Biology subjects

Rudich, A.

Publications and source records attributed to Rudich, A..

5 recordsLinked to original sources

bioRxiv2025

Mid-aged mice rapidly normalize dysglycemia but aggravate obesity-induced hypothalamic and microglial changes upon dietary obesity reversal

ObjectiveObesity-induced-dysglycemia and hypothalamic-microgliosis coincide, but whether they remain linked upon obesity reversal, and what is the effect of age, remain unclear. Here we hypothesized that rapid normalization of dysglycemia upon obesity-reversal remains linked to microgliosis resolution, but differs between young and mid-aged mice. MethodsYoung (7w) and mid-aged (1y) mice were fed normal chow (NC) or high-fat diet (HFD,8w), then switched to NC (Rev,2w). ResultsCompared to young mice, NC-fed mid-aged mice were heavier and weight-stable, gained weight with HFD comparably, and lost less weight in Rev. HFD-induced dysglycemia was less severe in mid-aged compared to young mice, but similarly normalized by obesity-reversal. However, whole-hypothalamus RNA sequencing revealed 2,419 differentially expressed genes (DEGs) in mid-aged mice, [~]4-times more than in young mice, and in both age-groups [~]80% of DEGs obesity-induced changes were aggravated in Rev. Furthermore, compared with young mice, middle-aged mice showed greater obesity-induced microglial cyto-morphological changes in the arcuate nucleus (ARC), which associated with increased p-NF{kappa}B-(p-p65) nuclear staining. Only in middle-aged mice obesity-induced microglial changes were aggravated by obesity reversal, with cell volume correlating (Rho({rho})=0.691, p=0.001) with adipose tissue crown-like-structures. ConclusionsIn conclusion, rapid dysglycemia normalization is uncoupled to the resolution of hypothalamic microgliosis, more-so in mid-age.

cell biology↗

bioRxiv2025

Regulation of hematopoietic stem cell (HSC) proliferation by Epithelial Growth Factor Like-7 (EGFL7)

Understanding the pathways regulating normal and malignant hematopoietic stem cell (HSC) biology is important for improving outcomes for patients with hematologic disorders. Epithelial Growth Factor Like-7 (EGFL7) is [~]30 kDa secreted protein that is highly expressed in adult HSCs. Using Egfl7 genetic knock-out (Egfl7 KO) mice and recombinant EGFL7 (rEGFL7) protein, we examined the role of Egfl7 in regulating normal hematopoiesis. We found that Egfl7 KO mice had decreases in overall BM cellularity resulting in significant reduction in the number of hematopoietic stem and progenitor cells (HSPCs), which was due to dysregulation of normal cell-cycle progression along with a corresponding increase in quiescence. rEGFL7 treatment rescued our observed hematopoietic defects of Egfl7 KO mice and enhanced HSC expansion after genotoxic stress such as 5-FU and irradiation. Furthermore, treatment of WT mice with recombinant EGFL7 (rEGFL7) protein expands functional HSCs evidenced by an increase in transplantation potential. Overall, our data demonstrates a role for EGFL7 in HSC expansion and survival and represents a potential strategy for improving transplant engraftment or recovering bone marrow function after stress.

cell biology↗

bioRxiv2023

Cellular taxonomy of the preleukemic bone marrow niche of acute myeloid leukemia

Mutations in hematopoietic stem/progenitor cells (HSPCs) can remain dormant within the bone marrow (BM) for decades before leukemia onset. Understanding the mechanisms by which these mutant clones eventually slead to full blown leukemia is of critical importance to develop strategies to eliminate these clones before they achieve their full leukemogenic potential. Recent data suggest that leukemic stem cells (LSCs) induce alterations within BM microenvironment (BMM) favoring LSC growth over normal HSCs. However, the cross talk between preleukemic stem cells (pLSC) and BMM is not completely understood. We hypothesize that pLSC induces critical changes within the BMM that are critical for leukemogenesis. To address this question, we are using our previously developed murine model of AML that highly recapitulates the human disease, develops AML sporadically with a preleukemic phase in which mice display normal white blood counts (WBCs) and absence of blasts in the BM. Thus, this is an excellent model to evaluate changes in the BMM that occurs during progression into AML. Using this model we performed single cell RNA-sequencing on cells from the BMM compared to wild-type (WT) controls. Overall, we defined the transcriptional profiles of pre-leukemic BMM cells and observed decreased percentages of normal BMM cells such as LepR+ mesenchymal stem cells (MSCs) and endothelial cells (ECs), known to regulate normal HSC function. Concomitantly, we found increases in CD55+ fibroblasts and NG2+ pericytes, that might play a more important role in regulation of pre-LSCs. Preleukemic CD55+ fibroblasts had a higher proliferation rate and showed significant down-regulation of several collagen genes known for regulating extra cellular matrix (ECM) including: Col1a1, Col1a2, Col3a1, Col4a1, and Col6a1, suggesting that ECM remodeling occurs in the early stages of leukemogenesis. Importantly, co-culture assays found that pre-leukemic CD55+ BM fibroblasts expanded pre-LSCs significantly over normal HSCs. In conclusion, we have identified distinct changes in the preleukemic BMM and identified a novel CD55+ fibroblast population that is expanded in preleukemic BMM that promote the fitness of pre-LSCs over normal HSCs. STATEMENT OF SIGNIFICANCEWe have identified changes in the BMM landscape that define a preleukemic BM niche which includes the expansion of a novel CD55+ fibroblast population. These data suggest that a distinct preleukemic BM niche exists and preferentially supports LSC survival and expansion over normal HSCs to promote leukemogenesis.

cancer biology↗

bioRxiv2023

Human subcutaneous and visceral adipocyte atlases uncover classical and specialized adipocytes and depot-specific patterns

Human adipose depots are functionally distinct. Yet, recent single-nucleus RNA-sequencing (snRNA-seq) analyses largely uncovered overlapping/similar cell-type landscapes. We hypothesized that adipocytes subtypes, differentiation trajectories, and/or intercellular communication patterns could illuminate this depot similarity-difference gap. For this, we performed snRNA-seq of human subcutaneous and visceral adipose tissue. Whereas the majority of adipocytes in both depots were classical, namely enriched in lipid metabolism pathways, we also observed specialized adipocyte subtypes that were enriched in immune-related, extracellular matrix deposition (fibrosis), vascularization/angiogenesis, or ribosomal processes. Pseudo-temporal analysis suggested a developmental trajectory from adipose progenitor cells to classical adipocytes via specialized adipocytes, suggesting that the classical state stems from loss, rather than gain, of specialized functions. Lastly, intercellular communication routes were consistent with the different inflammatory tone of the two depots. Jointly, these findings provide a high-resolution view into the contribution of cellular composition, differentiation, and intercellular communication patterns to human fat depot differences.

systems biology↗

bioRxiv2023

sNucConv: A bulk RNA-seq deconvolution method trained on single-nucleus RNA-seq data to estimate cell-type composition of human subcutaneous and visceral adipose tissues

Deconvolution algorithms rely on single-cell RNA-sequencing (scRNA-seq) data applied onto bulk RNA-sequencing (bulk RNA-seq) to extract information on the cell-types composition and proportions comprising a certain tissue. Adipose tissues cellular composition exhibits enormous plasticity in response to weight changes and high variance at different anatomical locations (depots). However, adipocytes - the functionally unique cell type of adipose tissue, are not amenable to scRNA-seq, a challenge recently met by applying single-nucleus RNA-sequencing (snRNA-seq). Here we aimed to develop a deconvolution method to estimate the cellular composition of human visceral and subcutaneous adipose tissues (hVAT and hSAT, respectively) using snRNA-seq to assess the true cell-type proportions. To correlate deconvolution-estimated cell-type proportions to true (snRNA-seq -derived) proportions, we analyzed seven hVAT and 5 hSAT samples by both bulk RNA-seq and snRNA-seq. snRNA-seq uncovered 15 distinct cell types in hVAT and 13 in hSAT. Deconvolution tools - SCDC, MuSiC, and Scaden exhibited low performance in estimating cell-type proportions (median |R|= 0.12 for estimated vs. true correlations). Notably, estimation accuracy somewhat improved by decreasing the number of cell-types groups, which nevertheless remained low (|R|<0.42). We therefore developed sNuConv, a novel method that employs Scaden, a deep-learning tool, trained using snRNA-seq - based data corrected by i. snRNA-seq/bulk RNA-seq highly-correlated genes, ii. corrected estimated cell-type proportions based on individual cell-type regression models. Applying sNuConv on our bulk RNA-seq data resulted in cell-type proportion estimation accuracy with median R=0.93 (range:0.76-0.97) for hVAT, and median R=0.95 (range:0.92-0.98) for hSAT. The resulting model was depot-specific, reflecting depot-differences in gene expression patterns. Thus, we present sNuConv, a novel, AI-based, method to deduce the cellular landscape of hVAT and hSAT from bulk RNA-seq data, providing proof-of-concept for producing validated deconvolution algorithms for tissues un-amenable to single-cell RNA sequencing.

bioinformatics↗