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Biology subjects

Josephides, J. M.

Publications and source records attributed to Josephides, J. M..

3 recordsLinked to original sources

Alzheimer's disease causes bone marrow myelopoiesis dysfunction

Accumulating evidence suggests that both innate and adaptive immunity play crucial roles in combating Alzheimers disease (AD). Specifically, enhancing the homing of monocyte-derived macrophages to the affected brain has been shown to reduce local inflammation, decrease proteinopathy, rescue neurons, and mitigate cognitive decline. However, the factors limiting their spontaneous recruitment remain unclear. Using multi-omics techniques, we identified impaired myelopoiesis and monocyte development in both mice and AD patients. While not the primary cause of the disease, this impairment is associated with disease progression. In the 5xFAD mouse model, monocyte differentiation was found to be disrupted due to a maladaptive bone marrow (BM) response, driven by type I interferon (IFN-I) signaling. A similar phenotype was found in circulating monocytes from AD patients compared to healthy controls. Blocking IFN-I with monoclonal antibodies or using chimeric AD mice with BM from mice lacking the IFN-I receptor (IFNAR1) alleviated myelopoiesis dysfunction, normalized monocyte phenotypes, and reduced cognitive impairment. These improvements in myeloid function were accompanied by an increased homing of monocyte-derived macrophages in the AD brain. Our results reveal an unexpected dysfunction in BM myelopoiesis in the context of neurodegeneration and support the emerging concept that neurodegenerative diseases are not solely brain-centric.

neuroscience↗

MmM: a machine learning approach to detect replication states and genomic subpop-ulations for single-cell DNA replication timing disentanglement

We introduce MnM, an efficient tool for characterising single-cell DNA replication states and revealing genomic subpopulations in heterogeneous samples, notably cancers. MnM uses single-cell copy-number data to accurately perform missing-value imputation, classify cell replication states and detect genomic heterogeneity, which allows to separate somatic copy-number alterations from copy-number variations due to DNA replication. By applying our machine learning methods, our research unveils critical insights into chromosomal aberrations and showcases ubiquitous aneuploidy in tumorigenesis. MnM democratises single-cell subpopulation detection which, in hand, enables the extraction of single-cell DNA replication timing (scRT) profiles from genomically-heterogenous subpopulations detected by DNA content and issued from single samples. By analysing over 119,000 human single cells from cultured cell lines, patient tumours as well as patient-derived xenograft samples, the copy-number and replication timing profiles issued in this study lead to the first multi-sample subpopulation-disentangled scRT atlas and act as data contribution for further cancer research. Our results highlight the necessity of studying in vivo samples to comprehensively grasp the complexities of DNA replication, given that cell lines, while convenient, lack dynamic environmental factors. This tool offers to advance our understanding of cancer initiation and progression, facilitating further research in the interface of genomic instability and replication stress. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/573369v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@25047forg.highwire.dtl.DTLVardef@4a57faorg.highwire.dtl.DTLVardef@d61dd5org.highwire.dtl.DTLVardef@140c6e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Kronos scRT: a uniform framework for single-cell replication timing analysis

Mammalian genomes are replicated in a cell-type specific order and in coordination with transcription and chromatin organization. Although the field of replication is also entering the single-cell era, current studies require cell sorting, individual cell processing and have yielded a limited number (<100) of cells. Here, we have developed Kronos scRT (https://github.com/CL-CHEN-Lab/Kronos_scRT), a software for single-cell Replication Timing (scRT) analysis. Kronos scRT does not require a specific platform nor cell sorting, allowing the investigation of large datasets obtained from asynchronous cells. Analysis of published available data and droplet-based scWGS data generated in the current study, allows exploitation of scRT data from thousands of cells for different mouse and human cell lines. Our results demonstrate that, although most cells replicate within a close timing range for a given genomic region, replication can also occur stochastically throughout S phase. Altogether, Kronos scRT allows investigating the RT program at a single-cell resolution for both homogeneous and heterogeneous cell populations in a fast and comprehensive manner.

genomics↗