Biology subjects

Veltri, A.

Publications and source records attributed to Veltri, A..

4 recordsLinked to original sources

bioRxiv2026

Single-cell Transcriptomic Variance Analysis Reveals Intercellular Circadian Desynchrony in the Alzheimer's Affected Human Brain

Bulk tissue rhythms arise from the coordination of thousands of individual cellular oscillations. Bulk rhythm amplitude differences may reflect changes in the amplitude of the underlying cellular oscillators or changes in their temporal coherence. To resolve this fundamental ambiguity, we developed ORPHEUS (Oscillatory Rhythm Phase Heterogeneity Estimated Using Statistical-moments), an analytical method that quantifies cellular desynchrony by leveraging the unique 12hr rhythmic signature it imparts on intercellular expression variance. After validating ORPHEUS in silico and on data from the mouse suprachiasmatic nucleus (SCN), we applied it to data from the mouse liver and human brain to uncover disease- and pathway-related differences in intercellular synchrony. In both tissues, we found that circadian synchrony is higher in cells and samples with higher MTORC activity. Most critically, we observed a dramatic loss of cellular synchrony in excitatory neurons from subjects with Alzheimers Disease (AD) dementia. By decoupling the influence of cellular amplitude and synchrony, ORPHEUS introduces a new, interpretable tool for analyzing circadian coordination in time-course single-cell data.

bioinformatics↗

bioRxiv2025

Vcam1 in endothelial and stromal cells regulates hematopoietic stem cell contact with the niche

Hematopoietic stem and progenitor cells (HSPCs) are essential for differentiation into all blood cell types. In mammals, the interaction between HSPCs and the fetal liver niche during development is critical for stem cell maturation. Integrin alpha 4 (Itga4) on HSPCs and vascular cell adhesion molecule (Vcam1) on niche cells are critical for HSPC colonization of the fetal liver (FL). Itga4 and Vcam1 also function in the zebrafish equivalent of the FL, the caudal hematopoietic tissue (CHT), however, the specific niche cells that express Vcam1 remain unclear. Using multiple approaches, including fluorescent in situ hybridization, we found Vcam1 is expressed in endothelial cells (ECs) and mesenchymal stromal cells (MSCs), but not macrophages. Time-lapse live imaging of itga4 mutants showed the Itga4-Vcam1 axis is required for HSPC retention in the CHT niche, but not homing or lodgment. Our results show that Itga4 on HSPCs and Vcam1 on ECs and MSCs are involved in retention in the CHT niche. SummaryBlood stem cell interaction with the niche microenvironment during development is critical for establishing a robust stem cell pool into adulthood. This study determines the niche cell types that present Vcam1 in the embryo and allow interaction with blood stem cells.

developmental biology↗

bioRxiv2025

Single-cell RNA sequencing of murine liver reveals an aligned circadian clock and cell-population specific circadian regulated pathways

The circadian clock is tightly connected to metabolism, which is evident in various metabolic processes performed by the liver. Perturbation of these processes due to circadian dysregulation leads to liver specific pathology. The liver is composed of multiple different cell populations each with distinct functions contributing to organ homeostasis, but individual cell population contributions to circadian clock function is not yet known. Single-cell RNA sequencing provides the opportunity to understand clock function and oscillating gene expression within an organ system at the individual cell population level that would allow for better understanding of the crosstalk between the circadian clock and metabolic pathways within the liver. In the past, barriers to achieving this goal included complexity associated with generating single-cell RNA sequencing time series data as well as the complexity of data analysis. Here, we established a protocol that enabled the generation of murine liver cell population time series data, as well as a methodological approach to evaluate the core molecular clock and oscillating gene expression in individual cell populations. Using a combination of normalized coefficient of variation, clock-correlation and aggregate pseudobulk, we found a robust and aligned circadian clock in each of the cell populations. We then employed a pseudoreplicate / pseudobulk strategy to identify oscillating gene expression and benchmarked against bulk RNA sequencing data; we demonstrated that many metabolic genes were oscillating in several of the cell populations, including non-hepatocyte clusters. Finally, we identified oscillating genes unique to specific cell populations that play critical roles in liver function. The findings in this study lay an important foundation for understanding clock function and contributions of oscillating gene function at the individual cell population level in liver.

molecular biology↗

bioRxiv2022

Genomic and transcriptional profiling stratifies VQ myeloma lines into two clusters with distinct risk signatures and drug responses

Multiple myeloma (MM) is a cancer of malignant plasma cells in the bone marrow and extramedullary sites. We previously characterized a VQ model for human high-risk MM. Different VQ lines display distinct disease phenotypes and survivals, suggesting significant intra-model variation. Here, we use whole exome sequencing and copy number variation (CNV) analysis coupled with RNA-Seq to stratify VQ lines into corresponding clusters: Cluster I VQ cells carried recurrent amplification of chromosome (chr) 3 and displayed upregulation of growth pathways and high-risk myeloma gene signatures, whereas Cluster II cells had monosomy chr5 and overexpressed genes and pathways associated with positive response to bortezomib (Btz) treatment in human MM patients. Consistently, in sharp contrast to Cluster II VQ cells that showed short-term response to Btz, Cluster I VQ cells were de novo resistant to Btz in vivo. Our study highlights Cluster I VQ lines as highly representative of human high-risk MM subset.

cancer biology↗