Biology subjects

Adler, M.

Publications and source records attributed to Adler, M..

15 recordsLinked to original sources

bioRxiv2026

Novel LRRK2 Kinase Inhibitors Enhance Phosphorylation and Restore Adapter Protein Binding in LRRK2 Variants

Autosomal dominant mutations in LRRK2 that increase kinase activity significantly increase the risk of developing Parkinson's disease (PD). Efforts to reduce the resulting hyperphosphorylation have focused mainly on small-molecule type I kinase inhibitors (KIs); however, these bind the active, closed conformation of the LRRK2 kinase domain, which affects protein tertiary structure and can alter other functions of this multi-domain protein. Because disruption of these functions may contribute to pathogenesis independently of, or in addition to, augmented kinase activity, inhibitors that engage LRRK2 differently may offer an advantage. We hypothesize that KIs, which bind distinct conformations of LRRK2 and modulate non-kinase functions differently than type I inhibitors, may be beneficial. Here we tested two series of LRRK2 inhibitors, based on hesperadin (series A) and GNF-7 (series B), which each inhibited LRRK2 kinase activity in biochemical and cellular assays while differing in effects on other LRRK2 functions. Interestingly, series B compounds enhanced phosphorylation of interdomain heterologous phosphosites and restored 14-3-3 binding in LRRK2 variants with suppressed phosphorylation. These chemotypes provide tools for dissecting the consequences of different inhibitor-bound LRRK2 conformations and support conformation-selective inhibition as a therapeutic strategy for PD.

biochemistry↗

bioRxiv2026

Cross-source proteogenomic profiling of human microglia reveals a conserved core membrane protein and HERV signature

Microglia are essential immune cells of the brain parenchyma which are responsible for maintaining homeostasis and responding to brain injury. When activated, they induce immune signaling and become phagocytic. In the context of neurodegenerative diseases, they exhibit both pro- and anti-inflammatory properties. Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral germline infections that integrated into the human genome, and their expression has been directly linked to microglial-mediated neurodegenerative diseases. Despite this, HERV expression is not consistently included in analyses characterizing microglia. Investigating the function of microglia across different diseases is critical for elucidating mechanisms of disease progression and for the development of effective therapeutic interventions. Approaches to studying microglia include isolation from post-mortem brain tissues, differentiation from peripheral blood monocytes or differentiation of induced pluripotent stem cells (iPSC). Ex vivo brain derived microglia (BdMG) are considered most physiologically relevant, but constraints including the unpredictable timing of availability, labor-intensive protocols, and low yields reduce their practicality. Existing alternatives are iPSC-derived microglia (iMG) and monocyte-derived microglia (MDMi) models that circumvent sample accessibility and scalability issues. Here, we explored the transcriptome and proteome of these three microglia sources and identified a common microglia surface marker expression profile, establishing that MDMi and iMG exhibit similar phenotypes relative to BdMG. We also identified a common HERV expression profile across BdMG, iMG and MDMi, indicating deeper similarities across different sources. Altogether, our findings indicate that given the phenotypic similarities of the 2 models, MDMi represent a practical and reliable model for investigating microglial function with iMG models serving for more molecular based approaches, such as CRISPRa/i.

neuroscience↗

bioRxiv2025

Temporal control of axonal floor plate crossing through a combination of incoherent feedforward and feedback loops of gene regulatory network regulating Robo3 expression

Spinal commissural neurons play a fundamental role in motor control and sensory perception. Robo3, a receptor expressed on pre-crossing commissural axons, is required for midline crossing. Its downregulation in post-crossing axons is essential for forming synapses with contralateral CNS targets. We demonstrate that, at the transcriptional level, the dynamic expression of Robo3 in pre-crossing neurons is controlled by incoherent feed-forward loops (iFFLs) and negative feedback loops (NFLs) that precisely regulate its transience and thereby determine midline crossing. Lhx2 and Lhx9 activate Robo3 while also inducing its repressor, Barhl2. Additionally, negative feedback loops fine-tune the transience of Robo3 expression by adjusting the relative strength of the activation and repression modules. Our genomic analysis reveals that this regulatory circuitry converges on an enhancer element of the Robo3 gene. These findings imply that diverse iFFLs, together with NFLs, are essential for regulating the extent of midline crossing across different spinal commissural subtypes.

developmental biology↗

bioRxiv2025

Tissue-level division of labor is coordinated across organs through universal programs and context-specific adaptations

Fibroblasts, macrophages, and endothelial cells are common to most mammalian tissues, where they support homeostasis, repair, and immune regulation. Yet how they coordinate their functions across diverse tissue environments remains unclear. Here, we analyze single-cell RNA sequencing data from 14 human tissues using Pareto optimality framework and identify 16 archetypes - specialized transcriptional programs representing functional tradeoffs. These include universal archetypes shared across tissues and tissue-specific archetypes shaped by local context. We find that tissues align along a continuous axis of archetype distributions, from metabolically active to barrier organs, reflecting coordinated functional adaptation. Using ligand-receptor enrichment mapping, we reveal task-specific crosstalk across cell types, suggesting that intercellular communication underlies supportive division of labor. Applying this analysis to mouse tissues, we find similar patterns, indicating evolutionary conserved tradeoffs. These findings provide a framework for understanding how division of labor is coordinated in health and how its dysregulation may contribute to disease.

systems biology↗

bioRxiv2025

ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference

MotivationTrade-offs between different functions or tasks are pervasive across scales in biological systems. For example, individual cells cannot perform all possible functions simultaneously; instead they allocate limited resources to specialize in subsets of tasks by activating specific gene expression programs. Pareto Task Inference (ParTI) is a framework for analyzing biological trade-offs grounded in the theory of multi-objective optimality. However, existing software implementations of ParTI lack scalability to large datasets and do not integrate well with standard biological data analysis workflows, especially in the context of single-cell transcriptomics, limiting broader adoption. ResultsWe have developed ParTIpy (Pareto Task Inference in Python), an open-source Python package that combines advances in optimization and coreset methods to scale archetypal analysis, the primary algorithm underlying ParTI, to large-scale datasets. By providing additional tools to characterize archetypes, comprehensive documentation, and adopting standard scverse data structures, ParTIpy facilitates seamless integration into existing analysis workflows and broadens accessibility, particularly within the single-cell community. We demonstrate how ParTIpy can be used to study intra-cell-type gene expression variability through the lens of task allocation, offering a principled alternative to methods that impose discrete cell state classifications on inherently continuous variation. Availability and implementationParTIpys open-source code is available on GitHub (https://github.com/saezlab/ParTIpy) and pypi (https://pypi.org/project/partipy). Documentation is available at https://partipy.readthedocs.io. The code to reproduce the results of this paper is on GitHub (https://github.com/saezlab/ParTIpy_paper)

bioinformatics↗

bioRxiv2025

A fibroblast-centric network drives cold fibrosis in the tumor microenvironment of lung squamous cell carcinoma

The tumor microenvironment (TME) of chronic inflammation-associated cancers (CIACs) is shaped by cycles of injury and maladaptive repair, yet the principles organizing fibrotic stroma in these tumors remain unclear. Here, we applied the concept of hot versus cold fibrosis, originally credentialed in non-cancerous fibrosis of heart and kidney, to lung squamous cell carcinoma (LUSC), a prototypical CIAC. Single-cell transcriptomics of matched tumor and adjacent-normal tissue from 16 treatment-naive LUSC patients identified a cold fibrotic architecture in the LUSC TME: cancer-associated fibroblasts (CAFs) expanded and adopted myofibroblast and stress-response states, while macrophages were depleted. This macrophage-poor, CAF-rich stroma was maintained by CAF autocrine growth factor loops, including TIMP1, INHBA, TGFB1, and GMFB. In parallel, the immune compartment exhibited a hot tumor phenotype with abundant T and B cells, forming spatially distinct but molecularly engaged networks with CAFs. CAF gene programs typifying cold fibrosis in LUSC were conserved in other CIACs, including esophageal and gastric adenocarcinomas. These results redefine desmoplastic regions of tumors through the lens of a non-cancer fibrosis model, demonstrating that conserved stromal circuits constitute therapeutic vulnerabilities in CIACs.

cancer biology↗

bioRxiv2024

Small molecule activation of the tumor suppressor kinase LKB1

The ability to identify and target oncogenic signals has transformed clinical oncology. Drug development for targeted therapies has historically focused on the inhibition of oncogenic kinases and GTPases. However, many cancer patients do not benefit from targeted approaches because their tumors lack targetable mutations. Therapeutic augmentation of tumor suppressive signaling could be a viable alternative but poses challenges. Specifically, designing compounds capable of stimulating kinase activity is more structurally challenging than inhibitor design, and most kinases lack targetable allosteric pockets. Inactivation of the liver kinase B1 (LKB1) tumor suppressor kinase is associated with poor prognosis and therapeutic resistance. Thus, augmented LKB1 function could be beneficial for cancer patients whose tumors retain intact copies of the gene. LKB1 signals as part of an obligate trimer including the scaffolding protein Mouse protein-25 (MO25) and the pseudokinase (PSK) STE20-related kinase adapter protein (STRAD). As STRAD binds but does not metabolize ATP, it provides the opportunity for a novel activation strategy. We have developed STRAD-binding compounds capable of activating LKB1 and demonstrate the therapeutic benefits of LKB1 activation in a target-dependent manner within cancer cell lines.

biochemistry↗

bioRxiv2024

Recurrent hyper-motif circuits in developmental programs

During embryogenesis, homogenous groups of cells self-organize into stereotypic spatial and temporal patterns that make up tissues and organs. These emergent patterns are controlled by transcription factors and secreted signals that regulate cellular fate and behaviors through intracellular regulatory circuits and cell-cell communication circuits. However, the principles of these circuits and how their properties are combined to provide the spatio-temporal properties of tissues remain unclear. Here we develop a framework to explore building-block circuits of developmental programs. We use single-cell gene expression data across developmental stages of the human intestine to infer the key intra- and inter-cellular circuits that control developmental programs. We study how these circuits are joined into higher-level hyper-motif circuits and explore their emergent dynamical properties. This framework uncovers design principles of developmental programs and reveals the rules that allow cells to develop robust and diverse patterns.

systems biology↗

bioRxiv2023

Circuit to target approach defines an autocrine myofibroblast loop that drives cardiac fibrosis

Fibrosis is a broad pathology of excessive scarring with substantial medical implications. The fibrotic scar is produced by myofibroblasts that interact with macrophages. Fibrosis is a complex process involving thousands of factors, therefore, to better understand fibrosis and develop new therapeutic approaches, it is necessary to simplify and clarify the underlying concepts. Recently, we described a mathematical model for a macrophage-myofibroblast cell circuit, predicting two types of fibrosis - hot fibrosis with abundant macrophages and myofibroblasts, and cold fibrosis dominated by myofibroblasts alone. To test these concepts and intervention strategies in a medically relevant system, we use a widely studied in-vivo injury model for fibrosis, myocardial infarction (MI). We show that cold fibrosis is the final outcome of MI in both mice and pigs and demonstrate that fibrosis can shift toward healing in regenerative settings. MI begind with an increase of myofibroblasts and macrophages, followed by macrophage decline leading to persistent cold fibrosis (only myofibroblasts). During this process, fibroblasts, unlike macrophages, acquire distinct fate changes. Using mathematical modeling we predict that targeting of the autocrine signal for myofibroblast division could block cold fibrosis. We identify TIMP1 as an autocrine cardiac myofibroblast growth factor in-vitro. Treatment of adult mice after MI with anti-TIMP1 antibodies reduces fibrosis in-vivo. This study shows the utility of the concepts of hot and cold fibrosis and the feasibility of our circuit-to-target approach to reduce fibrosis after acute cardiac injury by inhibiting the myofibroblast autocrine loop.

systems biology↗

bioRxiv2022

Emergence of division of labor in tissues through cell interactions and spatial cues

Most cell types in multicellular organisms can perform multiple functions. However, not all functions can be optimally performed simultaneously by the same cells. Functions incompatible at the level of individual cells can be performed at the cell population level, where cells divide labor and specialize in different functions. Division of labor can arise due to instruction by tissue environment or through self-organization. Here, we develop a computational framework to investigate the contribution of these mechanisms to division of labor within a cell-type population. By optimizing collective cellular task performance under trade-offs, we find that distinguishable expression patterns can emerge from cell-cell interactions vs. instructive signals. We propose a method to construct ligand-receptor networks between specialist cells and use it to infer division-of-labor mechanisms from single-cell RNA-seq and spatial transcriptomics data of stromal, epithelial, and immune cells. Our framework can be used to characterize the complexity of cell interactions within tissues.

systems biology↗

bioRxiv2022

iPSC Motor Neurons with Familial ALS Mutations Capture Gene Expression Changes in Postmortem Sporadic ALS Motor Neurons

Motor neuron degeneration, the defining feature of ALS, is a primary example of cell-type specificity in neurodegenerative diseases. Using isogenic pairs of iPSCs harboring different familial ALS mutations, we assess the capacity of iPSC-derived spinal motor neurons, sensory neurons, astrocytes, and superficial cortical neurons to capture disease features including transcriptional and splicing dysregulation observed in human post-mortem neurons. At surprisingly early time points, differentially regulated genes in iPSC-derived spinal motor neurons, but not other cell types, overlap with one-third of the differentially regulated genes in laser-dissected motor neurons from postmortem spinal cords. The extent of dysregulation correlates well between iPSC-derived and bona fide spinal motor neurons. In iPSC-derived spinal motor neurons, but not other derived cell types, we detect downregulation of genes affected by TDP-43-dependent aberrant splicing. This reduction takes place exclusively within genotypes known to involve TDP-43 pathology and occurs without evidence of TDP-43 mislocalization or protein level alteration.

neuroscience↗

bioRxiv2022

Microenvironmental sensing by fibroblasts controls macrophage population size

Animal tissues are comprised of diverse cell types. However, the mechanisms controlling the number of each cell type within tissue compartments remain poorly understood. Here, we report that different cell types utilize distinct strategies to control population numbers. Proliferation of fibroblasts, stromal cells important for tissue integrity, is limited by space availability. In contrast, proliferation of macrophages, innate immune cells involved in defense, repair, and homeostasis, is constrained by growth factor availability. Examination of density-dependent gene expression in fibroblasts revealed that Hippo and TGF-{beta} target genes are both regulated by cell density. We found YAP1, the transcriptional co-activator of the Hippo signaling pathway, directly regulates expression of Csf1, the lineage-specific growth factor for macrophages, through an enhancer of Csf1 that is specifically active in fibroblasts. Activation of YAP1 in fibroblasts elevates Csf1 expression and is sufficient to increase the number of macrophages at steady state. Our data also suggest that expression programs in fibroblasts that change with density may result from sensing of mechanical force through actin-dependent mechanisms. Altogether, we demonstrate that two different modes of population control are connected and coordinated to regulate cell numbers of distinct cell types. Sensing of the tissue environment may serve as a general strategy to control tissue composition. Significance StatementCollections of distinct cell types constitute animal tissues. To perform their unique functions, each cell type must exist in the correct number and proportion in a given tissue compartment. However, many of the mechanisms regulating and coordinating cell population sizes remain enigmatic. Our study characterizes two different modes of population size control, utilized by two ubiquitous cell types, macrophages and fibroblasts. Macrophage populations are more sensitive to the presence of growth factors in the environment and fibroblasts are more sensitive to space limitations. Intriguingly, space-sensing mechanisms in fibroblasts directly control the production of growth factor for macrophages and thus macrophage numbers. This link suggests a mechanism by which macrophage compartment size is controlled by stromal cells according to the microenvironment.

immunology↗

bioRxiv2019

Principles of Cell Circuits for Tissue Repair and Fibrosis

Tissue-repair is a protective response after injury, but repetitive or prolonged injury can lead to fibrosis, a pathological state of excessive scarring. To pinpoint the dynamic mechanisms underlying fibrosis, it is important to understand the principles of the cell circuits that carry out tissue-repair. In this study, we establish a cell-circuit framework for the myofibroblast-macrophage circuit in wound-healing, including the accumulation of scar-forming extracellular matrix. We find that fibrosis results from multistability between three outcomes, which we term hot fibrosis characterized by many macrophages, cold fibrosis lacking macrophages, and normal wound-healing. The cell-circuit framework clarifies several unexplained phenomena including the paradoxical effect of macrophage depletion, the limited time-window in which removing inflammation leads to healing, the effects of cellular senescence, and why scar maturation takes months. We define key parameters that control the transition from healing to fibrosis, which may serve as potential targets for therapeutic reduction of fibrosis.

systems biology↗

bioRxiv2019

Multidimensional extracellular-matrix analysis reveals a silent pre-clinical signature in inflammatory disease

Identification of early processes leading to complex tissue pathologies, such as inflammatory bowel diseases, poses a major scientific and clinical challenge that is imperative for improved diagnosis and treatment. Most studies of inflammation onset focus on cellular processes and signaling molecules, while overlooking the environment in which they take place, the continuously remodeled extracellular matrix. In this study, we used colitis models for investigating extracellular-matrix dynamics during disease onset, while treating the matrix as a complete and defined entity. Through the analysis of matrix structure, stiffness and composition, we unexpectedly revealed that even prior to the first clinical symptoms, the colon displays its own unique extracellular-matrix signature and found specific markers of clinical potential, which were also validated in human subjects. We also show that the emergence of this pre-symptomatic matrix is mediated by sub-clinical infiltration of neutrophils and monocytes bearing remodeling enzymes. Remarkably, whether the inflammation is chronic or acute, its matrix signature converges at pre-symptomatic states. We suggest that the existence of a pre-symptomatic extracellular-matrix is general and relevant to a wide range of diseases.

systems biology↗

bioRxiv2017

Note on the power law of forgetting

Power functions (e.g., f(t) = at-b) describe the relationships among many variables observed in nature. One example of this is the power law of forgetting: The decline in memory performance with time or intervening events is well fit by a power function. This simple functional relationship accounts for a great deal of accumulated data. In this note, we consider a simple yet general memory model in which all items decay monotonically in strength, but at different rates. To translate between continuous changes in strength and actual memory for events we assume a simple strength threshold for remembering. We prove a limit theorem for this model: as time grows large and memories decay, the empirical forgetting function approaches a power function under very general conditions. Power forgetting emerges for almost any monotonically decreasing strength function (including linear and exponential cases). We also illustrate by way of simulations that the power function provides an excellent fit to the entire time-course of the forgetting function, not just its limiting behavior.

neuroscience↗