Biology subjects

Dhapola, P.

Publications and source records attributed to Dhapola, P..

11 recordsLinked to original sources

bioRxiv2025

Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics

Cell type annotation remains a critical bottleneck, with current methods often inaccurate and requiring extensive manual validation, particularly in disease contexts. While large language models (LLMs) show promise, they can be unreliable due to hallucinations. We developed CyteType, a multi-agent framework that generates competing hypotheses grounded in full expression data and study context, validates against external databases, and iteratively self-evaluates. Comprehensive benchmarking demonstrates that CyteType substantially outperforms reference-based and LLM-based methods, with self-generated confidence scores reliably identifying trustworthy annotations. CyteType transforms cell type annotation from label assignment into evidence-grounded biological discovery. Python (AnnData compatible): https://github.com/NygenAnalytics/CyteType R (Seurat compatible): https://github.com/NygenAnalytics/CyteTypeR

bioinformatics↗

bioRxiv2023

CD9 marks myeloid/MegE-biased human hematopoiesis

Rare hematopoietic stem cells make up an infrequent but critical population in the bone marrow (BM), maintaining and replenishing the entire hematopoietic system. Importantly, despite sharing the unique stem cell properties of multilineage differentiation and self-renewal, individual HSCs are functionally heterogeneous, and this heterogeneity increases during aging. While HSCs in young mice are qualitatively more similar, ageing is marked by an increased size of the HSC pool and substantial functional variation of individual HSCs. CD9 is a cell surface marker that is highly expressed in HSCs in mice, while CD9 expression within the human HSC population has been reported to be low during neonatal hematopoiesis. Here, we have investigated CD9 expression levels in the human HSPC population over time and identified that early in life; CD9 is infrequent in HSCs, but marks progenitor populations with low engraftment potential and high proliferation capacity. However, during situations of myeloid/Megakaryocyte-erythoid (MegE) biased hematopoiesis, such as during ageing or in leukemia, there is a substantial increase of CD9 expression in HSPCs. Thus, CD9 represents an HSC marker for myeloid/MegE-biased hematopoiesis.

cell biology↗

bioRxiv2023

Single cell multi-omics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response

The advent of tyrosine kinase inhibitors (TKIs) as treatment of chronic myeloid leukemia (CML) is a paradigm in molecularly targeted cancer therapy. Nonetheless, TKI insensitive leukemia stem cells (LSCs) persist in most patients even after years of treatment. The sustained presence, heterogeneity and evolvability of LSCs are imperative for disease progression as well as recurrence during treatment-free remission (TFR). However, dynamic changes among LSC sub-populations upon TKI therapy impede their measurement and targeting. Here, we used cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to generate high-resolution single cell multiomics maps from CML patients at diagnosis, retrospectively stratified by BCR::ABL1IS (%) following 12 months of TKI therapy as per European LeukemiaNet (ELN) recommendations. Simultaneous measurement of global gene expression profiles together with >40 surface markers from the same cells revealed that each patient harbored a unique composition of stem and progenitor cells at diagnosis demonstrating that cellular heterogeneity is a hallmark of CML. The patients with treatment failure after 12 months of therapy had markedly higher abundance of molecularly defined primitive cells at diagnosis compared to the optimal responders. Furthermore, deconvolution of an independent dataset of CML patient-derived bulk transcriptomes (n=59) into constituent cell populations showed that the proportion of primitive cells versus lineage primed sub-populations significantly connected with the TKI-treatment outcome. The multiomic feature landscape enabled visualization of the primitive fraction as a heterogenous mixture of molecularly distinct Lin-CD34+CD38-/low BCR::ABL1+ LSCs and BCR::ABL1- hematopoietic stem cells (HSCs) in variable ratio across patients and guided their prospective isolation by a combination of CD26 and CD35 cell surface markers. We for the first time show that BCR::ABL1+ LSCs and BCR::ABL1- HSCs can be distinctly separated as CD26+CD35- and CD26-CD35+ respectively. In addition, we found the relative proportion of CD26-CD35+ HSCs to be higher in optimal responders when compared to treatment failures, at diagnosis as well as following 3 months of TKI therapy, and that the LSC/HSC ratio was increased in patients with prospective treatment failure. Collectively, the patient-specific cellular heterogeneity multiomics maps build a framework towards understanding therapy response and adapting treatment by devising strategies that either extinguish TKI-insensitive LSCs or engage the immune effectors to suppress the residual leukemogenic cells.

cancer biology↗

bioRxiv2023

Tracking Early Mammalian Organogenesis - Prediction and Validation of Differentiation Trajectories at Whole Organism Scale

Early organogenesis represents a key step in animal development, where pluripotent cells divide and diversify to initiate formation of all major organs. Here, we used scRNA-Seq to profile over 300,000 single cell transcriptomes sampled in 6 hour intervals from mouse embryos between E8.5 and E9.5. Combining this dataset with our previous E6.5 to E8.5 atlas resulted in a densely sampled time course of over 400,000 cells from early gastrulation to organogenesis. Computational lineage reconstruction at full organismal scale identified complex waves of blood and endothelial development, including a new molecular programme for somite-derived endothelium. To assess developmental fates across the primitive streak, we dissected the E7.5 primitive streak into four adjacent regions, performed scRNA- Seq and predicted cell fates computationally. We next defined early developmental state/fate relationships experimentally by a combination of orthotopic grafting, microscopic analysis of graft contribution as well as scRNA-Seq to transcriptionally determine cell fates of the grafted primitive streak regions after 24h of in vitro embryo culture. Experimentally determined fate outcomes were in good agreement with the fates predicted computationally, thus demonstrating how classical grafting experiments can be revisited to establish high-resolution cell state/fate relationships. Such interdisciplinary approaches will benefit future studies in both developmental biology as well as guide the in vitro production of cells for organ regeneration and repair.

developmental biology↗

bioRxiv2021

A Combined Immunophenotypic And Transcriptional Single-Cell Map Of First Trimester Human Fetal Liver Hematopoiesis

Knowledge of human fetal blood development and how it differs from adult is highly relevant for our understanding of congenital blood and immune disorders as well as childhood leukemia, the latter known to originate in utero. Blood production during development occurs in waves that overlap in time and space adding to heterogeneity, which necessitates single cell approaches. Here, a combined single cell immunophenotypic and transcriptional map of first trimester primitive blood development is presented. Using CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) the molecular profile of established immunophenotypic gated progenitors was analyzed in the fetal liver (FL). Classical markers for hematopoietic stem cells (HSCs) such as CD90 and CD49F were largely preserved, whereas CD135 (FLT3) and CD123 (IL3R) had a ubiquitous expression pattern capturing heterogenous populations. Direct molecular comparison with an adult bone marrow (BM) data set revealed that HSC-like cells were less frequent in FL, whereas cells with a lympho-myeloid signature were more abundant. Furthermore, an erythro-myeloid primed multipotent progenitor cluster was identified, potentially representing a transient, FL-specific progenitor. Based on the projection performed, up- and downregulated genes between fetal and adult cells were analyzed. In general, cell cycle pathways, including MYC targets were shown to be upregulated in fetal cells, whereas gene sets involved in inflammation and human leukocyte antigen (HLA) complex were downregulated. Importantly, a fetal core molecular signature was identified that could discriminate certain types of infant and childhood leukemia from adult counterparts. Our detailed single cell map presented herein emphasizes molecular as well as immunophenotypic differences between fetal and adult primitive blood cells, of significance for future studies of pediatric leukemia and blood development in general.

developmental biology↗

bioRxiv2021

Scarf: A toolkit for memory efficient analysis of large-scale single-cell genomics data

The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the computational requirements to efficiently handle growing datasets. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for memory-efficient single-cell analysis of millions of cells on a laptop or low-cost devices like single board computers. We demonstrate Scarfs memory and compute-time efficiency by applying it to the largest existing single-cell RNA-Seq and ATAC-Seq datasets. Scarf wraps memory-efficient implementations of a graph-based t-stochastic neighbour embedding and hierarchical clustering algorithm. Moreover, Scarf performs accurate reference-anchored mapping of datasets while maintaining memory efficiency. By implementing a novel data downsampling algorithm, Scarf additionally can generate representative sampling of cells from a given dataset wherein rare cell populations and lineage differentiation trajectories are conserved. Together, Scarf provides a framework wherein any researcher can perform advanced processing, downsampling, reanalysis, and integration of atlas-scale datasets on standard laptop computers.

bioinformatics↗

bioRxiv2021

Single-Cell Multiomics Reveals Distinct Cell States at the Top of Human Hematopoietic Hierarchy

The advent of single cell (Sc) genomics has challenged the dogma of haematopoiesis as a tree-like structure of stepwise lineage commitment through distinct and increasingly restricted progenitor populations. Instead, analysis of ScRNA-seq has proposed that the earliest events in human hematopoietic stem cell (HSC) differentiation are characterized by only subtle molecular changes, with hematopoietic stem and progenitor cells (HSPCs) existing as a continuum of low-primed cell-states that gradually transition into a specific lineage (CLOUD-HSPCs). Here, we combine ScRNA-seq, ScATAC-seq and cell surface proteomics to dissect the heterogeneity of CLOUD-HSPCs at different stages of human life. Within CLOUD-HSPCs, pseudotime ordering of both mRNA and chromatin data revealed a bifurcation of megakaryocyte/erythroid and lympho/myeloid trajectories immediately downstream a subpopulation with an HSC-specific enhancer signature. Importantly, both HSCs and lineage-restricted progenitor populations could be prospectively isolated based on correlation of their molecular signatures with CD35 and CD11A expression, respectively. Moreover, we describe the changes that occur in this heterogeneity as hematopoiesis develops from neonatal to aged bone marrow, including an increase of HSCs and depletion of lympho-myeloid biased MPPs. Thus, this study dissects the heterogeneity of human CLOUD-HSPCs revealing distinct HSPC-states of relevance in homeostatic settings such as ageing.

cell biology↗

bioRxiv2021

Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood

Understanding how hematopoietic stem and progenitor cells (HSPCs) are regulated is of central importance for the development of new therapies for blood disorders and stem cell transplantation. To date, HSPC regulation has been extensively studied in vitro and in animal models, but less is known about the mechanisms in vivo in humans. Here, in a genome-wide association study on 13,167 individuals, we identify 9 significant and 2 suggestive DNA sequence variants that influence HSPC (CD34+) levels in human blood. The identified loci associate with blood disorders, harbor known and novel HSPC genes, and affect gene expression in HSPCs. Interestingly, our strongest association maps to the PPM1H gene, encoding an evolutionarily conserved serine/threonine phosphatase never previously implicated in stem cell biology. PPM1H is expressed in HSPCs, and the allele that confers higher blood CD34+ cell levels downregulates PPM1H. By functional fine-mapping, we find that this downregulation is caused by the variant rs772557-A, which abrogates a MYB transcription factor binding site in PPM1H intron 1 that is active in specific HSPC subpopulations, including hematopoietic stem cells, and interacts with the promoter by chromatin looping. Furthermore, rs772557-A selectively increases HSPC subpopulations in which the MYB site is active, and PPM1H shRNA- knockdown increased CD34+ and CD34+90+ cell proportions in umbilical cord blood cultures. Our findings represent the first large-scale association study on a stem cell trait, illuminating HSPC regulation in vivo in humans, and identifying PPM1H as a novel inhibition target that can potentially be utilized clinically to facilitate stem cell harvesting for transplantation.

genomics↗

bioRxiv2020

Nabo - a framework to define leukemia-initiating cells and differentiation in single-cell RNA-sequencing data

Single-cell transcriptomics facilitates innovative approaches to define and identify cell types within tissues and cell populations. An emerging interest in the cancer field is to assess the heterogeneity of transformed cells, including the identification of tumor-initiating cells based on similarities to their normal counterparts. However, such cell mapping is often confounded by the large effects on total gene expression programs introduced by strong perturbations such as an oncogenic event. Here, we present Nabo, a novel computational method that allows mapping of cells from one population to the most similar cells in a reference population, independently of confounding changes to gene expression programs initiated by perturbation. We validated this method on multiple datasets from different sources and platforms and show that Nabo achieves higher rates of accuracy than conventional classification methods. Nabo is available as an integrated toolkit for preprocessing, cell mapping, differential gene expression identification, and visualization of single-cell RNA-Seq data. For exploratory studies, Nabo includes methods to help evaluate the reliability of cell mapping results. We applied Nabo on droplet-based single-cell RNA-Seq data of healthy and oncogene-induced (MLL-ENL) hematopoietic progenitor cells (GMLPs) differentiating in vitro. Despite a substantial cellular heterogeneity resulting from differentiation of GMLPs and the large transcriptional effects induced by the fusion oncogene, Nabo could pinpoint the specific cell stage where differentiation arrest occurs, which included an immunophenotypic definition of the tumor-initiating population. Thus, Nabo allows for relevant comparison between target and control cells, without being confounded by differences in population heterogeneity.

bioinformatics↗

bioRxiv2020

Concurrent stem- and lineage-affiliated chromatin programs precede hematopoietic lineage restriction

The emerging notion of hematopoietic stem- and progenitor cells (HSPCs) as a low-primed cloud without sharply demarcated gene expression programs raises the question on how cellular fate options emerge, and at which stem-like stage lineage priming is initiated. Here we investigated single-cell chromatin accessibility of Lineage-, cKit+, Sca1+ (LSK) HSPCs spanning the early differentiation landscape. Application of a signal-processing algorithm to detect transition points corresponding to massive alterations in accessibility of 571 transcription factor-motifs revealed a population of LSK FMS-like tyrosine kinase 3(Flt3)intCD9high cells that concurrently display stem-like and lineage-affiliated chromatin signatures pointing to a simultaneous gain of both Lympho-Myeloid and Megakaryocyte-Erythroid programs. Molecularly and functionally, these cells position between stem cells and committed progenitors, display multi-lineage capacity in vitro and in vivo, but lack self-renewal activity. This integrative molecular analysis resolves the heterogeneity of cells along hematopoietic differentiation and permits investigation of chromatin-mediated transition between multipotency and lineage restriction.

cell biology↗

bioRxiv2017

Transcriptomic Dynamics of a non-coding trinucleotide repeat expansion disorder SCA12 in iPSC derived neuronal cells: signatures of interferon induced response

Spinocerebellar ataxia type-12 (SCA12) is a neurological disorder that exhibits a unique progressive tremor/ataxia syndrome induced by triplet (CAG) repeat expansion in 5 UTR of PPP2R2B. SCA12 is one of the most prominent SCA-subtype in India and till date no appropriate disease models have been described. Our aim was to establish human iPSC derived neuronal cell lines of SCA12 and study transcriptomic level alterations induced by CAG expansion. For translational application, peripheral blood transcriptomics of SCA12 patients was also performed. Lymphoblastoid cell lines of three SCA12 patients were reprogrammed to iPSCs and then re-differentiated into pan-neuronal lineage. RNA-sequencing based comparative transcriptomics was performed for disease and control cell lineages. Microarray based transcriptomic profiling of peripheral blood of SCA12 patients was performed in a case/control (n=15/9) design. We have successfully created human neuronal cell lines of SCA12 patient as exhibited by their molecular profiling. Differential expression analysis of RNA-Seq data has shown enrichment for type-I interferon signaling and other relevant cellular processes in SCA12-neurons. At the splice-isoform level, we observed an upregulation of expanded CAG containing non-coding transcript of PPP2R2B. Peripheral blood transcriptomics analysis and targeted validation of RNA-Seq data has allowed us to identify inflammatory signatures as potential markers of molecular pathology in SCA12. Our study has allowed us to establish first iPSC based neuronal cell lines of SCA12. We have identified pro-inflammatory signatures in SCA12-neurons suggestive of a dsRNA mediated activation of interferon signaling and that corroborates with the emerging evidence of neuronal atrophy due to neuro-inflammation in common neurodegenerative diseases. This study involved development of an iPSCs derived neuronal cells of SCA12 and look through signatures of neurodegeneration by whole RNA sequencing. This model sheds light upon key role of RNA mediated induced response in Interferon signaling for neurodegeneration.

molecular biology↗