Biology subjects

Ansari, M.

Publications and source records attributed to Ansari, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Distinct roles of Hsp110 proteins in regulating prion propagation

Prion diseases are fatal, transmissible neurodegenerative disorders characterized by the conformational conversion of the cellular prion protein (PrPC) into its pathogenic isoform PrPSc. Propagation of prions depends on the fragmentation of PrPSc aggregates to generate new seeds. However, the factors regulating this process remain incompletely understood. For yeast prions, Hsp104 that has no mammalian homologue, is firmly established as a disaggregase. Hsp110 has emerged as a potential mediator of protein disaggregation and aggregate remodeling in mammalian cells. Although Hsp110 proteins have been implicated in several protein misfolding disorders, their individual contributions to mammalian prion propagation have not been characterized. In this study, we examined the roles of the three Hsp110 proteins -Apg-1, Apg-2, and Hsp105- in cellular prion infection. CRISPR-generated knockout cell lines were established for each Hsp110 and evaluated for their effect on de novo prion infection. PrPSc accumulation was assessed by immunoblot across serial passages and up to 40 days, and prion seeding activity was quantified using real-time quaking-induced conversion (RT-QuIC). Loss of individual Hsp110s produced distinct effects on prion propagation. Apg-1-deficient cells exhibited strongly reduced levels of PrPSc over all passages analyzed, suggesting a role for Apg-1 in establishing persistent prion infection. Interestingly, prion seeding activity was detectable in later passages. Hsp105-deficient cells displayed reduced PrPSc levels during the early stages, indicating that Hsp105 contributes to early prion replication. In contrast, Apg-2 knockout resulted in high prion seeding activity over all passages analyzed and only slightly reduced PrPSc levels in early passages. Collectively, these findings demonstrate that Hsp110 family members perform distinct functions during early phases of prion infection and establishment of persistent infection. This work provides new insight into the role of molecular chaperones in prion biology and identifies Hsp110 proteins as potential modulators of prion replication and potentially therapeutic targets for protein misfolding diseases.

molecular biology↗

bioRxiv2026

Borrelia burgdorferi infection-enhanced Ixodes scapularis serpins S12c5 and S13c5, target MASP1/3 to inhibit MBL-pathway complement activation and promote spirochete survival

Tick serine protease inhibitors (serpins) are critical for tick feeding success and pathogen transmission. We previously demonstrated that two unique serpins, S12c5 and S13c5, are tandemly duplicated on Ixodes scapularis chromosome 5 and are injected into the host at heightened levels during feeding by Borrelia burgdorferi (Bb)-infected nymphs. Here, we characterize the biochemical properties and immunomodulatory functions of these serpins and investigate their roles in promoting Bb transmission. Despite their response to Bb infection, S12c5 and S13c5 share less than 20% overall amino acid identity and differ critically at their reactive center loop (RCL) P1 site, which determines substrate specificity: S13c5 contains a basic arginine residue, while S12c5 contains a polar serine residue. Consistent with these differences, recombinant S13c5 efficiently inhibited innate immune proteases including fXa, plasmin, and trypsin IV (SI: 2.5, 1.9, and 1.0; ka: 8.56 x 103, 3.97 x 10, and 1.08 x 10 M-{superscript 1}s-{superscript 1}, respectively), and consequently delayed plasma clotting via the common pathway, whereas rS12c5 did not inhibit these proteases. However, despite molecular modeling predicting stronger interactions between S13c5 and complement proteases, both serpins inhibited MBL-pathway complement activation by targeting MASP1/3. Deletion of the RCL domain abolished this inhibitory activity, confirming both proteins function as typical inhibitory serpins. Functionally, rS13c5 enhanced Bb colonization in C3H mouse organs. Interestingly, immune response assays revealed a trade-off: S13c5, despite its broader inhibitory activity, was less immunogenic than S12c5. Collectively, these findings establish S12c5 and S13c5 as Bb transmission factors that promote spirochete survival through disruption of host innate immunity.

Molecular Biology↗

bioRxiv2025

Single cell decomposition of multicellular aging programs associated with impaired lung regeneration

Aging impairs the regenerative capacity of mammalian organs and is a major risk factor for organ fibrosis. Mechanisms underlying persistent fibrosis after lung injury in old individuals remain unclear. We used longitudinal single-cell RNA-seq after lung injury and dissected aging effects computationally and experimentally at baseline and during repair. In old mice, sustained fibroblast activation in the resolution phase of fibrosis was associated with prolonged epithelial senescence and persistent epithelial-mesenchymal crosstalk. Single-cell interpretable tensor decomposition analysis revealed that aging most strongly affected T/B-lymphocytes and macrophages. Notably, we identified a Granzyme K-high CD8+ T cell state that was unique to aged mice, co-localized with epithelial progenitors, and its co-culture or Gzmk treatments in lung organoids impaired progenitor function by inducing stem cell senescence. In summary, our study highlights the effects of immune aging on epithelial progenitor function and provides a time-resolved high resolution map of lung regeneration in the context of aging.

cell biology↗

bioRxiv2024

JUNB O-GlcNAcylation-mediated promoter accessibility of metabolic genes modulates distinct epithelial lineage in pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lethal disease with substantial unmet medical needs. While aberrant epithelial remodelling is a key factor in IPF progression, the molecular mechanisms behind this process remain elusive. Using a patient-derived 3D distal airway epithelial organoid model, we successfully recapitulate important IPF features, including the emergence of aberrant KRT5+/COL1A1+ basal cells and a metabolic shift towards increased O-linked {beta}-N-acetylglucosamine (O-GlcNAc) levels. Consistent with this, single-cell analysis of accessible chromatin reveals an increased chromatin accessibility in these aberrant basal cells, particularly at JUNB motif-enriched promoter regions of metabolic genes. O-GlcNAcylation shapes JUNB function and promotes a pro-fibrotic response to chronic injury, leading to aberrant epithelial remodelling. Site-specific deletion of O-GlcNAcylation on JUNB attenuates the metaplastic differentiation of basal cells, thereby aiding in the restoration of the alveolar lineage. Together, these data establish a novel link between metabolic dysregulation, mediated by the O-GlcNAc-JUNB axis, and bronchiolization in IPF, offering new therapeutic strategies to treat this fatal disease.

cell biology↗

bioRxiv2024

Cell circuits underlying nanomaterial specific respiratory toxicology

Nanomaterials emerged as boundless resource of innovation, but their shape and biopersistence related to respiratory toxicology raise longstanding concerns. The development of predictive safety tests for inhaled nanomaterials, however, is hampered by limited understanding of cell type-specific responses. To advance this knowledge, we used single-cell RNA-sequencing to longitudinally analyze cellular perturbations in mice, caused by three carbonaceous nanomaterials of different shape and toxicity upon pulmonary delivery. Focusing on nanomaterial-specific dynamics of lung inflammation, we found persistent depletion of alveolar macrophages by fiber-shaped nanotubes. While only little involvement was observed for alveolar macrophages during the initiation phase, they emerged, together with infiltrating monocyte-derived macrophages, as decisive factors in shifting inflammation towards resolution for spherical nanomaterials, or chronic inflammation for fibers. Fibroblasts, central for fibrosis, sensed macrophage and epithelial signals and emerged as orchestrators of nanomaterial-induced inflammation. Thus, the mode of actions identified in this study will significantly inspire the precision of future in vitro testing. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/579746v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1d6f061org.highwire.dtl.DTLVardef@3fabb1org.highwire.dtl.DTLVardef@21040eorg.highwire.dtl.DTLVardef@1915c3b_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2023

Learning Peptide Properties with Positive Examples Only

AO_SCPLOWBSTRACTC_SCPLOWDeep learning can create accurate predictive models by exploiting existing large-scale experimental data, and guide the design of molecules. However, a major barrier is the requirement of both positive and negative examples in the classical supervised learning frameworks. Notably, most peptide databases come with missing information and low number of observations on negative examples, as such sequences are hard to obtain using high-throughput screening methods. To address this challenge, we solely exploit the limited known positive examples in a semi-supervised setting, and discover peptide sequences that are likely to map to certain antimicrobial properties via positive-unlabeled learning (PU). In particular, we use the two learning strategies of adapting base classifier and reliable negative identification to build deep learning models for inferring solubility, hemolysis, binding against SHP-2, and non-fouling activity of peptides, given their sequence. We evaluate the predictive performance of our PU learning method and show that by only using the positive data, it can achieve competitive performance when compared with the classical positive-negative (PN) classification approach, where there is access to both positive and negative examples.

bioinformatics↗

bioRxiv2023

Phosphoproteomics of cellular mechanosensing reveals NFATC4 as a regulator of myofibroblast activity

Feedback connections between tissue stiffness and cellular contractile forces can instruct cell identity and activity via a process referred to as mechanosensing. Specific phosphoproteome changes during mechanosensing are poorly characterized. In this work, we chart the global phosphoproteome dynamics of primary human lung fibroblasts sensing the stiffness of injury relevant fibronectin coated Poly(dimethylsiloxane) substrates. We discovered a key signaling threshold at a Youngs modulus of eight kPa stiffness, above which cells activated a large number of pathways including RhoA, CK2A1, PKA, AMPK, AKT1, and Hippo-YAP1/TAZ mediated signaling. Time-resolved phosphoproteomics of cell spreading on stiff substrates revealed the temporal dynamics of these stiffness-sensitive signaling pathways. ECM substrate stiffness above eight kPA induced fibroblast contractility, cytoskeletal rearrangements, ECM secretion, and a fibroblast to myofibroblast transition. Our data indicate that phosphorylation of the transcriptional regulator NFATC4 at S213/S217 enhances myofibroblast activity, which is the key hallmark of fibrotic diseases. NFATC4 knock down cells display reduced stiffness induced collagen secretion, cell contractility, nuclear deformation and invasion, suggesting NFATC4 as a novel target for antifibrotic therapy. SynopsisHow tissue stiffness regulates identity and activity of tissue fibroblasts is unclear. Mass spectrometry based analysis of tissue stiffness dependent phosphoproteome changes reveals how primary lung fibroblasts sense the mechanical properties of their environment and identifies NFATC4 as a novel regulator of the stiffness dependent transition of fibroblasts to ECM secreting myofibroblasts. O_LIMass spectrometry analysis reveals the signaling landscape of fibroblast mechanosensing C_LIO_LITime-resolved phosphoproteomic analysis of cell spreading on fibronectin C_LIO_LINFATC4 regulates myofibroblast collagen secretion, cell contractility and invasion C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=38 SRC="FIGDIR/small/528335v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@329c68org.highwire.dtl.DTLVardef@ba7513org.highwire.dtl.DTLVardef@15c32c4org.highwire.dtl.DTLVardef@90b96_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Ex vivo tissue perturbations coupled to single cell RNA-seq reveal multi-lineage cell circuit dynamics in human lung fibrogenesis

Pulmonary fibrosis develops as a consequence of failed regeneration after injury. Analyzing mechanisms of regeneration and fibrogenesis directly in human tissue has been hampered by the lack of organotypic models and analytical techniques. In this work, we coupled ex vivo cytokine and drug perturbations of human precision-cut lung slices (hPCLS) with scRNAseq and induced a multi-lineage circuit of fibrogenic cell states in hPCLS, which we show to be highly similar to the in vivo cell circuit in a multi-cohort lung cell atlas from pulmonary fibrosis patients. Using micro-CT staged patient tissues, we characterized the appearance and interaction of myofibroblasts, an ectopic endothelial cell state and basaloid epithelial cells in the thickened alveolar septum of early-stage lung fibrosis. Induction of these states in the ex vivo hPCLS model provides evidence that the basaloid cell state was derived from alveolar type-2 cells, whereas the ectopic endothelial cell state emerged from capillary cell plasticity. Cell-cell communication routes in patients were largely conserved in the hPCLS model and anti-fibrotic drug treatments showed highly cell type specific effects. Our work provides an experimental framework for perturbational single cell genomics directly in human lung tissue that enables analysis of tissue homeostasis, regeneration and pathology. We further demonstrate that hPCLS offers novel avenues for scalable, high-resolution drug testing to accelerate anti-fibrotic drug development and translation.

cell biology↗

bioRxiv2022

An efficient method to generate fluorescent amyloid fibrils

Studies on fluorophore-tagged peptides help in elucidating the molecular mechanism of amyloidogenesis including their cellular internalization and crosstalk potential. Despite several advantages, unavoidable difficulties including expensive and tedious synthesis-protocols exist in fluorophore-based tools. Importantly, covalently-tagged fluorophores could introduce structural constraints which may influence the conformation of the monomeric and aggregated forms of protein. To resolve this problem, we describe a robust yet simple method to make fluorescent amyloid fibrils through non-covalent incorporation of fluorophores into amyloid fibrils. We used aggregation protocol in which a small amount of fluorophore is incorporated into the amyloids, and this protocol does not alter the aggregation kinetics and the characteristic {beta}-sheet-conformers of the generated amyloid fibrils. We have successfully prepared fluorescent amyloid fibrils of Insulin, Lysozyme and A{beta}1-42, and the noncovalently incorporated fluorophores remained intact in the amyloid fibrils without leaching, even after serial-dilutions and prolonged-storage. Further, this method enables successful monitoring of cellular-internalization of the fluorescent amyloids into SH-SY5Y and A549 cells, and it also detects FRET-signals during interfibrillar interactions. The findings establish a simple and affordable protocol to prepare fluorescent amyloid structures, which may significantly help amyloid researchers working on both in vitro and animal model systems.

biophysics↗

bioRxiv2022

HLA variants and TCR diversity against SARS-CoV-2 in the pre-COVID-19 era

HLA antigen presentation and T-cell immunity are critical to control viral infection such as SARS-CoV-2. This study performed on samples collected in the pre-COVID-19 era demonstrates that individuals are fully equiped at the genetic level in terms of TCR repertoire and HLA variants to recognize and kill SARS-CoV-2 infected cells. HLA diversity, heterologous immunity and random somatic TCR recombination could explain these observations.

immunology↗

bioRxiv2022

Autocrine Sfrp1 inhibits lung fibroblast invasion during transition to injury induced myofibroblasts

Fibroblast to myofibroblast conversion is a major driver of tissue remodeling in organ fibrosis. Several distinct lineages of fibroblasts support homeostatic tissue niche functions, yet, specific activation states and phenotypic trajectories of fibroblasts during injury and repair have remained unclear. Here, we combined spatial transcriptomics, longitudinal single-cell RNA-seq and genetic lineage tracing to study fibroblast fates during mouse lung regeneration. We discovered a transitional fibroblast state characterized by high Sfrp1 expression, derived from both Tcf21-Cre lineage positive and negative cells. Sfrp1+ cells appeared early after injury in peribronchiolar, adventitial and alveolar locations and preceded the emergence of myofibroblasts. We identified lineage specific paracrine signals and inferred converging transcriptional trajectories towards Sfrp1+ transitional fibroblasts and Cthrc1+ myofibroblasts. Tgf{beta}1 downregulated Sfrp1 in non-invasive transitional cells and induced their switch to an invasive Cthrc1+ myofibroblast identity. Finally, using loss of function studies we showed that autocrine Sfrp1 directly inhibits fibroblast invasion by regulating the RhoA pathway. In summary, our study reveals the convergence of spatially and transcriptionally distinct fibroblast lineages into transcriptionally uniform myofibroblasts and identifies Sfrp1 as an autocrine inhibitor of fibroblast invasion during early stages of fibrogenesis.

cell biology↗

bioRxiv2022

Serverless Prediction of Peptide Properties with Recurrent Neural Networks

We present three deep learning sequence prediction models for hemolysis, solubility, and resistance to non-specific interactions of peptides that achieve comparable results to the state-of-the-art models. Our sequence-based solubility predictor, MahLooL, outperforms the current state-of-art methods for short peptides. These models are implemented as a static website without the use of a dedicated server or cloud computing. Web-based models like this allow for accessible and effective reproducibility. Most existing approaches rely on third-party servers typically that require upkeep and maintenance. That trend leads to a relatively longer lifetime of web-based models. These predictive models do not require servers, require no installation of dependencies, and work on across a range of devices. The models are bidirectional recurrent neural networks. This serverless prediction model is a demonstration of edge machine learning that removes the dependence on cloud providers. The code and models are accessible at https://github.com/ur-whitelab/peptide-dashboard.

bioinformatics↗

bioRxiv2022

An integrated cell atlas of the human lung in health and disease

Organ- and body-scale cell atlases have the potential to transform our understanding of human biology. To capture the variability present in the population, these atlases must include diverse demographics such as age and ethnicity from both healthy and diseased individuals. The growth in both size and number of single-cell datasets, combined with recent advances in computational techniques, for the first time makes it possible to generate such comprehensive large-scale atlases through integration of multiple datasets. Here, we present the integrated Human Lung Cell Atlas (HLCA) combining 46 datasets of the human respiratory system into a single atlas spanning over 2.2 million cells from 444 individuals across health and disease. The HLCA contains a consensus re-annotation of published and newly generated datasets, resolving under- or misannotation of 59% of cells in the original datasets. The HLCA enables recovery of rare cell types, provides consensus marker genes for each cell type, and uncovers gene modules associated with demographic covariates and anatomical location within the respiratory system. To facilitate the use of the HLCA as a reference for single-cell lung research and allow rapid analysis of new data, we provide an interactive web portal to project datasets onto the HLCA. Finally, we demonstrate the value of the HLCA reference for interpreting disease-associated changes. Thus, the HLCA outlines a roadmap for the development and use of organ-scale cell atlases within the Human Cell Atlas.

cell biology↗

bioRxiv2022

Characterization of alveolar epithelial lineage heterogeneity during the late pseudoglandular stage of mouse lung development

The specification, characterization, and fate of alveolar type 1 and type 2 (AT1 and 2) progenitors during embryonic lung development remains mostly elusive. In this paper, we build upon our previously published work on the regulation of airway epithelial progenitors by fibroblast growth factor receptor 2b (Fgfr2b) signalling during early (E12.5) and mid (E14.5) pseudoglandular lung development. Here, we looked at the regulation by Fgfr2b signalling on alveolar progenitors during late pseudoglandular/early canalicular (E14.5-E16.5) development. Using a dominant negative mouse model to conditionally inhibit Fgfr2b ligands at E16.5, we used gene array analyses to characterize a set of potential direct targets of Fgfr2b signalling. By mining published single-cell RNA sequence (scRNAseq) datasets, we showed that these Fgfr2b signature genes narrow on a discreet subset of AT2 cells at E17.5 and in adult lungs. Furthermore, we demonstrated that Fgfr2b signalling is lost in AT2 cells in their transition to AT1 cells during repair after injury. We also used CreERT2-based mouse models to conditionally knock-out the Fgfr2b gene in AT2 and in AT1 progenitors, as well as lineage label these cells. We found, using immunofluorescence, that in wildtype controls AT1 progenitors labeled at E14.5-E15.5 contribute a significant proportion to AT2 cells at E18.5; while AT2 progenitors labeled at the same time contribute significantly to the AT1 lineage. We show, using immunofluorescence and FACS-based analysis, that knocking out of Fgfr2b at E14.5-E15.5 in AT2 progenitors leads to an increase in lineage-labeled AT1 cells at E18.5; while the reverse is true in AT1 progenitors. Furthermore, we demonstrate that increased Fgfr signalling in AT2 progenitors reduces their contribution to the AT1 pool. Taken together, our results suggest that a significant proportion of AT2 and AT1 progenitors are cross-lineage committed during late pseudoglandular development, and that lineage commitment is regulated in part by Fgfr2b signalling. We have characterized a set of direct Fgfr2b targets at E16.5 which are likely involved in alveolar lineage formation. These signature genes concentrate on a subpopulation of AT2 cells later in development, and are downregulated in AT2 cells transitioning to the AT1 lineage during repair after injury in adults. Our findings highlight the extensive heterogeneity of alveolar cells by elucidating the role of Fgfr2b signalling in these cells during early alveolar lineage formation, as well as during repair after injury.

developmental biology↗

bioRxiv2021

Single cell RNA Sequencing Identifies G-protein Coupled Receptor 87 as a Novel Basal Cell Marker of Distal Honeycomb Cysts in Idiopathic Pulmonary Fibrosis

Idiopathic Pulmonary Fibrosis (IPF) is a progressive and fatal lung disease with limited therapeutic options. Epithelial reprogramming and honeycomb cysts are key pathological features of IPF, however, the IPF distal bronchiole cell subtypes and their potential contribution to IPF development and progression still remain poorly characterized. Here, we utilized single-cell RNA sequencing on enriched EpCAM+ cells of the distal IPF and Donor lung. Using the 10x Genomics platform, we generated a dataset of 47,881 cells and found distinct cell clusters, including rare cell types, such as suprabasal cells recently reported in the healthy lung. We identified G-protein coupled receptor (GPR) 87 as a novel surface marker of distal Keratin (KRT)5+ basal cells. GPR87 expression was localized to distal bronchioles and honeycomb cysts in IPF in situ by RNA Scope and immunolabeling. Modulation of GPR87 in primary human bronchial epithelial cells cultures resulted in impaired airway differentiation and ciliogenesis. Thus, GPR87 is a novel marker and potentially druggable target of KRT5+ basal progenitor cells likely contributing to bronchiole remodeling and honeycomb cyst development in IPF.

cell biology↗

bioRxiv2021

A transcriptomics-guided drug target discovery strategy identifies novel receptor ligands for lung regeneration

Currently, there is no pharmacological treatment targeting defective tissue repair in chronic disease. Here we utilized a transcriptomics-guided drug target discovery strategy using gene signatures of smoking-associated chronic obstructive pulmonary disease (COPD) and from mice chronically exposed to cigarette smoke, identifying druggable targets expressed in alveolar epithelial progenitors of which we screened the function in lung organoids. We found several drug targets with regenerative potential of which EP and IP prostanoid receptor ligands had the most significant therapeutic potential in restoring cigarette smoke-induced defects in alveolar epithelial progenitors in vitro and in vivo. Mechanistically, we discovered by using scRNA-sequencing analysis that circadian clock and cell cycle/apoptosis signaling pathways were enriched in alveolar epithelial progenitor cells in COPD patients and in a relevant model of COPD, which was prevented by PGE2 or PGI2 mimetics. Conclusively, specific targeting of EP and IP receptors offers therapeutic potential for injury to repair in COPD.

pharmacology and toxicology↗

bioRxiv2021

Single cell trajectory analysis of human pluripotent stem cells differentiating towards lung and hepatocyte progenitors

Understanding the development of human respiratory tissues is crucial for modeling and treating lung disorders. The molecular details for the specification of lung progenitors from human pluripotent stem cells (hPSCs) are unclear. Here, we use single cell RNA-sequencing with high temporal resolution along an optimized differentiation protocol to determine the transcriptional hierarchy of lung specification from human hPSCs and map out the underlying single cell trajectories. We show that Sonic hedgehog, TGF-{beta} and Notch activation are required in an ISL1/NKX2-1 trajectory that gives rise to lung progenitors during the foregut endoderm stage. Induction of HHEX marks an alternative trajectory at the early definitive endoderm stage, which precedes the lung trajectory and generates a major hepatoblast population. Moreover, neither KDR+ nor mesendoderm progenitors are apparent intermediate states of lung and hepatic lineages. Our hierarchical multistep model predicts mechanisms leading to lung organogenesis, and creates a basis for studying early human lung development, as well as hPSC based disease and drug research. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/432413v2_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@12143b7org.highwire.dtl.DTLVardef@e4aa1dorg.highwire.dtl.DTLVardef@5c5766org.highwire.dtl.DTLVardef@6e2432_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2020

CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell-state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for mapping the fate of single cells in diverse scenarios, including perturbations such as regeneration or disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, derived from ratios of spliced to unspliced reads. CellRank takes into account both the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in RNA velocity vectors. On data from pancreas development, we show that it automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. CellRank also predicts a novel dedifferentiation trajectory during regeneration after lung injury, which we follow up experimentally by confirming the existence of previously unknown intermediate cell states.

bioinformatics↗