Biology subjects

Sauter, T.

Publications and source records attributed to Sauter, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Accessing Enzyme Kinetic Data and Prediction Methods at Scale

Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at predictor.openkinetics.org), an open-source platform integrating thirteen methods in isolated environments behind one interface. The platform optionally reports similarity between query proteins and each method's training data to contextualise reliability. A common featurisation-prediction abstraction keeps it extensible, and independent parties, including original authors, contributed many methods. We pair it with a data portal (at data.openkinetics.org) that exposes CatLog, a curated kinetic dataset, with precomputed embeddings, predicted binding sites, and standardised splits. Both offer a web interface and an API, and the GECKO modelling toolbox already calls the predictor API. As a case study, we predict across an E. coli model and find inter-predictor agreement varies with metabolic context and data availability.

systems biology↗

bioRxiv2026

Identification of Parkinson's disease-associated regulatory variants in human dopaminergic neurons reveals modulators of SCARB2 and BAG3 expression

A hallmark of Parkinsons disease (PD) is the degeneration of midbrain dopaminergic neurons (mDANs). Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with PD, but causal variants and mechanisms remain unknown. Many PD-associated SNPs reside in regulatory regions, where they may disrupt transcription factor binding sites (TFBS) and alter gene expression. To assess how non-coding PD SNPs affect gene regulation in mDANs, we identify variants predicted to alter TF binding and functionally validate their effects in a cell type-specific context. We integrate time-series transcriptome and chromatin accessibility data from iPSC-derived neurons with chromatin topology and genetic variants. We profile 3D chromatin conformation in neuronal progenitors (smNPCs) and mDANs using LowC, identifying changes in A/B compartments and topologically associated domains. PD SNPs are enriched near genes expressed in mDANs, and we predict 254 regulatory variants that create or disrupt TFBS. Using chromatin conformation data, we link variants to target genes. At the BAG3 and SCARB2 loci, reporter assays in mDANs show reduced transcription driven by PD-associated alleles. Knock-down of NR2C2, a putative SCARB2 regulator, increases SCARB2 expression in differentiating neurons. The PD-associated SCARB2 allele shows reduced chromatin accessibility in mDANs and is associated with decreased expression in brain eQTL data. Insertion of PD-associated BAG3 allele by prime editing reduces chromatin accessibility across cell types, consistent with altered binding of LIM-homeodomain transcription factors. Together, these results prioritize functional PD SNPs and show that variants at SCARB2 and BAG3 modulate gene expression in mDANs, providing mechanistic insight into PD.

molecular biology↗

bioRxiv2026

FASTERCC: Accelerating Flux Consistency Testing and Context-Specific Reconstruction for Large-Scale Metabolic Network Models

The increase in size of metabolic network models especially with the advent of single-cell data calls for scalable reconstruction and analysis tools. Such models, often used for drug discovery and the analysis of microbial communities rely on consistency testing and reconstruction algorithms such as FASTCORE and FASTCC. However, with models nowadays comprising hundreds of thousands of reactions, the running times of such algorithms increased from few minutes to hours or days even with high performance computing. Experiments that require multiple reconstructions, such as parameter tuning or cross-validation, are practically infeasible in very large networks. Here we introduce FASTERCC, a new version of FASTCC, that leverages structural information for removing type I and II dead-ends, the orientation of reversible reactions and correcting the reversibility of reactions that are structurally incapable of carrying flux in both directions prior to any feasibility tests. These improvements reduce drastically the running time of FASTERCC by a median 20-fold speedup in comparison to FASTCC for networks with a larger number of block reactions. The model cleaning performed by FASTERCC also reduces the computational time of downstream analyses, notably of FASTCORE up to 50%.

systems biology↗

bioRxiv2026

K-Ras controls asymmetric cell divisions from the primary cilium

The Ras-MAPK pathway drives central cellular processes, including cell proliferation and differentiation. How exactly Ras controls differentiation is however not understood. Supported by mathematical modelling and single-cell RNA sequencing we show that K-Ras4B sustains ciliation during differentiation thus restricting commitment of skeletal muscle stem and progenitor cells during asymmetric cell divisions. Modulation of K-Ras4B abundance or expression of oncogenic K-Ras4B-G12C perturb normal differentiation. K-Ras4B, but not N-Ras and H-Ras, localizes to the primary cilium and its abundance there depends on the ciliary trafficking chaperone PDE6D. The presence of B-Raf and active MEK at the base of and active ERK inside the cilium suggests that K-Ras4B is active there. Conditions that localize a K-Ras4B mutant only to the cilium are sufficient to sustain ciliation and normal differentiation. Finally, in vivo modulation of K-Ras4B activity during zebrafish embryogenesis perturbs ciliation-dependent heart-looping. Our results thus imply a novel fundamental role of K-Ras4B in controlling ciliation and differentiation and suggest an explanation for the phenotypic similarities between RASopathies and ciliopathies.

cell biology↗

bioRxiv2025

ZFHX4 is necessary for dopaminergic neuron differentiation and controls cell cycle by regulating LIN28A

The selective degeneration of midbrain dopaminergic neurons (mDANs) is the main pathological hallmark of Parkinsons disease (PD). Although many transcription factors (TFs) guiding mDAN development have been identified, the details of the underlying regulatory networks remain elusive. We have previously generated time-series transcriptomic and epigenomic profiles of human induced pluripotent stem cell (hiPSC)-derived mDANs. Integrative analysis of the data identified ZFHX4 as a prominent super-enhancer-controlled TF induced in mDAN differentiation. ZFHX4 has been associated with neurodevelopmental processes in several species and shows reduced expression in midbrain of PD patients. Using in vitro knockdown (KD) and overexpression experiments, we show that ZFHX4 is necessary but not sufficient for mDAN differentiation. ZFHX4 binds preferentially at active promoter regions and transcriptomic analysis upon ZFHX4 depletion during mDAN differentiation revealed putative primary target genes to be enriched for targets of cell-cycle-related TFs and pathways. Consistently, ZFHX4-depleted cells accumulated in G2-phase of the cell cycle, preventing normal cell cycle progression and exit. The RNA-binding protein LIN28A, involved in stem-cell maintenance and microRNA (miRNA) maturation, emerged as one of the most upregulated genes upon ZFHX4-KD, in parallel with downregulation of neurogenic miRNA miR-9. Moreover, the LIN28A locus was enriched for ZFHX4 binding in CUT&Tag analysis. Taken together, our analysis indicates a pivotal role for ZFHX4 in regulating the cell cycle, specifically in silencing multipotency and proliferative programs, while maintaining mDANs in a post-mitotic state by controlling LIN28A-miR-9 axis.

molecular biology↗

bioRxiv2025

Changes in DNA methylation after trauma processing and meditation in a large group setting of 1.6 years duration (Timeless Wisdom Training)

Psychological trauma is associated with significant alterations of biological functions and is correlated with epigenetic changes specifically of DNA methylation. Trauma therapy is aiming at relieving the impact of trauma and is in initial studies also correlated with changes in DNA methylation. In this study we explored the changes in whole blood DNA methylation of participants of a program focusing on individual, ancestral and collective trauma processing and meditation in a large group setting of 1.6 years duration. Based on accompanying questionnaires, training participants report slight improvements in anxiety, depression and overall life satisfaction and some mystical experiences. 3227 CpGs and 253 genes were found to be differentially methylated during the training. Although these genes are not involving any of the known trauma related genes and relevant gene ontology terms, they comprise a large number of genes involved in the nervous function, as well as in cellular and developmental functions, the immune system and metabolism. Also, epigenetic aging is predicted to slow down during training. In summary this pilot study yielded additional findings showcasing the potential correlation of trauma therapy and alterations of DNA methylation.

genomics↗

bioRxiv2024

DJ-1 mediates regulation of metabolism and immune response in Parkinsons disease astrocytes and Glioblastoma cells

An inverse correlation for the expression of Parkinsons disease (PD)- and cancer-associated genes has been previously reported. Genes that are upregulated in cancer are frequently downregulated in PD and vice versa. PARK7, encoding DJ-1, was initially identified as an oncogene, but loss of DJ-1 causes early-onset PD. However, it remains elusive how differential DJ-1 levels contribute to opposite cell fates in cancer and PD. Here, we demonstrate specific effects of differential DJ-1 protein levels on the energy metabolism and cell growth in patient-derived cellular models of PD and glioblastoma (GBM) cell lines. Impaired energy metabolism was associated with an increased immune response upon IL-1{beta} stimulation and increased apoptosis and decreased cell growth in models of PD, whereas in GBM cells increased metabolic activity translated into a reduced immune response and increased cell growth. Furthermore, we found decreased glutathione (GSH) synthesis and therefore increased levels of reactive oxygen species (ROS) and oxidized glutathione (GSSG) in models of DJ-1 deficiency and decreased ROS levels in GBM cell lines. Thus, the mechanism by which DJ-1 modulates these phenotypes is the same in both diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/621212v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@4eccb4org.highwire.dtl.DTLVardef@161669corg.highwire.dtl.DTLVardef@197bfc3org.highwire.dtl.DTLVardef@1aecb36_HPS_FORMAT_FIGEXP M_FIG C_FIG DJ-1 levels modulate GSSG/GSH ratio and ROS levels, which results in divergent effects on cell growth and immune response in DJ-1-dependent glial pathologies in glioblastoma and PD. In models of PD, DJ-1 level dependent phenotypes can be rescued by antioxidant treatment that reduces the GSSG/GSH ratio and ROS levels.

neuroscience↗

bioRxiv2024

Data-driven inference of Boolean networks from transcriptomes to predict cellular differentiation and reprogramming

Boolean networks provide robust explainable and predictive models of cellular dynamics, especially for cellular differentiation and fate decision processes. Yet, the construction of such models is extremely challenging, as it requires integrating prior knowledge with experimental observation of transcriptome, potentially relating thousands of genes. We present a general methodology, implemented in the software tool BoNesis, for the qualitative modeling of gene regulation behind the observed state changes from transcriptome data and prior knowledge of the gene regulatory network. BoNesis allows computing ensembles of Boolean networks, where each of them is able to reproduce the modeled differentiation process. We illustrate the scalability and versatility of BoNesis with two applications: the modeling of hematopoiesis from single-cell RNA-Seq data, and modeling the differentiation of bone marrow stromal cells into adipocytes and osteoblasts from bulk RNA-seq time series data. For this later case, we took advantage of ensemble modeling to predict combinations of reprogramming factors for trans-differentiation that are robust to model uncertainties due to variations in experimental replicates and choice of binarization method. Moreover, we performed an in silico assessment of the fidelity and efficiency of the reprogramming, and conducted preliminary experimental validation.

systems biology↗

bioRxiv2024

Circadian clock features define novel breast cancer subtypes and shape drug sensitivity

The circadian clock regulates key physiological processes, including cellular responses to DNA damage. Circadian-based therapeutic strategies optimize treatment timing to enhance drug efficacy and minimize side effects, offering potential for precision cancer treatment. However, applying these strategies in cancer remains limited due to limited understanding of the clocks function across cancer types and incomplete insights into how the circadian clock affects drug responses. To address this, we conducted deep circadian phenotyping across a panel of breast cancer cell lines using two complementary reporters. Observing diverse circadian dynamics, we developed metrics to assess circadian rhythm strength and stability. This led to the identification of four distinct circadian-based phenotypes in breast cancer: functional, weak, unstable, and dysfunctional clocks. Furthermore, we demonstrate that the circadian clock plays a critical role in shaping pharmacological responses to various anti-cancer drugs and identify circadian features that accurately predict drug sensitivity. Collectively, our findings establish a foundation for advancing the use of chronotherapeutic strategies in breast cancer treatment, expanding their potential application to improve therapeutic outcomes in breast cancer.

cancer biology↗

bioRxiv2024

Epigenetic control of metabolic identity across cell types

BackgroundConstraint-based network modeling is a powerful genomic-scale approach for analyzing cellular metabolism, capturing metabolic variations across tissues and cell types, and defining the metabolic identity essential for identifying disease-associated transcriptional states. ResultsUsing RNA-seq and epigenomic data from the EpiATLAS resource of the International Human Epigenome Consortium (IHEC), we reconstructed metabolic networks for 1,555 samples spanning 58 tissues and cell types. Analysis of these networks revealed the distribution of metabolic functionalities across human cell types and provides a compendium of human metabolic activity. This integrative approach allowed us to define, across tissues and cell types, i) reactions that fulfil the basic metabolic processes (core metabolism), and ii) cell type-specific functions (unique metabolism), that shape the metabolic identity of a cell or a tissue. Integration with EpiATLAS-derived cell-type-specific gene-level chromatin states and enhancer-gene interactions identified enhancers, transcription factors, and key nodes controlling core and unique metabolism. Transport and first reactions of pathways were enriched for high expression, active chromatin state, and Polycomb-mediated repression in cell types where pathways are inactive, suggesting that key nodes are targets of repression. DiscussionThis integrative analysis forms the basis for identifying regulation points that control metabolic identity in human cells.

systems biology↗

bioRxiv2024

Park7 deletion leads to age- and sex-specific transcriptome changes involving NRF2-CYP1B1 axis in mouse midbrain astrocytes

AbstractdispeLoss-of-function mutations in PARK7, encoding for DJ-1, can lead to early onset Parkinsons disease (PD). In mice, Park7 deletion leads to dopaminergic deficits during aging, and increased sensitivity to oxidative stress. However, the severity of the reported phenotypes varies. To understand the early molecular changes upon loss of DJ-1, we performed transcriptomic profiling of midbrain sections from young mice. Interestingly, while at 3 months the transcriptomes of both male and female mice were unchanged compared to their wildtype littermates, an extensive deregulation was observed specifically in 8-month-old males. The affected genes are involved in processes such as focal adhesion, extracellular matrix interaction, and epithelial-to-mesenchymal transition (EMT), and enriched for primary target genes of Nuclear factor erythroid 2-related factor 2 (NRF2). Consistently, the antioxidant response was altered specifically in the midbrain of male DJ-1 deficient mice. Many of the misregulated genes are known target genes of estrogen and retinoic acid signaling and show sex-specific expression in wildtype mice. Depletion of DJ-1 or NRF2 in male, but not female primary astrocytes recapitulated many of the in vivo changes, including downregulation of cytochrome P450 family 1 subfamily B member 1 (CYP1B1), an enzyme involved in estrogen and retinoic acid metabolism. Interestingly, knock-down of CYP1B1 led to gene expression changes in focal adhesion and EMT in primary male astrocytes. Finally, male iPSC-derived astrocytes with loss of function mutation in the PARK7 gene also showed changes in the EMT pathway and NRF2 target genes. Taken together, our data indicate that loss of Park7 leads to sex-specific gene expression changes specifically in males through astrocytic alterations in the NRF2-CYP1B1 axis. These findings suggest higher sensitivity of males to loss of DJ-1 and might help to better understand variation in the reported Park7-/-phenotypes.

molecular biology↗

bioRxiv2023

Time-of-day effects of drugs revealed by high-throughput deep phenotyping

The circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a novel high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devised a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.

cancer biology↗

bioRxiv2023

Cell-type-specific characterization of miRNA gene dynamics in immune cell subpopulations during aging and atherosclerosis disease development at single-cell resolution

MicroRNAs (miRNAs) are a class of regulatory non-coding RNAs that finetune cellular functions by modulating the stability and abundance of their target mRNAs, thereby contributing to regulation of tissue homeostasis. MiRNA genes are transcribed similarly to protein-coding genes and recent studies have enabled their annotation and quantification genome-wide from bulk nascent transcriptomes. Here, we developed an approach to quantify and integrate miRNA gene signatures into single-cell studies. To characterize miRNA gene expression dynamics, we first compared the suitability of droplet and plate-based single-cell RNA-sequencing (scRNA-seq) platforms using the matched datasets provided by the Tabula Muris Senis and Tabula Sapiens consortiums. We found high concordance between the platforms and with cell type-specific bulk expression data. Based on the comprehensive aging profiles, our analysis comparing spleen immune cells between young and old mice revealed a concordant regulation of miRNAs involved in senescence and inflammatory pathways in multiple immune cell types, including up-regulation of mmu-mir-146a, mmu-mir-101a and mmu-mir-30 family genes. To study the aberrant regulation of immune cell homeostasis and tissue inflammation that pre-dispose to aging-related disease development, we collected transcriptome profiles from atherosclerosis development in LDLR-/-ApoB100/100 mice. We found an elevated myeloid cell proportion in the adipose tissue and further characterized the cell subtypes based on reproducible transcriptome clusters. We then compared miRNA gene expression in early versus late disease and upon inflammatory challenge to monitor different stages during disease progression. At atherosclerotic stage, pro-inflammatory mmu-mir-511 expression increased in several macrophage subtypes, while immunosuppressive mmu-mir-23b[~]mir-24-2[~]mir-27b up-regulation was specific to Trem2+ lipid-associated macrophages. The infiltrating monocytes up-regulated mmu-mir-1938 and mmu-mir-22 expression and in classical monocytes maturation further increased mmu-mir-221[~]222, mmu-mir-511 and mmu-mir-155 expression. To validate that these changes detected from single cell profiles represent miRNA gene transcriptional regulation, we used nascent transcriptomics data from ex vivo macrophage cultures with pro-inflammatory stimulation, confirming both rapid and long-lasting transcriptional activation of the miRNA loci studied. Collectively, our work enables integrating miRNA gene analysis to current single cell genomics pipelines and facilitates characterization of miRNA regulatory networks during aging and disease development.

molecular biology↗

bioRxiv2023

Multi-omics analysis identifies LBX1 and NHLH1 as central regulators of human midbrain dopaminergic neuron differentiation

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior under physiological conditions and are implicated in human diseases such as Parkinsons disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation during development have been described, but much of the regulatory landscape remains undefined. Using a tyrosine hydroxylase (TH) iPSC reporter line, we have generated time series transcriptomic and epigenomic profiles of purified mDANs during differentiation. Integrative analysis predicted novel central regulators of mDAN differentiation and super-enhancers were used to prioritize key TFs. We find LBX1, NHLH1 and NR2F1/2 to be necessary for mDAN differentiation and show that overexpression of either LBX1 or NHLH1 can also improve mDAN specification. NHLH1 is necessary for the induction of neuronal miR-124, while LBX1 regulates cholesterol biosynthesis, possibly through mTOR signaling. Consistently, rapamycin treatment led to an inhibition of mDAN differentiation. Thus, our work reveals novel regulators of human mDAN differentiation.

genomics↗

bioRxiv2022

Integration of external biomass reactions into existing metabolic models

Currently, seven biomass objective functions have been defined in human metabolic reconstructions. The integration of published biomass reactions into alternative models can contribute to the prediction power of the model. Thus, in this work, we present a workflow to integrate reactions and biomass functions originating from several genome-scale reconstructions into models other than their home models. Additionally, a benchmark to identify the biomass that confers the highest prediction accuracy in terms of gene essentiality and growth predictions is provided. For complete details on the use and execution of this protocol, please refer to Moscardo Garcia et al. (2021).

systems biology↗

bioRxiv2020

The IRE1 Inhibitor KIRA6 Curtails The Inflammatory Trait Of Immunogenic Anticancer Treatments By Targeting HSP60 Independent Of IRE1

Cellular stress evoked by immunogenic anticancer treatments engaging the unfolded protein response (UPR) can elicit inflammation with conflicting therapeutic outcomes. To define cell-autonomous mechanisms coupling the UPR to molecular mediators of inflammation, we profiled the transcriptome of cancer cells responding to immunogenic or weakly immunogenic-treatments. Bioinformatics-driven pathway analysis indicated that immunogenic treatments instigated NF-{kappa}B/AP-1-inflammatory pathways, which were abolished by the IRE1-kinase inhibitor KIRA6. Cell-free fractions of chemotherapy and KIRA6 co-treated cancer cells were deprived of pro-inflammatory/chemoattractant factors and failed to mobilize innate immune cells. Strikingly, these potent KIRA6 anti-inflammatory effects were found to be independent of IRE1. Generation of a KIRA6-clickable photoaffinity probe, mass spectrometry and co-immunoprecipitation analysis identified cytosolic HSP60 as a KIRA6 off-target in the NF-{kappa}B pathway. In sum, our study unravels that inflammation evoked by immunogenic treatments is curtailed by KIRA6 independently of IRE1 and further suggests great caution in interpreting the anti-inflammatory action of IRE1 chemical inhibitors.

cancer biology↗

bioRxiv2020

Quantitative trait locus mapping identifies Col4a6 as a novel regulator of striatal dopamine level and axonal branching in mice.

The features of dopaminergic neurons (DAns) of nigrostriatal circuitry are orchestrated by a multitude of yet unknown factors, many of them genetic. Genetic variation between individuals at baseline can lead to differential susceptibility to and severity of diseases. As decline of DAns, a characteristic of Parkinsons disease, heralds a significant decrease in dopamine level, measuring dopamine can reflect the integrity of DAns. To identify novel genetic regulators of the integrity of DAns, we used the Collaborative Cross (CC) mouse strains as model system to search for quantitative trait loci (QTLs) related to dopamine levels in the dorsal striatum. The dopamine levels in dorsal striatum varied greatly in the eight CC founder strains, and the differences were inheritable in 32 derived CC strains. QTL mapping in these CC strains identified a QTL associated with dopamine level on chromosome X containing 393 genes. RNA-seq analysis of the ventral midbrain of two of the founder strains with large striatal dopamine difference (C57BL/6J and A/J) revealed 24 differentially expressed genes within the QTL. The protein-coding gene with the highest expression difference was Col4a6, which exhibited a 9-fold reduction in A/J compared to C57BL/6J, consistent with decreased dopamine levels in A/J. Publicly available single cell RNA-seq data from developing human midbrain suggests that Col4a6 is highly expressed in radial glia-like cells and neuronal progenitors, indicating possible involvement in neurogenesis. Interestingly, the lowered dopamine levels were accompanied by reduced striatal axonal branching of striatal DAns in A/J compared to C57BL/6J. Because Col4a6 is known to control axogenesis in non-mammal model organisms, we hypothesize that different dopamine levels in mouse dorsal striatum are due to differences in axogenesis induced by varying COL4A6 levels during neural development.

neuroscience↗

bioRxiv2020

Single nuclei chromatin profiles of ventral midbrain reveal cell identity transcription factors and cell type-specific gene regulatory variation

Cell types in ventral midbrain are involved in diseases with variable genetic susceptibility such as Parkinsons disease and schizophrenia. Many genetic variants affect regulatory regions and alter gene expression. We report 20 658 single nuclei chromatin accessibility profiles of ventral midbrain from two genetically and phenotypically distinct mouse strains. We distinguish ten cell types based on chromatin profiles and analysis of accessible regions controlling cell identity genes highlights cell type-specific key transcription factors. Regulatory variation segregating the mouse strains manifests more on transcriptome than chromatin level. However, cell type-level data reveals changes not captured at tissue level. To discover the scope and cell-type specificity of cis-acting variation in midbrain gene expression, we identify putative regulatory variants and show them to be enriched at differentially expressed loci. Finally, we find TCF7L2 to mediate trans-acting variation selectively in midbrain neurons. Our dataset provides an extensive resource to study gene regulation in mesencephalon.

genomics↗