Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single cell resolution
Abstract
Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single cell RNA sequencing (scRNAseq) to characterize an enriched population of human hematopoietic stem and progenitor cells (HSPCs) obtained from young and elderly healthy individuals. Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain age-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and gene regulatory networks (GRN) regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2 and RUNX1 suggesting a role of these TF in the pathogenesis of the disease. In summary, we demonstrate that the combination of single cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in complex biological systems such as early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with perturbations such as aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.
Data availability
All the single cell RNA sequencing data is available at Gene Expression Omnibus under accession number GSE180298. The scripts needed to replicate the analysis are deposited on GitHub:https://github.com/mainciburu/scRNA-Hematopoiesis
-
Single-cell, multi-omic analysis identifies regulatory programs in mixed phenotype acute leukemiaNCBI Gene Expression Omnibus, GSE139369.
Article and author information
Author details
Funding
Instituto de Salud Carlos III
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Ministerio de Ciencia e Innovación (PhD fellowship FPU18/05488)
- Marina Ainciburu
Fundación Científica Asociación Española Contra el Cáncer (Investigador AECC award)
- Teresa Ezponda
H2020 Marie Skłodowska-Curie Actions (Grant Agreement No. 898356)
- Mikel Hernaez
Federación Española de Enfermedades Raras (PI17/00701,PI19/00726 and PI20/01308)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Centro de Investigación Biomédica en Red de Cáncer (CB16/12/00489 and CB16/12/00225)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Gobierno de Navarra (ERAPerMed MEET-AML 0011-2750-2019-000001; AGATA 0011-1411-2020-000010/0011-1411-2020-000011 and DIAN)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
la Caixa" Foundation " (GR-NET NORMAL-HIT HR20-00871)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Cancer Research UK (C355/A26819)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Fundación Científica Asociación Española Contra el Cáncer (Accelerator Award Program)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Associazione Italiana per la Ricerca sul Cancro (Accelerator Award Program)
- Marina Ainciburu
- Teresa Ezponda
- Nerea Berastegui
- Ana Alfonso-Pierola
- Amaia Vilas-Zornoza
- Patxi San Martin-Uriz
- Diego Alignani
- Jose Lamo de Espinosa
- Mikel San Julian
- Tamara Jiménez Solas
- Felix Lopez
- Sandra Muntion
- Fermin Sanchez-Guijo
- Antonieta Molero
- Julia Montoro
- Guillermo Serrano
- Aintzane Diaz-Mazkiaran
- Miren Lasaga
- David Gomez-Cabrero
- Maria Diez-Campelo
- David Valcarcel
- Mikel Hernaez
- Juan Pablo Romero
- Felipe Prosper
Gobierno de Navarra (PhD fellowship 0011-0537-2019-000001)
- Nerea Berastegui
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The samples and data from the patients included in the study were provided by the Biobank of the University of Navarra and were processed according to standard operating procedures. Patients and healthy donors provided informed consent, together with consent for publication. The study was approved by the Clinical Research Ethics Committee of the Clinica Universidad de Navarra, following protocol # 2017.218.
Copyright
© 2023, Ainciburu et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,039
- views
-
- 563
- downloads
-
- 25
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
- Neuroscience
Audiovisual information reaches the brain via both sustained and transient input channels, representing signals’ intensity over time or changes thereof, respectively. To date, it is unclear to what extent transient and sustained input channels contribute to the combined percept obtained through multisensory integration. Based on the results of two novel psychophysical experiments, here we demonstrate the importance of the transient (instead of the sustained) channel for the integration of audiovisual signals. To account for the present results, we developed a biologically inspired, general-purpose model for multisensory integration, the multisensory correlation detectors, which combines correlated input from unimodal transient channels. Besides accounting for the results of our psychophysical experiments, this model could quantitatively replicate several recent findings in multisensory research, as tested against a large collection of published datasets. In particular, the model could simultaneously account for the perceived timing of audiovisual events, multisensory facilitation in detection tasks, causality judgments, and optimal integration. This study demonstrates that several phenomena in multisensory research that were previously considered unrelated, all stem from the integration of correlated input from unimodal transient channels.
-
- Cell Biology
- Computational and Systems Biology
Induced pluripotent stem cell (iPSC) technology is revolutionizing cell biology. However, the variability between individual iPSC lines and the lack of efficient technology to comprehensively characterize iPSC-derived cell types hinder its adoption in routine preclinical screening settings. To facilitate the validation of iPSC-derived cell culture composition, we have implemented an imaging assay based on cell painting and convolutional neural networks to recognize cell types in dense and mixed cultures with high fidelity. We have benchmarked our approach using pure and mixed cultures of neuroblastoma and astrocytoma cell lines and attained a classification accuracy above 96%. Through iterative data erosion, we found that inputs containing the nuclear region of interest and its close environment, allow achieving equally high classification accuracy as inputs containing the whole cell for semi-confluent cultures and preserved prediction accuracy even in very dense cultures. We then applied this regionally restricted cell profiling approach to evaluate the differentiation status of iPSC-derived neural cultures, by determining the ratio of postmitotic neurons and neural progenitors. We found that the cell-based prediction significantly outperformed an approach in which the population-level time in culture was used as a classification criterion (96% vs 86%, respectively). In mixed iPSC-derived neuronal cultures, microglia could be unequivocally discriminated from neurons, regardless of their reactivity state, and a tiered strategy allowed for further distinguishing activated from non-activated cell states, albeit with lower accuracy. Thus, morphological single-cell profiling provides a means to quantify cell composition in complex mixed neural cultures and holds promise for use in the quality control of iPSC-derived cell culture models.