A CutFEM Method for a Mechanistic Modelling of Astrocytic Metabolism in 3D Physiological Morphologies

Scientific Conference (2022, June 07)

Investigating neurodegenerative diseases can be done complementary through biological and computational experiments. A good computational approach describing a simplification of the reality and focusing ... [more ▼]

Investigating neurodegenerative diseases can be done complementary through biological and computational experiments. A good computational approach describing a simplification of the reality and focusing only on some features of the problem can help getting insights on the field. The question addressed in our work is the role of astrocytes in neurodegeneration. These cells have two interesting characteristics that we want to investigate in our model: first, their role as metabolic mediator between neurons and blood vessels and second, their peculiar morphology. In fact, metabolic dysfunctions and morphological changes have been noticed in astrocyte affected by neuropathology. Computationally the main difficulty arising from solving a metabolic model into cellular shape comes from the complexity of the domain. The shape of astrocytes are very ramified, with thin branches and sharp edges. As shown in our previous work \cite{Farina}, a \cutfem{} \cite{Burman} approach is a suitable tool to deal with this issue. In our latest work we use real human three-dimensional astrocyte morphologies obtained via microscopy \cite{Salamanca} as domain to solve our system. The performed simulations highlight the effect of morphological changes on the system output. Suggesting that our model can be crucial in understanding the morphological-dependency in neuropathologies and that the spatial component cannot be neglected. [less ▲]

Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis

in Science of the Total Environment (2022), 827

Continuous surveillance of COVID-19 diffusion remains crucial to control its diffusion and to anticipate infection waves. Detecting viral RNA load in wastewater samples has been suggested as an effective ... [more ▼]

Continuous surveillance of COVID-19 diffusion remains crucial to control its diffusion and to anticipate infection waves. Detecting viral RNA load in wastewater samples has been suggested as an effective approach for epidemic monitoring and the development of an effective warning system. However, its quantitative link to the epidemic status and the stages of outbreak is still elusive. Modelling is thus crucial to address these challenges. In this study, we present a novel mechanistic model-based approach to reconstruct the complete epidemic dynamics from SARS-CoV-2 viral load in wastewater. Our approach integrates noisy wastewater data and daily case numbers into a dynamical epidemiological model. As demonstrated for various regions and sampling protocols, it quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. Following its quantitative analysis, we also provide recommendations for wastewater data standards and for their use as warning indicators against new infection waves. In situations of reduced testing capacity, our modelling approach can enhance the surveillance of wastewater for early epidemic prediction and robust and cost-effective real-time monitoring of local COVID-19 dynamics. [less ▲]

Buffering variability in cell regulation motifs close to criticality

in Physical Review. E. (2022)

Bistable biological regulatory systems need to cope with stochastic noise to fine tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to ... [more ▼]

Bistable biological regulatory systems need to cope with stochastic noise to fine tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative interactions buffer system variability, hampering noise-induced regime shifts. Our analysis also shows that, in the considered cooperativity range, impending regime shifts can be generically detected by statistical early warning signals from distributional data. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality. [less ▲]

Single-cell transcriptomics of human iPSC differentiation dynamics reveal a core molecular network of Parkinson’s disease

in Communications Biology (2022), 5(1), 1--19

Parkinson’s disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly ... [more ▼]

Parkinson’s disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly understood and there is no treatment to reverse PD progression. Here, we investigated the disease mechanism using mDA neurons differentiated from human induced pluripotent stem cells (hiPSCs) carrying the ILE368ASN mutation within the PINK1 gene, which is strongly associated with PD. Single-cell RNA sequencing (RNAseq) and gene expression analysis of a PINK1-ILE368ASN and a control cell line identified genes differentially expressed during mDA neuron differentiation. Network analysis revealed that these genes form a core network, members of which interact with all known 19 protein-coding Parkinson’s disease-associated genes. This core network encompasses key PD-associated pathways, including ubiquitination, mitochondrial function, protein processing, RNA metabolism, and vesicular transport. Proteomics analysis showed a consistent alteration in proteins of dopamine metabolism, indicating a defect of dopaminergic metabolism in PINK1-ILE368ASN neurons. Our findings suggest the existence of a network onto which pathways associated with PD pathology converge, and offers an inclusive interpretation of the phenotypic heterogeneity of PD. [less ▲]

3D Modelling of a Spatially Resolved Energy Metabolism in Physiological Astrocytic Morphology

Scientific Conference (2022)

Astrocytes, the most abundant cell in the central nervous system, have a star-shaped morphology and play a central role in brain homeostasis as metabolic mediators between neurons and blood vessels ... [more ▼]

Astrocytes, the most abundant cell in the central nervous system, have a star-shaped morphology and play a central role in brain homeostasis as metabolic mediators between neurons and blood vessels. Recent evidence put astrocytes therefore in the focus of neurodegeneration (ND), since in case of metabolic dysfunctions as e.g. observed in Alzheimer’s disease or Parkinson’s disease, they cannot provide neurons with sufficient amount of nutrients. Furthermore, progression of ND is often accompanied by changes in astrocytic morphology further indicating the essential role of astrocytes in the brain. Despite its importance, the complex astrocytic morphology is often neglected in modelling of metabolic reactions [1]. In this study, we propose a computational model that describes cellular metabolism through a reaction-diffusion system including two fundamental pieces of information: the intracellular spatial arrangement of the reaction sites and the real, complex geometries by using the previously developed method CutFEM([2][3]). Our findings show how intracellular spatial organisation and diffusion limitation as well as the physio- logical cell shape must be taken into account to go towards biological models that are closer to reality. In particular, the spatial distribution of mitochondria notably impacts the cellular ATP : ADP ratio, which is an indicator of the energetic state of the cell. Finally, we solve our system in a 3D human astrocytic morphology and study the different spatial arrangements of the reaction sites simulating physiological and dysfunctional behaviour. In this regard, we believe, that the proposed model is a useful instrument to gain insights into the role astrocytes play in neurodegeneration. [less ▲]

Stress hormone signalling inhibits Th1 polarization in a CD4 T-cell-intrinsic manner via mTORC1 and the circadian gene PER1

in Immunology (2022), 165(4), 428--444

Stress hormones are believed to skew the CD4 T-cell differentiation towards a Th2 response via a T-cell-extrinsic mechanism. Using isolated primary human naïve and memory CD4 T cells, here we show that ... [more ▼]

Stress hormones are believed to skew the CD4 T-cell differentiation towards a Th2 response via a T-cell-extrinsic mechanism. Using isolated primary human naïve and memory CD4 T cells, here we show that both adrenergic- and glucocorticoid-mediated stress signalling pathways play a CD4 naïve T-cell-intrinsic role in regulating the Th1/Th2 differentiation balance. Both stress hormones reduced the Th1 programme and cytokine production by inhibiting mTORC1 signalling via two parallel mechanisms. Stress hormone signalling inhibited mTORC1 in naïve CD4 T cells (1) by affecting the PI3K/AKT pathway and (2) by regulating the expression of the circadian rhythm gene, period circadian regulator 1 (PER1). Both stress hormones induced the expression of PER1, which inhibited mTORC1 signalling, thus reducing Th1 differentiation. This previously unrecognized cell-autonomous mechanism connects stress hormone signalling with CD4 T-cell differentiation via mTORC1 and a specific circadian clock gene, namely PER1. [less ▲]

COVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach

in Economics and Human Biology (2021), 43

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg ... [more ▼]

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021. [less ▲]

Single‑nuclei chromatin profiling of ventral midbrain reveals cell identity transcription factors and cell‑type‑specific gene regulatory variation

in Epigenetics and Chromatin (2021)

Background: Cell types in ventral midbrain are involved in diseases with variable genetic susceptibility, such as Parkinson’s disease and schizophrenia. Many genetic variants affect regulatory regions and ... [more ▼]

Background: Cell types in ventral midbrain are involved in diseases with variable genetic susceptibility, such as Parkinson’s disease and schizophrenia. Many genetic variants affect regulatory regions and alter gene expression in a cell-type-specific manner depending on the chromatin structure and accessibility. Results: 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. Conclusions: Our data set provides an extensive resource to study gene regulation in mesencephalon and provides insights into control of cell identity in the midbrain and identifies cell-type-specific regulatory variation possibly underlying phenotypic and behavioural differences between mouse strains. [less ▲]

Mechanistic modelling of astrocytic metabolism in physiological geometries reveals spatiotemporal effects potentially driving neurodegeneration

Presentation (2021, May)

A cut finite element method for spatially resolved energy metabolism models in complex neuro-cell morphologies with minimal remeshing

in Advanced Modeling and Simulation in Engineering Sciences (2021), 8

A thorough understanding of brain metabolism is essential to tackle neurodegenerative diseases. Astrocytes are glial cells which play an important metabolic role by supplying neurons with energy. In ... [more ▼]

A thorough understanding of brain metabolism is essential to tackle neurodegenerative diseases. Astrocytes are glial cells which play an important metabolic role by supplying neurons with energy. In addition, astrocytes provide scaffolding and homeostatic functions to neighboring neurons and contribute to the blood–brain barrier. Recent investigations indicate that the complex morphology of astrocytes impacts upon their function and in particular the efficiency with which these cells metabolize nutrients and provide neurons with energy, but a systematic understanding is still elusive. Modelling and simulation represent an effective framework to address this challenge and to deepen our understanding of brain energy metabolism. This requires solving a set of metabolic partial differential equations on complex domains and remains a challenge. In this paper, we propose, test and verify a simple numerical method to solve a simplified model of metabolic pathways in astrocytes. The method can deal with arbitrarily complex cell morphologies and enables the rapid and simple modification of the model equations by users also without a deep knowledge in the numerical methods involved. The results obtained with the new method (CutFEM) are as accurate as the finite element method (FEM) whilst CutFEM disentangles the cell morphology from its discretisation, enabling us to deal with arbitrarily complex morphologies in two and three dimensions. [less ▲]