Fabian Spill

The mitochondrial dicarboxylate carrier SLC25A10 mediates reversible exchange among succinate, malate, and phosphate, contributing to mitochondrial metabolic regulation. Structural studies establish a ping–pong mechanism, but most mathematical models still assume sequential binding, lacking mechanistic justification and overlooking the alternation of a single binding site. Here, we present the first mechanistically derived and thermodynamically consistent model of SLC25A10 based on a ping–pong framework. The model incorporates competitive binding of succinate, malate, and phosphate, heteroexchange, reversibility, and electroneutrality, and is calibrated using experimental datasets from intact mitochondria and reconstituted proteoliposomes. To estimate kinetic parameters and quantify their uncertainty, we employed Bayesian inference, enabling statistically rigorous calibration to uptake and competition assays. The model introduces new terms that quantify which substrate and from which side of the membrane is most likely to start the transport cycle. Beyond reproducing experimentally observed exchange kinetics, the model resolves non-equilibrium transport dynamics that are difficult to access directly in classical uptake assays. In particular, the simulations reveal a two-phase response in which an initial phosphate-driven high-flux uptake regime for malate and succinate is followed by a slower redistribution phase in which the two dicarboxylates continue to readjust primarily against each other. The model also predicts that mitochondrial morphology modulates early transport behaviour, with matrix swelling increasing and matrix condensation decreasing the initial SLC25A10 flux magnitude. More broadly, the framework provides a quantitative basis for studying how substrate competition, thermodynamic driving forces, and compartment geometry shape SLC25A10-mediated exchange, and it offers a transferable modelling strategy for other carriers in the SLC25 family.

The coupling between evolutionary and ecological changes (eco-evolutionary dynamics) has been shown to be relevant among diverse species, and is also of interest outside of ecology, i.e. in cancer evolution. These dynamics play an important role in determining survival in response to climate change, motivating the need for mathematical models to capture their complex interplay. Models incorporating eco-evolutionary dynamics often sacrifice analytical tractability to capture the complexity of real systems, do not explicitly consider the effect of population heterogeneity, or focus on long-term behaviour. In order to capture population heterogeneity, both transient, and long-term dynamics, while retaining tractability, we generalise a moment-based method applicable in the regime of small segregational variance to the case of time-dependent mortality and birth. These results are applied to a predator-prey model, where ecological parameters such as the contact rate between species are trait-structured. The trait-distribution of the prey species is shown to be approximately Gaussian with constant variance centered on the mean trait, which is asymptotically governed by an autonomous ODE. In this way, we make explicit the impact of eco-evolutionary dynamics on the transient behaviour and long-term fate of the prey species.

Background Seronegative hepatitis (SNH) is an acute fulminant liver injury which leads to liver failure, requiring urgent transplantation. Its clinical, biochemical, and histological features mimic autoimmune hepatitis (AIH). SNH aetiology and pathogenesis is unknown thus defining triggers and immune pathways is essential for timely diagnosis and effective treatment. Methods We applied multi-modal spatial transcriptomics, combining CosMx™ single-cell resolution with Visium whole-transcriptome profiling, to SNH, AIH and healthy donor explant liver tissue. Data were integrated with meta-transcriptomics and multiplex imaging on the same tissues to identify disease-specific signatures. Results SNH livers displayed a significant expansion of macrophages enriched for interferon-stimulated genes ( MX1, ISG15, OAS1, IFIT3 ), compared to AIH. MX1⁺hepatocytes were also uniquely expanded in SNH. Meta-transcriptomic profiling of matched livers revealed transcriptional upregulation of human endogenous retroviruses (HERVs), including HERV-K, in SNH and AIH livers but absent in donor livers. HERV-K protein was detected in SNH by tissue staining, implicating viral aetiology as a potential immune trigger. Furthermore, SNH was distinguished by CD63 upregulation and selective activation of the LIGHT-HVEM pathway between macrophages and hepatocytes. Conclusions Multi-modal spatial profiling reveals that SNH is transcriptionally and immunologically distinct from classical AIH, with evidence for viral-associated immune activation driving severe liver injury.

We study the long time behaviour of a non-local parabolic integro-differential equation modelling the evolutionary dynamics of a phenotypically-structured population in a changing environment. Such models can arise in variety of contexts from climate change to chemotherapy to the ageing body. The main novelty is that there are two locally optimal traits, each of which shifts at a possibly different linear velocity. We determine sufficient conditions to guarantee extinction or persistence of the population in terms of associated eigenvalue problems. When the population does not go extinct, we study the behaviour of long time solutions in the case of rare mutations: the long time solution concentrates as a sum of Dirac masses on a point set of "lagged optima" which are strictly behind the true shifting optima as the mutation rate goes to zero. If we further assume the shift velocities are different, we show the solution concentrates specifically on the positive lagged optimum with maximum lagged fitness. Our results imply that for populations undergoing competition in temporally changing environments, both the true optimal fitness and the required rate of adaptation for each of the diverging optimal traits determine the eventual dominance of one trait.

The extracellular matrix (ECM) is a complex network of fibrous proteins and other macromolecules that provides both structural support and directional cues that regulate cancer cell invasion and tumour progression. Its fibre organisation plays a critical role in directing migration through contact guidance, while cancer cells simultaneously remodel the matrix through biochemical and mechanical interactions. However, the interplay between ECM architecture, chemical gradients, and matrix remodelling remains poorly understood. Mathematical modelling offers a powerful approach to explore how ECM architecture regulates this process. We present a hybrid computational model, implemented in PhysiCell, that integrates a discrete agent-based cell model with a continuous representation of the chemical microenvironment and ECM microstructure. In an advance over previous efforts, we adapt several mechanisms to a fibre-focused representation of the ECM, including “cell-front” ECM sensing reflecting protrusion-driven engagement of the matrix, contact-guided cell movement via ECM fibre orientation integrated with chemotaxis bias, and proliferation regulated by oxygen and mechanical pressure. In addition, we introduce a new mechanical mechanism for ECM density displacement alongside degradation to simulate how cells redistribute matrix fibres. Simulations reveal how the interplay between initial fibre alignment, anisotropy (fibre-fibre alignment correlation), and fibre reorientation capacity affects invasion, and how competing mechanical and chemical cues influence the invasive potential of tumour cells. Furthermore, our results demonstrate that the balance between degradation and displacement strongly affects invasion dynamics, with high displacement promoting the formation of dense ECM rims around tumour spheroids, whereas increased degradation enables greater invasive spread. This work provides mechanistic insights into bidirectional interactions between cancer cells and the surrounding ECM, highlighting how structural remodelling of the ECM influences the invasive potential of cancer cells. Author summary: Cancer cells invade surrounding tissue by interacting with the extracellular matrix (ECM), a fibrous network of proteins that provides both mechanical support and directional cues for migration. Experiments have shown that the orientation of ECM fibres can either promote or hinder invasion, but it remains difficult to disentangle the underlying mechanisms because cells both respond to and actively remodel the matrix. To address this challenge, we developed a computational model that simulates how cancer cells migrate through and reshape the ECM. The model combines individual cell behaviour with a representation of ECM structure, including fibre orientation, anisotropy (fibre-fibre alignment correlation), and density. Our simulations show that invasion depends on the initial fibre orientation and on chemical cues. We also introduce a mechanism that allows cells to mechanically displace the matrix, revealing how the balance between matrix degradation and physical pushing can generate either compact tumour growth or sparse invasion. These results help explain how physical interactions between cells and their environment shape tumour invasion. More broadly, the framework provides a tool to explore how mechanical and chemical signals together regulate collective cell migration in cancer and other biological systems.

From single-cell extrusion to centimetre-sized wounds, epithelial gaps of various sizes and geometries appear across organisms. Their closure involves two orthogonal modes: lamellipodial crawling at convex edges and purse string-like movements at concave edges. The mechanisms driving this curvature-dependent migration remain unclear. Here we perform an intracellular cartography to reveal that in both micropatterned and naturally arising gaps, the endoplasmic reticulum (ER) undergoes edge curvature-dependent morphological reorganizations, forming tubules at convex edges and sheets at concave edges. This reorganization depends on cytoskeleton-generated protrusive and contractile forces. Mathematical modelling reveals that these morphologies minimize strain energy under their respective geometric regime. Functionally, ER tubules at the convex edge favour perpendicularly oriented focal adhesions, supporting lamellipodial crawling, while ER sheets at the concave edge favour parallelly oriented focal adhesions, supporting purse string-like movements. Altogether, ER emerges as a central mechanotransducer, integrating signals from cytoskeletal networks to orchestrate two orthogonal modes of cell migration.

Ectopic lymphoid structures (ELS) are aggregates of lymphoid cells that often form within inflamed tissues in patients with autoimmune diseases, cancer, infectious diseases and cardiovascular conditions. These structures drive B cell maturation into memory B cells and plasma cells through B cell and T cell co-stimulation, and their role in pathogenesis is increasingly recognized. Understanding how ELS develop and persist in inflamed tissues is essential for elucidating the pathogenesis and treatment responses in diseases in which they have a prominent role. Here we show that metabolic pathways and specific metabolites, in particular lactate, are master regulators of ELS organization in Sjögren’s disease (SjD), the second-most common autoimmune rheumatic disease. Furthermore, inhibiting lactate uptake by lactate transporters, specifically by SLC5A12 blockade, represents a previously unappreciated checkpoint in autoimmune inflammatory diseases. This approach results in multidimensional pro-resolution effects, including reduced inflammatory cytokine levels, enhanced T cell egress from inflamed sites and diminished T cell and B cell areas and their segregation within ELS.

From single-cell extrusion to centimeter-sized wounds, epithelial gaps of various sizes and geometries appear in all organisms. For gap closure, epithelial cells invoke two orthogonal modes: lamellipodial crawling at the convex edge and purse-string-like movements at the concave edge. The mechanisms underlying these differential responses to geometric cues remain elusive. Here we perform an intracellular cartography to reveal that in both micropatterned and naturally arising gaps, the endoplasmic reticulum (ER) undergoes edge curvature-dependent morphological reorganizations with convex and concave edges promoting ER tubules and sheets, respectively. This reorganization depends on cytoskeleton-generated protrusive and contractile forces. Additionally, theoretical modeling predicts that the curvature-specific ER morphology leads to a lower strain energy state. ER tubules at the convex edge favor perpendicularly oriented focal adhesions, supporting lamellipodial crawling while ER sheets at the concave edge favor parallelly oriented focal adhesions, supporting purse-string-like movements. Altogether, ER emerges as a central player in cellular mechanotransduction, which orchestrates two orthogonal modes of cell migration by integrating signals from cytoskeletal networks.