Biology subjects

Carlesso, N.

Publications and source records attributed to Carlesso, N..

6 recordsLinked to original sources

bioRxiv2025

Modeling cerebral development in vitro with L-MYC-immortalized human neural stem cell-derived organoids

A promising advance for ex vivo studies of human brain development and formulation of therapeutic strategies has been the adoption of brain organoids that, to a greater extent than monolayer or spheroid cultures, recapitulate to varying extents the patterns of tissue development and cell differentiation of human brain. Previously, such studies been hampered by limited access to relevant human tissue, inadequate human in vitro models, and the necessity of using rodent models that imperfectly reproduce human brain physiology. Here we present a novel organoid-based research platform utilizing L-MYC-immortalized human fetal neural stem cells (LMNSC01) grown in a physiological 4% oxygen environment. We visualized developmental processes in LMNSC01 brain organoids for over 120 days in vitro by immunofluorescence and NanoString gene expression profiling. Gene expression patterns revealed by NanoString profiling were quantitatively compared to those occurring during normal brain development (BrainSpan database) using the Singscore method. We observe similar developmental patterns in LMNSC01 organoids and developing cortex for genes characterizing neurons, astrocytes, and oligodendrocytes, and multiple pathways including those involved in apoptosis, neuronal cytoskeleton, neurotransmission, and metabolism. Notable properties of this LMNSC01 platform are its initiation with immortalized authentic human neural stem cells, growth in a physiological oxygen environment, the consistency of the organoids produced, and favorable comparison of their gene expression patterns with those reported for normal cortical development. SUMMARYEx vivo studies of human brain development has been advanced by adoption of organoids recapitulating to varying extents in utero patterns of tissue development and cell differentiation. We here present an organoid-based human cortical development platform employing immortalized fetal neural stem cells (LMNSC01) grown in a physiological (4% oxygen) environment. Characterizing LMNSC01 organoids for over 120 days in vitro by immunofluorescence and expression profiling (using NanoString), and then comparing these profiles to those of normal cortical development (BrainSpan database), revealed similar developmental patterns for neurons, astrocytes and oligodendrocytes. Notable properties of this platform are its initiation with immortalized authentic human NSCs, growth at physiological oxygen concentration, and subsequent favorable comparison of their gene expression patterns with those observed during cortical development.

neuroscience↗

bioRxiv2024

Semaphorin 4A maintains functional diversity of the hematopoietic stem cell pool

Somatic stem cell pools are comprised of diverse, highly specialized subsets whose individual contribution is critical for the overall regenerative function. In the bone marrow, myeloid-biased HSC (myHSC) are indispensable for replenishment of myeloid cells and platelets during inflammatory response but at the same time, become irreversibly damaged during inflammation and aging. Here, we identify an extrinsic factor, Semaphorin 4A (Sema4A), which non cell-autonomously confers myHSC resilience to inflammatory stress. We show that the absence of Sema4A, myHSC inflammatory hyper-responsiveness in young mice drives excessive myHSC expansion, myeloid bias and profound loss of regenerative function with age. Mechanistically, Sema4A is mainly produced by neutrophils, signals via a cell surface receptor Plexin D1 and safeguards myHSC epigenetic state. Our study shows that by selectively protecting a distinct stem cell subset, an extrinsic factor preserves functional diversity of somatic stem cell pool throughout organismal lifespan.

cell biology↗

bioRxiv2022

Myeloid-biased HSC require Semaphorin 4A from the bone marrow niche for self-renewal under stress and life-long persistence

Tissue stem cells are hierarchically organized. Those that are most primitive serve as key drivers of regenerative response but the signals that selectively preserve their functional integrity are largely unknown. Here, we identify a secreted factor, Semaphorin 4A (Sema4A), as a specific regulator of myeloid-biased hematopoietic stem cells (myHSC), which are positioned at the top of the HSC hierarchy. Lack of Sema4A leads to exaggerated myHSC (but not downstream "balanced" HSC) proliferation after acute inflammatory stress, indicating that Sema4A enforces myHSC quiescence. Strikingly, aged Sema4A knock-out myHSC expand but almost completely lose reconstitution capacity. The effect of Sema4A is non cell-autonomous, since upon transplantation into Sema4A-deficient environment, wild-type myHSC excessively proliferate but fail to engraft long-term. Sema4A constrains inflammatory signaling in myHSC and acts via a surface receptor Plexin-D1. Our data support a model whereby the most primitive tissue stem cells critically rely on a dedicated signal from the niche for self-renewal and life-long persistence.

cell biology↗

bioRxiv2021

State-Transition Analysis of Time-Sequential microRNA Expression Predicts Development of Acute Myeloid Leukemia

MicroRNAs (miRNAs) are small non-coding RNA molecules involved in post-transcriptional regulation of gene expression and have been shown to hold prognostic value in a variety of settings, including acute myeloid leukemia (AML). However, the temporal dynamics of miRNA expression profiles as it relates to AML initiation and progression is poorly understood. Using serial samples from a mouse model of AML, we show that the miRNA transcriptome undergoes state-transition during AML initiation and progression. The AML state-transition was visualized and modeled by constructing an AML state-space from singular value decomposition of the time-series miRNA sequencing data. Within the AML state-space, we identified critical points of AML development characterized by unique differentially expressed miRNAs compared to healthy controls at critical points of leukemogenesis (early, transition, and late). Interestingly, we observed that changes in miRNA expression during leukemogenesis followed two patterns: 1) a monotonic pattern with continuously increasing or decreasing expression; and 2) a non-monotonic pattern with a local maximum or minimum at the transition critical point which was the "point of no-return" from health to AML. We validated the AML state-space and dynamics in an independent cohort of mice and demonstrated the state-transition model accurately predicted time to AML. Of note, we show that the miRNA-derived state-transition model produced a state-space and critical points that were strikingly similar, but not identical to that produced by the coding (i.e., messenger [m]RNA-based) transcriptome. This indicates that while both miRNA and mRNA expression may provide similar information, they also capture independent features of AML state-transition. SignificanceWe show that the microRNA transcriptome undergoes a global state transition during the initiation and progression of acute myeloid leukemia, and accurately predicts time to disease development.

cancer biology↗

bioRxiv2017

Transcriptome dynamics describe and predict state transition from health to leukemia

Temporal dynamics of gene expression are informative of changes associated with disease development and evolution. Given the complexity of high-dimensional temporal datasets, an analytical framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Herein, we use acute myeloid leukemia as a proof-of-principle to model gene expression dynamics in a transcriptome state-space constructed based on time-sequential RNA-sequencing data. We describe the construction of a state-transition model to identify state-transition critical points which accurately predicts leukemia development. We show an analytical approach based on state-transition critical points identified step-wise transcriptomic perturbations driving leukemia progression. Furthermore, the gene(s) trajectory and geometry of the transcriptome state-space provides biologically-relevant gene expression signals that are not synchronized in time, and allows quantification of gene(s) contribution to leukemia development. Therefore, our state-transition model can synthesize information, identify critical points to guide interpretation of transcriptome trajectories and predict disease development.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=193 HEIGHT=200 SRC=\"FIGDIR/small/238923v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (55K):\norg.highwire.dtl.DTLVardef@12eeaccorg.highwire.dtl.DTLVardef@1392af9org.highwire.dtl.DTLVardef@34786dorg.highwire.dtl.DTLVardef@ce78bb_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe theory of state-transition is applied to acute myeloid leukemia (AML) to model transcriptome dynamics and trajectories in a state-space, and is used to identify critical points corresponding to critical transcriptomic perturbations that predict leukemia development.\n\nHighlightsO_LILeukemia transcriptome dynamics are modeled as movement in transcriptome state-space\nC_LIO_LIState-transition model and critical points accurately predicts leukemia development\nC_LIO_LICritical point-based approach identifies step-wise transcriptome events in leukemia\nC_LIO_LIState-based geometric analysis provides quantification of leukemogenic contribution\nC_LI

cancer biology↗

bioRxiv2017

Aging in a relativistic biological space-time

Here we present a theoretical and mathematical perspective on the process of aging. We extend the concepts of physical space and time to an abstract, mathematically-defined space, which we associate with a concept of \"biological space-time\" in which biological clocks operate. We hypothesize that biological dynamics, represented as trajectories in biological space-time, may be used to model and study different rates of biological aging. As a consequence of this hypothesis, we show how the dilation or contraction of time resulting from accelerated or decelerated biological dynamics may be used to study precipitous or protracted aging. We show specific examples of how these principles may be used to model different rates of aging, with an emphasis on cancer in aging. We discuss the implications of this theory, including novel concepts that may improve our interpretation of biological aging.

cancer biology↗