Biology subjects

Laux, L.

Publications and source records attributed to Laux, L..

10 recordsLinked to original sources

bioRxiv2026

Cellular senescence is associated with age-related loss of liver zonation and hepatocyte function

The liver is organized into tightly regulated zones with distinct metabolic functions but zonation erodes with age. Cellular senescence contributes to aging and liver diseases, however, its impact on aging biology is ill-defined. As part of The Cellular Senescence Network Consortium, we used multiple spatial transcriptomics approaches (GeoMx, Visium, CosMx) with snRNA-seq to profile senescence signatures, zonation markers, and metabolic pathways in livers from wild-type (WT) mice of multiple ages. We observed a loss of canonical zone signatures in aged mouse livers characterized by "expansion" of midlobular (zone 2) marker gene expression, accompanied by diminished expression of zone 3 marker genes by middle-age (18 months), indicative of loss of cell identity. Multiple analytic approaches identified distinct age-, zone- and sex-specific senescence signatures, which were significantly associated with zonation markers changes. This was recapitulated in Ercc1 mutant models of accelerated senescence, supporting a causal role of senescent cells in liver aging. A "no-zone" hepatocyte-like cluster expanded with age and with the strongest Senescence-Associated Secretory Phenotype (SASP) profile. Gene expression profiles from senescent hepatocytes implicate decreased WNT signaling and increased BMP as contributing to age-related loss of zonation. Together, these data elucidate the role of senescent cells in driving aging biology in non-diseased liver through disruption of cell:cell signaling and the loss of metabolic and cell identity gene expression necessary for hepatocyte function.

cell biology↗

bioRxiv2026

Cyclin D1 regulates the hepatic response to feeding: Evidence for non-cell cycle roles in the liver

ObjectivesPrior studies have shown that cyclin D1 regulates diverse aspects of liver metabolism during cell cycle progression. Interestingly, this protein is induced in hepatocytes by feeding, but its function in modulating hepatic postprandial physiology is poorly characterized. The aim of this study was to evaluate the contribution of cyclin D1 to the hepatic response to feeding and to gain insight into its potential non-proliferative roles in other conditions. MethodsMice with or without hepatocyte cyclin D1 (D1fl/fl or D1{Delta}Hep) were fasted and refed a high-carbohydrate diet. Mouse and human liver in the setting of aging and MASLD were analyzed. The C. elegans model was used to evaluate the role of cyclin D1 (CYD-1) in response to overnutrition. ResultsCyclin D1 regulated hepatic gene networks involved in glucose and lipid metabolism, protein synthesis, immune response, and other pathways after feeding. Induction of acute phase response proteins was markedly inhibited in D1{Delta}Hep mice, which was associated with corresponding changes in histone acetylation on key genes. In aged liver, hepatocyte cyclin D1 was induced without associated proliferation; this was markedly pronounced in progeroid Ercc1-deficient mice. Cyclin D1 was upregulated in MASLD and diminished with successful treatment. CYD-1 was induced by overnutrition in the intestine of Caenorhabditis elegans (which performs metabolic functions similar to liver) and regulates key nutrient-responsive proteins. CYD-1 inhibition prolonged lifespan in this setting. ConclusionsCyclin D1 regulates nutrient-mediated physiology in the liver and C. elegans, indicating that it has unexpected and highly conserved metabolic functions. Further study is warranted to define its role in hepatic disease and aging. HighlightsO_LICyclin D1 is induced in hepatocytes with feeding and broadly regulates hepatic gene expression. C_LIO_LIAcute phase response (APR) and senescence-associated secretory phenotype (SASP) proteins are markedly regulated by cyclin D1. C_LIO_LIHepatocyte expression of cyclin D1 is substantially upregulated in aging, premature aging, and MASLD without associated proliferation. C_LIO_LICyclin D1 (CYD-1) regulates nutrient-mediated signaling and lifespan in response to overnutrition in C. elegans. C_LI

physiology↗

bioRxiv2026

Excitatory Dysfunction and Phenotypic Rescue in a Human Neuronal Model of SCN2A-Related Disorders

SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorders result in variable age of onset epilepsy, autism spectrum disorder, and epileptic encephalopathies. While the mechanisms of haploinsufficiency resulting in autism spectrum disorder have been explored in detail, few studies report the impact of pathogenic missense variants in human neurons. In this work, we combined conventional electrophysiology and high-throughput all-optical electrophysiology assays to analyze the SCN2A p.M1879T pathogenic variant associated with early-onset epilepsy and developmental delay. In both platforms, iPSC-derived excitatory neurons expressing the disease variant showed greater firing at higher stimuli compared to the isogenic control neurons (corrected by CRISPR/Cas9), as well as changes to action potential shape (steeper slope and larger amplitude) with evoked firing. We used machine learning techniques on the optical physiology dataset to classify the two genotypes, finding that sodium channel blocking anti-seizure drugs could restore an isogenic phenotype. This work demonstrates proof of sodium channel blocker efficacy in a human neuronal model of SCN2A-related epilepsy and highlights the power of leveraging high-throughput all-optical electrophysiology for testing drug efficacy.

neuroscience↗

bioRxiv2026

Mean environmental associations obscure drivers of zooplankton community dynamics

Zooplankton communities are influenced by multiple environmental factors, including temperature, nutrient and resource availability, which fluctuate seasonally and across years. While long-term average effects can identify overall drivers, they may overlook dynamic, context-dependent effects that govern short-term changes in diversity and abundance. Understanding and disentangling both perspectives is crucial for identifying and estimating the drivers that shape community structure under varying environmental states. Here, we applied Empirical Dynamic Modeling (CCM, SMap) to a 12-year weekly zooplankton time series to identify causal environmental drivers of taxonomic and morphological diversity and quantify how the influence of each driver shifts over time. We contrast these results with static long-term average effects inferred from Generalized Linear Models which included predictor sets identified using covariate adjustment and accounting for temporal autocorrelation. Drivers linked to long-term average associations differed from those regulating short-term zooplankton dynamics, revealing a decoupling between mean environmental effects and the drivers of temporal variability. Temperature emerged as a persistent regulator of zooplankton dynamics across multiple diversity dimensions, while variables commonly associated with background trophic conditions (e.g. particulate organic matter) were primarily associated with long-term patterns and showed limited dynamical relevance. Importantly, we find evidence for morphological homogenisation in response to short-term fluctuations in chlorophyll a, which was not detectable in long-term average relationships. This contrast highlights that mean environmental associations do not necessarily reflect the mechanisms governing community dynamics. Impacts might be underestimated if average effects appear weak, or misinterpreted if arising mainly from shared trends or seasonality rather than direct mechanisms Integrating both perspectives clarifies the identity and role of environmental drivers, improving inference and prediction of zooplankton community change through time.

ecology↗

bioRxiv2026

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

Spatial transcriptomics enables the study of how cells coordinate their molecular states within tissue, providing insight into both normal function and disease processes. A key challenge is to identify gene expression programs that vary continuously across space and are coordinated between cell types. We present CoPro, a computational framework for detecting the spatially coordinated progression of cellular states. CoPro can operate in both supervised and unsupervised modes to identify gene programs that co-vary within or between cell types, and to disentangle multiple overlapping spatial patterns. CoPro can be applied to single-cell-level spatial transcriptomics datasets, including MERFISH, SeqFISH+, Xenium, and histology-imputed transcriptomic data. We demonstrate the utility of CoPro with data collected from colon, brain, liver, and kidney tissues. In the colon, CoPro separates epithelial differentiation along the crypt axis from spatially localized inflammatory signals. In the aging liver, it identifies multiple aging-associated cellular programs superimposed on anatomical zonation. In the brain, the flexible kernel design enables the decoupling of the gene expression gradient along the dorsal-ventral and medial-lateral axes. In the kidney, CoPro identifies tubule-vasculature coordination that is essential in nephron function. These results demonstrate CoPros utility for analyzing spatial coordination of gene expression in complex tissues and disentangling overlapping biological processes, such as anatomical organization and disease-associated variation.

bioinformatics↗

bioRxiv2026

ATGL-catalyzed lipid catabolism promotes DNA repair

An imbalance of DNA damage over DNA repair contributes to the genomic instability that drives aging and numerous age-related diseases. While numerous DNA repair mechanisms have been elucidated over decades of study, little is known about the contribution of metabolism to genomic stability. We report that adipose triglyceride lipase (ATGL), a lipolytic enzyme, promotes DNA repair. We show that lipid droplets (LDs) accumulate in response to DNA damage and that inhibition of LD biogenesis before genotoxic stress increases the persistence of DNA damage. Overexpression of ATGL, which increases lipolysis, reduces DNA damage following etoposide and ionizing radiation, thereby promoting genomic stability. Further, ATGL expression prior to DNA damage attenuates the long-term consequences of DNA damage, reducing senescence and enhancing viability. Mechanistically, ATGL promotes double-strand break repair via NHEJ and HR to mitigate DNA damage. Overall, these studies reveal a novel role for LDs and their proteins in DNA damage and repair, thereby unveiling a mechanism by which lipid metabolism contributes to genomic stability.

biochemistry↗

bioRxiv2026

KCNH1 variants associated with neurodevelopmental disorders exhibit prominent gain-of-function

Pathogenic variants in KCNH1, encoding the human ether-a-go-go voltage-gated potassium channel (EAG1, KV10.1), are associated with the neurodevelopmental disorders Temple-Baraitser syndrome (TBS), Zimmermann-Laband syndrome (ZLS), and epileptic encephalopathy. Investigating the functional consequences of KCNH1 variants can provide information about molecular and cellular pathophysiological mechanisms, and help guide therapeutic directions. In this study, we determined the functional properties of 26 disease-associated KCNH1 variants including three recurrent and five that were previously unpublished. Findings were compared to the wildtype (WT) channel along with six rare population variants. Our approach used automated patch clamp recording of heterologously expressed KCNH1 variants in both the homozygous state (variant alone) and the clinically-relevant heterozygous state (variant co-expressed with WT channels). We also examined the impact of alternative splice isoforms on functional consequences of specific variants. We demonstrated that the majority of disease-associated KCNH1 variants exhibit features consistent with gain-of-function including hyperpolarized voltage-dependence of activation, accelerated activation kinetics, or both that promote hyperpolarization of the resting membrane potential. By contrast, one unique variant discovered previously in an autism cohort had a depolarized voltage-dependence of activation and was associated with a depolarized resting potential in cells. Pharmacological testing of KCNH1 variants demonstrated differences in potency for channel block by imipramine and an investigational non-selective potassium channel blocker (LY97241) for specific variants. Collectively, our findings support gain-of-function as the most common, albeit not exclusive, molecular mechanism underlying KCNH1-related disorders and suggest opportunities for potential therapeutic drug repurposing strategies for these conditions.

neuroscience↗

bioRxiv2024

Ecological networks across interaction types are modular and highly driven by sampling intensity at biogeographical scales

Understanding how the structure of ecological communities varies across biotic and abiotic dimensions is a fundamental goal in ecology. This challenge is now approachable due to the increasing availability of data on community structure across the globe. Ecological communities are often defined with respect to the guilds considered and the interactions they engage in, but it is unclear whether interactions of different types respond similarly to large-scale environmental gradients. Therefore, we lack a deeper understanding of how the emergent structure of interaction networks varies across biogeographical gradients, and how this effect may change depending on their constituent interaction types. Here, using a unique dataset of 952 networks across the globe, we provide a first comparison of network structural metrics and their large-scale variability for five overarching interaction types (feeding, frugivory, herbivory, parasitism and pollination). We show that degree distribution, but not connectance alone, helps us understand the observed network structures, and this pattern is maintained across interaction types (with the partial exception of food webs). Moreover, degree distribution descriptors are generally explained by differences across studies, which represent a proxy for variability in sampling and network construction methods. Environ-mental factors show weaker but robust effects on network degree distribution, and food webs are generally more sensitive to changes in environmental factors than networks of other interaction types. By analysing common descriptors of the degree distributions of ecological networks, this study underscores for the first time generalities and differences across networks of different interaction types and their response to environmental and anthropogenic factors.

ecology↗

bioRxiv2021

Pathogenic MAST3 variants in the STK domain are associated with epilepsy

ObjectiveThe MAST family of microtubule-associated serine-threonine kinases (STK) have distinct expression patterns in the developing and mature human and mouse brain. To date, only MAST1 has been associated with neurological disease, with de novo variants in individuals with a neurodevelopmental disorder, including a mega corpus callosum. MethodsUsing exome sequencing we identify MAST3 missense variants in individuals with epilepsy. We also assess the effect of these variants on the ability of MAST3 to phosphorylate the target gene product ARPP-16 in HEK293T cells. ResultsWe identify de novo missense variants in the STK domain in 11 individuals, including two recurrent variants p.G510S (n=5) and p.G515S (n=3). All 11 individuals had Developmental and epileptic encephalopathy, with 8 having normal development prior to seizure onset at < 2 years of age. All patients developed multiple seizures types, while 9/11 had seizures triggered by fever and 9/11 had drug-resistant seizures. In vitro analysis of HEK293T cells transfected with MAST3 cDNA carrying a subset of these patient-specific missense variants demonstrated variable but generally lower expression, with concomitant increased phosphorylation of the MAST3 target, ARPP-16, compared to wildtype. These findings suggest the patient-specific variants may confer MAST3 gain-of-function. Moreover, single-nuclei RNA sequencing and immunohistochemistry shows that MAST3 expression is restricted to excitatory neurons in the cortex late in prenatal development and postnatally. InterpretationIn summary, we describe MAST3 as a novel epilepsy-associated gene with a potential gain-of-function pathogenic mechanism that may be primarily restricted to excitatory neurons in the cortex.

genetics↗

bioRxiv2020

Interactive machine learning for fast and robust cell profiling

Automatic profiling of cell morphology is a powerful tool for inferring cell function. However, this technique retains a high barrier to entry. In particular, configuring image processing parameters for optimal cell profiling is susceptible to cognitive biases and dependent on user experience. Here, we use interactive machine learning to identify the optimum cell profiling configuration that maximises quality of the cell profiling outcome. The process is guided by the user, from whom a rating of the quality of a cell profiling configuration is obtained. We use Bayesian optimisation, an established machine learning algorithm, to learn from this information and automatically recommend the next configuration to examine with the aim to maximize the quality of the processing or analysis. Compared to existing interactive machine learning tools that require domain expertise for per-class or per-pixel annotations, we rely on users explicit assessment of output quality of the cell profiling task at hand. We validated our interactive approach against the standard human trial-and-error scheme to optimise an object segmentation task using the standard software CellProfiler. Our toolkit enabled rapid optimisation of an object segmentation pipeline, increasing the quality of object segmentation over a pipeline optimised through trial-and-error. Users also attested to the ease of use and reduced cognitive load enabled by our machine learning strategy over the standard approach. We envision that our interactive machine learning approach can enhance the quality and efficiency of pipeline optimisation to democratise image-based cell profiling.

bioinformatics↗