Biology subjects

Belderbos, M. E.

Publications and source records attributed to Belderbos, M. E..

3 recordsLinked to original sources

bioRxiv2024

Single-cell multiomics of pediatric BM reveals age-dependent differences in lineage differentiation linked to stromal cell heterogeneity

Childhood is critical for hematopoietic development and the onset of hematologic diseases. To explore hematopoietic changes from infancy through adolescence, we generated a multi-modal single-cell atlas capturing mRNA and surface protein expression of 90.710 bone marrow (BM) cells. This includes hematopoietic stem/progenitor cells and mesenchymal stromal cells, from seven pediatric individuals and two young adults. We demonstrate that young pediatric BM is distinct from adolescents/young adults (AYA), shifting from B-lineage dominance in early childhood to myeloid and T-lineage bias in adolescence. We uncover two distinct lymphoid progenitors (LyPs) subsets regulating this shift: CD127-positive LyPs with B-lineage output, most abundant in early childhood, and CD127-negative LyPs with lymphoid and myeloid features, more common in AYAs. Age-related changes in stromal composition and signaling, mediated by IL-7 and TGF-{beta}1, correspond with this lineage shift. This study provides an in-depth resource for understanding healthy hematologic development and potential early-life perturbations underlying pediatric hematologic diseases.

immunology↗

bioRxiv2023

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole genome sequencing (WGS), but still generate hundreds of artefacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolkit (PTATO), to accurately detect single base substitutions, small insertions and deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90% for base substitution and 95% for indels), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that many hematopoietic stem and progenitor cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS technologies, have normal somatic single base substitution burdens, but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

genomics↗

bioRxiv2022

Parallel clonal and molecular profiling of hematopoietic stem cells using RNA barcoding

Anucleate cells - platelets and erythrocytes - constitute over 95% of all hematopoietic stem cell (HSC) output, but the clonal dynamics of HSC contribution to these lineages remains largely unexplored. Here, we use lentiviral RNA cellular barcoding and transplantation of HSCs, combined with single-cell RNA-seq, for quantitative analysis of clonal behavior with a multi-lineage readout - for the first time including anucleate and nucleate lineages. We demonstrate that most HSCs steadily contribute to hematopoiesis, but acute platelet depletion shifts the output of multipotent HSCs to the exclusive production of platelets, with the additional emergence of new myeloid-biased clones. Our approach therefore enables comprehensive profiling of multi-lineage output and transcriptional heterogeneity of individual HSCs, giving insight into clonal dynamics in both steady state and under physiological stress.

cell biology↗