Biology subjects

Comandante-Lou, N.

Publications and source records attributed to Comandante-Lou, N..

10 recordsLinked to original sources

bioRxiv2026

Altered microglial communication in brains with Alzheimers Disease pathology

Microglia are the resident immune cells of the central nervous system and are highly versatile, continuously monitoring the brain microenvironment with their motile processes and responding to perturbations in diverse ways. Recent studies have revealed substantial functional heterogeneity among microglial states, suggesting that analyzing individual subpopulations is essential to capture specialized signaling programs and disease-associated interactions that would otherwise be obscured in bulk analyses. To better understand how these cells interact, we performed a ligand-receptor communication analysis using single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex, comprising 16 microglial subpopulations together with other myeloid cells identified in brain tissue, including macrophages and monocytes. We characterized the signaling roles of these cell populations, compared individuals with and without neuropathologically defined Alzheimers disease, and associated cell-pair interactions with AD-related clinical and neuropathological traits. We found that AD was characterized by altered microglial composition and rewiring of intercellular communication, including disease-specific signaling pathways and distinct interaction hubs. Lipid-associated microglia were associated with tau pathology, whereas nuclear receptor signaling microglia were linked to hippocampal sclerosis. These findings were replicated in three independent datasets. Overall, this work provides an initial but comprehensive map of microglial communication in the aging human brain and identifies candidate signaling interactions for future functional validation.

neuroscience↗

bioRxiv2026

Neuroticism is linked to cognitive decline and increased risk of Alzheimer's disease through dysregulation of excitatory neurons

INTRODUCTIONNeuroticism is an established risk factor for Alzheimers disease (AD), yet the molecular mechanisms linking this personality trait to neurodegeneration remain poorly understood. METHODSWe leveraged single-nucleus RNA-sequencing data from longitudinal cohort studies of cognitive aging (n = 655) to investigate the mechanisms mediating the association between neuroticism and AD. RESULTSWe identified two genes associated with neuroticism, both of which are downregulated in excitatory neurons: ADRA1B and LY6E-DT. In addition, we found that neuroticism is associated with enrichment of a specific excitatory neuron subpopulation: Exc.12. Further analysis revealed that Exc.12 partially mediates the relationship between neuroticism and AD, accounting for 12.2% of the total effect. DISCUSSIONThe dysregulation of excitatory neurons may represent a key cellular change that links neuroticism to AD.

neuroscience↗

bioRxiv2025

BAG3 coordinates astrocytic proteostasis of Alzheimer's disease-linked proteins via proteasome, autophagy, and retromer complex interactions

BackgroundBcl-2-associated athanogene 3 (BAG3) is a mediator of chaperone assisted selective autophagy, and in the brain, most highly expressed in astrocytes. However, its role in astrocytes remains poorly defined. Given the genetic and pathological links of BAG3 to proteostasis and neurodegenerative diseases, we investigated how BAG3 contributes to astrocyte function and Alzheimers disease (AD). MethodsSnRNA-seq of the human brain determined cell type expression of BAG3. CRISPR/Cas9 gene editing in human iPSCs, followed by tandem mass tag-mass spectrometry and RNA-sequencing was performed to assess proteomic and transcriptomic changes following BAG3 loss. Co-immunoprecipitation of BAG3 in human astrocytes defined the interactome, with top interactors being validated by western blot (WB), AlphaFold modeling, and proximity ligation assays. In astrocytes, autophagic flux, lysosomal phenotypes, proteasome activity, and endocytic uptake were measured in BAG3 KO and BAG3 WT. Finally, BAG3 expression was assessed in postmortem AD brain by WB and snRNA-seq, and its functional relevance to amyloid-{beta} (A{beta}) degradation was tested in co-cultures of BAG3 KO iAs with familial AD neurons. ResultsIn human brain and iPSC models, BAG3 was most highly expressed in astrocytes. Further, BAG3 loss caused greater proteomic disruption in astrocytes than in neurons. In the absence of BAG3, astrocytes showed reduced autophagy, diminished lysosome abundance and activity, and decreased proteasome function. To uncover molecular binding partners of BAG3 that might influence these phenotypes, we performed co-immunoprecipitation, revealing interactions with HSPB8 and other heat shock proteins, proteasome regulators (PSMD5, PSMF1), and the retromer component, VPS35. Integration of BAG3 KO transcriptomic and proteomic datasets pinpointed AD-relevant proteins under post-translational control of BAG3, which included GFAP, BIN1, and HSPB8. HSPB8 levels were markedly reduced in BAG3-deficient astrocytes with overexpression partially rescuing its levels. Loss of astrocytic BAG3 impaired A{beta} clearance in co-culture with APP/PSEN1 mutant neurons, directly linking BAG3 to a disease-relevant astrocyte function. Finally, analysis of postmortem brain tissue revealed BAG3 marks a stress-responsive astrocyte subtype in the brain of aged individuals with AD. ConclusionsBAG3 binds to key regulators of autophagy, proteasome activity, and retromer function to coordinate astrocyte proteostasis, lysosomal function, and A{beta} clearance. These findings position BAG3 as a potential therapeutic target and coordinator of glial protein quality control in neurodegeneration.

neuroscience↗

bioRxiv2025

PLXNB1 and other signaling drives a pathologic astrocyte state contributing to cognitive decline in Alzheimer's Disease

Alzheimers disease (AD) is marked by the coordinated emergence of disease-associated cell states across multiple cell types. Here, we first performed a meta-analysis of single-nucleus transcriptomic (snRNAseq) data from 869 brains of diverse decedents, confirming the critical role of an SLC38A2highSMTNhighCACNA1Dhighastrocyte subset, Astrocyte 10 (Ast10), in AD and aging-related cognitive decline. We then investigated the signaling drivers of Ast10s emergence in the aging brain, focusing on interactions among microglial and astrocytic subsets. Analysis of the snRNAseq data prioritized a set of ligands and receptors that are robustly predictive of Ast10 proportions across participants, and we confirm our predictions in multiple studies. Independent validation with spatial transcriptomics reveals striking colocalization of these prioritized ligands with the Ast10 signature in AD brain tissue, but not with other astrocytic states. Genetic ablation of a top receptor PLXNB1 in murine and human iPSC-derived astrocytes decreased the Ast10 signature, confirming its regulatory role. Finally, we find that Ast10 may contribute to cognitive decline through synaptic loss and is associated with cognitive decline independent of AD. Thus, Ast10 and its regulators are potential points of convergence for multiple neurodegenerative mechanisms and may be promising targets for therapeutic development to preserve cognitive function.

neuroscience↗

bioRxiv2024

HDAC Inhibitors recapitulate Human Disease-Associated Microglia Signatures in vitro

Disease-associated microglia (DAM), initially described in mouse models of neurodegenerative diseases, have been classified into two related states; starting from a TREM2-independent DAM1 state to a TREM2 dependent state termed DAM2, with each state being characterized by the expression of specific marker genes1. Recently, single-cell (sc)RNA-Seq studies have reported the existence of DAMs in humans2-6; however, whether DAMs play beneficial or detrimental roles in the context of neurodegeneration is still under debate7,8. Here, we present a pharmacological approach to mimic human DAM in vitro by exposing different human microglia models to selected histone deacetylase (HDAC) inhibitors. We also provide an initial functional characterization of our model system, showing a specific increase of amyloid beta phagocytosis along with a reduction of MCP-1 secretion. Additionally, we report an increase in MITF expression, a transcription factor previously described to drive expression towards the DAM phenotype. We further identify CADM1, LIPA and SCIN as DAM- marker genes shared across various proposed DAM signatures and in our model systems. Overall, our strategy for targeted microglial polarization bears great potential to further explore human DAM function and biology.

neuroscience↗

bioRxiv2024

Relation of CMV and brain atrophy to trajectories of immunosenescence in diverse populations

Immunosenescence (ISC), the aging of the immune system, has largely been studied in populations of European descent. Here, circulating immune cell cytometric data from African-American, Hispanic, and non-Hispanic White participants were generated. Known and novel age effects were identified using either a meta-analysis approach or a parallel genetic approach. Most results are consistent across the three populations, but some cell populations display evidence of heterogeneity, such as a PD-L1+CD56+ NK cell subset. The study estimated "Immunological Age" (IA) during physiologic aging. While we found no relation of IA to Multiple Sclerosis, IA is associated with entorhinal cortex atrophy, a presymptomatic feature of Alzheimers disease, linking neurodegeneration and peripheral immunity. ISC trajectories were also inferred, highlighting age, CMV status, and genetic ancestry as key influences. Our assessment offers reference ISC trajectories for personalization of assessments of immune function over the life course in diverse populations.

immunology↗

bioRxiv2024

Understanding therapeutic tolerance through a mathematical model of drug-induced resistance

There is growing recognition that phenotypic plasticity enables cancer cells to adapt to various environmental conditions. An example of this adaptability is the persistence of an initially sensitive population of cancer cells in the presence of therapeutic agents. Understanding the implications of this druginduced resistance is essential for predicting transient and long-term tumor tumor dynamics subject to treatment. This paper introduces a mathematical model of this phenomenon of drug-induced resistance which provides excellent fits to time-resolved in vitro experimental data. From observational data of total numbers of cells, the model unravels the relative proportions of sensitive and resistance subpopulations, and quantifies their dynamics as a function of drug dose. The predictions are then validated using data on drug doses which were not used when fitting parameters. The model is then used, in conjunction with optimal control techniques, in order to discover dosing strategies that might lead to better outcomes as quantified by lower total cell volume.

systems biology↗

bioRxiv2024

A pharmacological toolkit for human microglia identifies Topoisomerase I inhibitors as immunomodulators for Alzheimer's disease

AbstractWhile efforts to identify microglial subtypes have recently accelerated, the relation of transcriptomically defined states to function has been largely limited to in silico annotations. Here, we characterize a set of pharmacological compounds that have been proposed to polarize human microglia towards two distinct states - one enriched for AD and MS genes and another characterized by increased expression of antigen presentation genes. Using different model systems including HMC3 cells, iPSC-derived microglia and cerebral organoids, we characterize the effect of these compounds in mimicking human microglial subtypes in vitro. We show that the Topoisomerase I inhibitor Camptothecin induces a CD74high/MHChigh microglial subtype which is specialized in amyloid beta phagocytosis. Camptothecin suppressed amyloid toxicity and restored microglia back to their homeostatic state in a zebrafish amyloid model. Our work provides avenues to recapitulate human microglial subtypes in vitro, enabling functional characterization and providing a foundation for modulating human microglia in vivo.

neuroscience↗

bioRxiv2021

AP-1 transcription factor network explains diverse patterns of cellular plasticity in melanoma

Cellular plasticity associated with fluctuations in transcriptional programs allows individual cells in a tumor to adopt heterogeneous differentiation states and switch phenotype during their adaptive responses to therapies. Despite increasing knowledge of such transcriptional programs, the molecular basis of cellular plasticity remains poorly understood. Here, we combine multiplexed transcriptional and protein measurements at population and single-cell levels with multivariate statistical modeling to show that the state of AP-1 transcription factor network plays a unifying role in explaining diverse patterns of plasticity in melanoma. We find that a regulated balance between AP-1 factors cJUN, JUND, FRA2, FRA1 and cFOS determines the intrinsic diversity of differentiation states and adaptive responses to MAPK inhibitors in melanoma cells. Perturbing this balance through genetic depletion of specific AP-1 proteins, or by MAPK inhibitors, shifts cellular heterogeneity in a predictable fashion. Thus, AP-1 may serve as a critical node for manipulating cellular plasticity with potential therapeutic implications.

systems biology↗

bioRxiv2019

Phenotype-Based Probabilistic Analysis of Heterogeneous Responses to Cancer Drugs and Their Combination Efficacy

Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence are developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (fa), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that fa metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used fa metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells.\n\nAuthor SummaryResistance to therapy due to tumor cell heterogeneity poses a major challenge to the use of cancer drugs. Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish therapeutic efficacy, even in populations of cells scored as highly sensitive based on drug potency. Overcoming such heterogeneity and blocking subpopulations of drug-tolerant cells motivate efforts toward identifying efficacious combination therapies. The success of these efforts depends on our ability to distinguish how heterogeneous populations of cells respond to individual drugs, and how these responses are influenced by combined drug interactions. In this paper, we propose mathematical and experimental frameworks to evaluate time-dependent drug interactions based on probabilistic metrics that quantify drug-induced tumor cell killing or inhibition of division at a single-cell level. These metrics can reveal heterogeneous drug responses and their changes with time and drug combinations. Thus, they have important implications for designing efficacious combination therapies, especially those designed to block or overcome drug-tolerant subpopulations of cancer cells.

systems biology↗