact with SWI/SNF and MLL complexes. Pharmacological targeting of p30 C/EBP arginine methylation may have clinical relevance in myeloproliferative and inflammatory diseases, in neutropenia, and in leukemic stem cells.

cell biology↗

bioRxiv2024

A novel GLYCEROPHOSPHODIESTER PHOSPHODIESTERASE 13 is involved in the Phosphate starvation-induced lipid remodeling in rice

Phosphorus (P) is one of the most vital macronutrient determinants in plant development and productivity. However, the bioavailability of inorganic phosphate (Pi), the only form that plants can assimilate, is limited in the soil, thus significantly affecting plant development. Plants have adopted various specialized strategies to modify their morphological, physiological, and biochemical properties for better adaptation to Pi deficiency conditions. GLYCEROPHOSPHODIESTER PHOSPHODIESTERASES (GDPDs), generally known as phospholipid remodeling proteins, have been suggested to play essential roles in maintaining phosphate homeostasis. The previous genome-wide association studies (GWAS) in a Vietnamese rice collection led to the discovery of a robust QTL named qRST9.14 associating with the phosphate adaption in rice, in which OsGDPD13 is located within this locus. Interestingly, we discovered an absence of OsGDPD13 from the Indica reference genome. A subcellular localization study showed that the GDPD13 protein localizes to the plasma membrane, cytoplasmic speckles, and plasmodesmata. The osgdpd13 knockout mutant was generated in the Japonica cv Kitaake background to characterize its function. Phenotypic analysis indicated that mutation of OsGDPD13 significantly lowered crown root number and reduced the plant height under Pi deficient condition. Moreover, osgdpd13 lines reduce the capability to degrade total phospholipids compared to the wild type under Pi starvation conditions. This finding suggests the involvement of the OsGDPD13 gene in rice growth and the Phosphate starvation-induced lipid remodeling under P deficiency. This work will provide valuable information for developing crop plants with higher Phosphate use efficiency.

plant biology↗

bioRxiv2024

Discovery of orally active SARS-CoV-2 papain-like protease (PLpro) inhibitors

Vaccines and first-generation antiviral therapeutics have provided important protection against coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there remains a need for additional therapeutic options that provide enhanced efficacy and protection against potential viral resistance. The SARS-CoV-2 papain-like protease (PLpro) is one of two essential cysteine proteases involved in viral replication. While inhibitors of the SARS-CoV-2 main protease (Mpro) have demonstrated clinical efficacy, known PLpro inhibitors have to date lacked the inhibitory potency and requisite pharmacokinetics to demonstrate that targeting PLpro translates to in vivo efficacy in a preclinical setting. Herein, we report the machine learning-driven discovery of potent, selective, and orally available SARS-CoV-2 PLpro inhibitors, with lead compound PF-07957472 (4) providing robust efficacy in a mouse-adapted model of COVID-19 infection.

microbiology↗

bioRxiv2023

A deep lung cell atlas reveals cytokine-mediated lineage switching of a rare cell progenitor of the human airway epithelium

The human airway contains specialized rare epithelial cells whose roles in respiratory disease are not well understood. Ionocytes express the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR), while chemosensory tuft cells express asthma-associated alarmins. However, surprisingly, exceedingly few mature tuft cells have been identified in human lung cell atlases despite the ready identification of rare ionocytes and neuroendocrine cells. To identify human rare cell progenitors and define their lineage relationship to mature tuft cells, we generated a deep lung cell atlas containing 311,748 single cell RNA-Seq (scRNA-seq) profiles from discrete anatomic sites along the large and small airways and lung lobes of explanted donor lungs that could not be used for organ transplantation. Of 154,222 airway epithelial cells, we identified 687 ionocytes (0.45%) that are present in similar proportions in both large and small airways, suggesting that they may contribute to both large and small airways pathologies in CF. In stark contrast, we recovered only 3 mature tuft cells (0.002%). Instead, we identified rare bipotent progenitor cells that can give rise to both ionocytes and tuft cells, which we termed tuft-ionocyte progenitor cells (TIP cells). Remarkably, the cycling fraction of these TIP cells was comparable to that of basal stem cells. We used scRNA-seq and scATAC-seq to predict transcription factors that mark this novel rare cell progenitor population and define intermediate states during TIP cell lineage transitions en route to the differentiation of mature ionocytes and tuft cells. The default lineage of TIP cell descendants is skewed towards ionocytes, explaining the paucity of mature tuft cells in the human airway. However, Type 2 and Type 17 cytokines, associated with asthma and CF, diverted the lineage of TIP cell descendants in vitro, resulting in the differentiation of mature tuft cells at the expense of ionocytes. Consistent with this model of mature tuft cell differentiation, we identify mature tuft cells in a patient who died from an asthma flare. Overall, our findings suggest that the immune signaling pathways active in asthma and CF may skew the composition of disease-relevant rare cells and illustrate how deep atlases are required for identifying physiologically-relevant scarce cell populations.

cell biology↗