Biology subjects

Weistuch, C.

Publications and source records attributed to Weistuch, C..

10 recordsLinked to original sources

bioRxiv2026

Spatially-resolved single cell atlas of liposarcoma reveals lineage hierarchies, immune niches, and regulatory circuits

Well-differentiated and dedifferentiated liposarcoma (WDLPS and DDLPS) exhibit markedly different clinical behaviors, with DDLPS showing greater aggressiveness, higher recurrence and metastasis rates, and worse outcomes. Using single-nucleus multiome sequencing, epigenomic profiling, and spatial transcriptomics, we characterized cellular and epigenetic heterogeneity between these subtypes at single-cell and spatial resolution. We found distinct phenotypic states reflecting altered lineage differentiation and plasticity: DDLPS is dominated by early-differentiated progenitor-like cells, sclerotic WDLPS displays broader mesenchymal lineage plasticity, and adipocytic WDLPS contains abundant committed adipocytes. The DDLPS immune microenvironment was dominated by immunosuppressive macrophages, whereas WDLPS harbored more T cells and inflammatory macrophages. Notably, sclerotic WDLPS displayed intermediate cellular and molecular features, suggesting it may represent a distinct WDLPS subtype. Importantly, we identified novel gene regulatory circuits underlying each state, including FABP4/PPARG programs in adipocytic WDLPS, GLI2/TCF7L2/RBPJ/KLF7 programs in sclerotic WDLPS, and KLF7/FOSL2/SP3/GLI2/RBPJ programs in DDLPS. H3K27ac-marked enhancers were enriched near adipocytic marker genes in WDLPS and mesenchymal markers in DDLPS. Together, these findings reveal the cellular heterogeneity of tumor and immune compartments across liposarcoma subtypes and identify regulatory programs driving their differentiation states. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/713651v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@1c84ee1org.highwire.dtl.DTLVardef@1b2ad42org.highwire.dtl.DTLVardef@18ce5a6org.highwire.dtl.DTLVardef@138f615_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Spatially convergent fMRI signatures of diabetes and male sex identify genetic vulnerabilities to accelerated brain aging

Age-related cognitive decline results from complex interactions between neuroendocrine and neurometabolic processes that undergo lifelong degredation, yet the mechanisms underlying these interactions remain poorly understood. This study examined the effects of diabetes and sex on functional brain networks across aging through analysis of two large cohorts (N=1,621 total) using both 3T and 7T functional MRI, complemented by spatial transcriptomic data from over 14,000 genes from six post-mortem brains. Four networks-- cingulo-opercular, default mode, salience, and lateral somatomotor--exhibited significant functional decline in both individuals with diabetes and independently in males. Gene expression analysis of vulnerable networks revealed significant overexpression of insulin-dependent glucose transporters, dopaminergic and GABAergic synaptic genes, and VEGFA-VEGFR2 pathway components. These findings suggest functionally-specific circuit vulnerability to metabolic and hormonal dysregulation, potentially offering targets for early intervention before irreversible neurodegeneration occurs.

neuroscience↗

bioRxiv2024

ORCO: Ollivier-Ricci Curvature-Omics: an unsupervised method for analyzing robustness in biological systems

Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret the large-scale omic data are still needed. To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature-omics (ORCO). ORCO incorporates gene interaction information with omic data into a biological network, and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC, an edge-based measure, indicates network robustness and captures global gene signaling changes in functional cooperation using a consistent information passing measure, thereby helping identify therapeutic targets and regulatory modules in biological systems. This tool can be applicable to any data that can be represented as a network. ORCO is an open-source Python package and publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

bioinformatics↗

bioRxiv2023

Transcriptional drift in aging cells: A global de-controller

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the upregulated genes code for sensory proteins upstream of stress responses and downregulated genes are growth- and metabolism-related. We propose a simple mechanistic model for how such global coordination of multi-protein expression levels may be achieved by the binding of a single ligand that concentrates with age. A key implication is that a cells own responses are part of its aging process, so unlike for wear-and-tear processes, intervention might be able to modulate these effects.

biophysics↗

bioRxiv2023

Mapping the Single-cell Differentiation Landscape of Osteosarcoma

The genetic intratumoral heterogeneity observed in human osteosarcomas (OS) poses challenges for drug development and the study of cell fate, plasticity, and differentiation, processes linked to tumor grade, cell metastasis, and survival. To pinpoint errors in OS differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs MSCs toward adipogenic and osteoblastic fates. Incorporating pre-existing chondrocyte data, we applied trajectory analysis and non-negative matrix factorization (NMF) to generate the first human mesenchymal differentiation atlas. This roadmap served as a reference to delineate the cellular composition of morphologically complex OS tumors and quantify each cells lineage commitment. Projecting a bulk RNA-seq OS dataset onto this roadmap unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. Our study takes the critical first step in accurately quantifying OS differentiation and lineage, a prerequisite to better understanding global differentiation bottlenecks that might someday be targeted therapeutically. Statement of SignificanceOS treatment kills proliferating cells without addressing the root disease cause: dysregulated differentiation. Constructing a roadmap of mesenchymal differentiation enabled us to identify gene modules linked to OS cell fate and patient survival. This ability to characterize and quantify cancer cell fate enables a novel, differentiation-based drug-screening strategy.

cancer biology↗

bioRxiv2023

D--hydroxybutyrate stabilizes the hippocampal CA3-CA1 circuit during acute insulin resistance.

1.The brain primarily relies on glycolysis for mitochondrial respiration but switches to alternative fuels such as ketone bodies (KBs) when less glucose is available. Neuronal KB uptake, which does not rely on glucose transporter 4 (GLUT4) or insulin, has shown promising clinical applicability in alleviating the neurological and cognitive effects of disorders with hypometabolic components. However, the specific mechanisms by which such interventions affect neuronal functions are poorly understood. In this study, we pharmacologically blocked GLUT4 to investigate the effects of exogenous KB D--hydroxybutyrate (D-Hb) on mouse brain metabolism during acute insulin resistance (AIR). We found that both AIR and D-Hb had distinct impacts across neuronal compartments: AIR decreased synaptic activity and long-term potentiation (LTP) and impaired axonal conduction, synchronization, and action potential (AP) properties, while D-Hb rescued neuronal functions associated with axonal conduction, synchronization, and LTP. 2. Significance statementThis study investigates the impact of acute insulin resistance on the functionality of the hippocampal circuit and the potential protective effects of ketone body supplementation. By inhibiting GLUT4 receptors to induce acute insulin resistance, we reveal several detrimental changes caused by impaired neuronal glucose uptake. These changes include impairments in synaptic activity, axonal conduction, and neuronal firing properties. The study further examines the distinctive effects of acute insulin resistance and the rescue agent D-{beta}Hb on synaptic activity, long-term potentiation, axonal conduction, synchronization, and neuronal firing. By shedding light on neuronal responses during insulin resistance, this investigation advances our understanding of neurological disorders associated with hypometabolism and highlights the potential therapeutic value of D-{beta}Hb.

neuroscience↗

bioRxiv2023

Ketosis regulates K+ ion channels, strengthening brain-wide signaling disrupted by age.

Aging is associated with impaired signaling between brain regions when measured using resting-state fMRI. This age-related destabilization and desynchronization of brain networks reverses itself when the brain switches from metabolizing glucose to ketones. Here, we probe the mechanistic basis for these effects. First, we established their neuronal basis using two datasets acquired from resting-state EEG (Lifespan: standard diet, 20-80 years, N = 201; Metabolic: individually weight-dosed and calorically-matched glucose and ketone ester challenge, age = 26.9 {+/-} 11.2 years, N = 36). Then, using the multi-scale Larter-Breakspear neural mass model, we identified the unique set of mechanistic parameters consistent with our clinical data. Together, our results implicate potassium (K+) gradient dysregulation as a mechanism for age-related neural desynchronization and its reversal with ketosis, the latter finding of which is consistent with direct measurement of ion channels.

neuroscience↗

bioRxiv2023

Cancer heterogeneity is defined by normal cellular trade-offs

Cancer transcriptional patterns exhibit both shared and unique features across diverse cancer types, but whether these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that cancer transcriptional diversity mirrors patterns in normal tissues optimized for distinct functional tasks. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2-breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

cancer biology↗

bioRxiv2022

The Maximum Entropy Principle For Compositional Data

In this work, we provide a general method for inferring the stochastic behavior of compositional systems. Our approach is guided by the principle of maximum entropy, a data-driven modeling technique. In particular, we show that our method can accurately capture stochastic, inter-species relationships with minimal model parameters. We provide two proofs of principle. First, we measure the relative abundances of different bacteria and infer how they interact. Second, we show that our method outperforms a common alternative for the extraction of gene-gene interactions in triple-negative breast cancer. Author summaryCompositional systems, represented as proportions of some whole, are ubiquitous. They encompass the abundances of proteins in a cell, the distribution of organisms in nature, and the stoichiometry of the most basic chemical reactions. Thus, a central goal is to understand how such processes emerge from the behaviors of their components and their pairwise interactions. Such a study, however, is challenging for two key reasons. Firstly, such systems are complex and depend, often stochastically, on their constituent parts. Secondly, the data lie on a simplex which influences their correlations. We provide a general and data-driven modeling tool for compositional systems to resolve both of these issues. We achieve this through the principle of maximum entropy, which requires only minimal assumptions and limited experimental data in contrast to current alternatives. We show that our approach provides novel and biologically-intuitive insights and is promising as a comprehensive quantitative framework for compositional data.

bioinformatics↗

bioRxiv2020

Younger, but not older, brains are poised at a critical point of functional activity

Brain aging is associated with hypometabolism and associated global changes in functional connectivity. Using fMRI, we show that network synchrony, a collective property of brain activity, decreases with age. Applying quantitative methods from statistical physics, we provide a generative (Ising) model for these changes as a function of the average communication strength between brain regions. In particular, we find healthy brains to be poised at a critical point of this communication strength, enabling a balance between segregated (to functional domains) and integrated (between domains) patterns of synchrony. However, one characteristic of criticality is a high sensitivity to small changes. Thus, minute weakening of pairwise communication between regions, as seen in the aging brain, gives rise to qualitatively abrupt changes in synchrony. Finally, by experimentally modulating metabolic activity in younger adults, we show how metabolism alone-independent of other changes associated with aging-can provide a mechanism for global changes in synchrony.

neuroscience↗