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

Dhapola, Parashar; Eldeeb, Mohamed; Ugale, Amol; Olofzon, Rasmus; Erlandsson, Eva; Soneji, Shamit; Bryder, David; Karlsson, Göran

doi:10.1101/2020.09.30.321216

Cited by 7 publications

(4 citation statements)

References 54 publications

(67 reference statements)

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“…( Supplementary Figure S4A and S4B ). To further understand the cell signature of the differential gene expression from GMP-HL60 uninduced, we subjected gene sets to the CellRadar analysis tool ( Dhapola et al, 2020 ). Interestingly, the NSG set showed a progenitor phenotype, the GMP-specific set showed a stem/progenitor phenotype, and the HL60-specific set gave both progenitor and monocytic phenotypes ( Figure 4C ).…”

Section: Resultsmentioning

confidence: 99%

Molecular and epigenetic alterations in normal and malignant myelopoiesis in human leukemia 60 (HL60) promyelocytic cell line model

Basu

Madhulika²,

Murmu³

et al. 2023

Front. Cell Dev. Biol.

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In vitro cell line model systems are essential in supporting the research community due to their low cost, uniform culturing conditions, homogeneous biological resources, and easy experimental design to study the cause and effect of a gene or a molecule. Human leukemia 60 (HL60) is an in-vitro hematopoietic model system that has been used for decades to study normal myeloid differentiation and leukemia biology. Here, we show that IMDM supplemented with 20% FBS is an optimal culturing condition and induces effective myeloid differentiation compared with RPMI supplemented with 10% FBS when HL60 is induced with 1α,25-dihydroxyvitamin D3 (Vit D3) and all-trans retinoic acid (ATRA). The chromatin organization is compacted, and the repressive epigenetic mark H3K27me3 is enhanced upon HL60-mediated terminal differentiation. Differential gene expression analysis obtained from RNA sequencing in HL60 cells during myeloid differentiation showed the induction of pathways involved in epigenetic regulation, myeloid differentiation, and immune regulation. Using high-throughput transcriptomic data (GSE74246), we show the similarities (genes that did not satisfy |log2FC|>1 and FDR<0.05) and differences (FDR <0.05 and |log2FC|>1) between granulocyte-monocyte progenitor vs HL60 cells, Vit D3 induced monocytes (vMono) in HL60 cells vs primary monocytes (pMono), and HL60 cells vs leukemic blasts at the transcriptomic level. We found striking similarities in biological pathways between these comparisons, suggesting that the HL60 model system can be effectively used for studying myeloid differentiation and leukemic aberrations. The differences obtained could be attributed to the fact that the cellular programs of the leukemic cell line and primary cells are different. We validated several gene expression patterns for different comparisons with CD34+ cells derived from cord blood for myeloid differentiation and AML patients. In addition to the current knowledge, our study further reveals the significance of using HL60 cells as in vitro model system under optimal conditions to understand its potential as normal myeloid differentiation model as well as leukemic model at the molecular level.

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Section: Resultsmentioning

confidence: 99%

Molecular and epigenetic alterations in normal and malignant myelopoiesis in human leukemia 60 (HL60) promyelocytic cell line model

Basu

Madhulika²,

Murmu³

et al. 2023

Front. Cell Dev. Biol.

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“…Generating co-embedding of large datasets can be time consuming when multiple mappings on multiple large datasets are performed. To this end, Scarf provides an additional alternative in the form of mapping scores 41 (see Methods). Here, we demonstrate individually generated mappings for astrocytes and oligodendrocytes, visualized by increasing cell size in proportion to their mapping score (figure 3N-O).…”

Section: Resultsmentioning

confidence: 99%

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

Dhapola

Rodhe

Olofzon

et al. 2021

Preprint

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The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the ability 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 Scarf's 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 has the capacity to 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.

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“…Upstream analysis was done with Qiagen IPA (https://digitalinsights.qiagen.com/IPA). Cell type enrichment was performed with CellRadar 64 .…”

Section: Methodsmentioning

confidence: 99%

IRF1 regulates self-renewal and stress-responsiveness to support hematopoietic stem cell maintenance

Nilsson

Xian

Shalapour

et al. 2023

Preprint

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Inflammatory mediators induce emergency myelopoiesis and cycling of adult hematopoietic stem cells (HSCs) through incompletely understood mechanisms. To suppress the unwanted effects of inflammation and preserve its beneficial outcomes, the mechanisms by which inflammation affects hematopoiesis need to be fully elucidated. Rather than focusing on specific inflammatory stimuli, we here investigated the role of transcription factor Interferon (IFN) regulatory factor 1 (IRF1), which receives input from several inflammatory signaling pathways. We identify IRF1 as a master HSC regulator. IRF1 loss impairs HSC self-renewal, increases stress-induced cell cycle activation, and confers apoptosis resistance. Transcriptomic analysis revealed an aged, inflammatory signature devoid of IFN signaling with reduced megakaryocytic/erythroid priming and antigen presentation in IRF1-deficient HSCs. Finally, we conducted IRF1-based AML patient stratification to identify groups with distinct proliferative, survival and differentiation features, overlapping with our murine HSC results. Our findings position IRF1 as a pivotal regulator of HSC preservation and stress-induced responses.

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

Cited by 7 publications

References 54 publications

Molecular and epigenetic alterations in normal and malignant myelopoiesis in human leukemia 60 (HL60) promyelocytic cell line model

Molecular and epigenetic alterations in normal and malignant myelopoiesis in human leukemia 60 (HL60) promyelocytic cell line model

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

IRF1 regulates self-renewal and stress-responsiveness to support hematopoietic stem cell maintenance

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