Hurricanes enhance coral connectivity but also superspread coral diseases.

Climate change poses an existential threat to coral reefs. A warmer and more acidic ocean weakens coral ecosystems and increases the intensity of hurricanes. The wind-wave-current interactions during a hurricane deeply change the ocean circulation patterns and hence potentially affect the dispersal of coral larvae and coral disease agents. Here, we modeled the impact of major hurricane Irma (September 2017) on coral larval and stony coral tissue loss disease (SCTLD) connectivity in Florida's Coral Reef. We coupled high-resolution coastal ocean circulation and wave models to simulate the dispersal of virtual coral larvae and disease agents between thousands of reefs. While being a brief event, our results suggest the passage of hurricane Irma strongly increased the probability of long-distance exchanges while reducing larval supply. It created new connections that could promote coral resilience but also probably accelerated the spread of SCTLD by about a month. As they become more intense, hurricanes' double-edged effect will become increasingly pronounced, contributing to increased variability in transport patterns and an accelerated rate of change within coral reef ecosystems.

Dynamics and predicted drug response of a gene network linking dedifferentiation with beta-catenin dysfunction in hepatocellular carcinoma.

BACKGROUND & AIMS: Alterations of individual genes variably affect the development of hepatocellular carcinoma (HCC). Thus, we aimed to characterize the function of tumor-promoting genes in the context of gene regulatory networks (GRNs). METHODS: Using data from The Cancer Genome Atlas, from the LIRI-JP (Liver Cancer - RIKEN, JP project), and from our transcriptomic, transfection and mouse transgenic experiments, we identify a GRN which functionally links LIN28B-dependent dedifferentiation with dysfunction of ß-catenin (CTNNB1). We further generated and validated a quantitative mathematical model of the GRN using human cell lines and in vivo expression data. RESULTS: We found that LIN28B and CTNNB1 form a GRN with SMARCA4, Let-7b (MIRLET7B), SOX9, TP53 and MYC. GRN functionality is detected in HCC and gastrointestinal cancers, but not in other cancer types. GRN status negatively correlates with HCC prognosis, and positively correlates with hyperproliferation, dedifferentiation and HGF/MET pathway activation, suggesting that it contributes to a transcriptomic profile typical of the proliferative class of HCC. The mathematical model predicts how the expression of GRN components changes when the expression of another GRN member varies or is inhibited by a pharmacological drug. The dynamics of GRN component expression reveal distinct cell states that can switch reversibly in normal conditions, and irreversibly in HCC. The mathematical model is available via a web-based tool which can evaluate the GRN status of HCC samples and predict the impact of therapeutic agents on the GRN. CONCLUSIONS: We conclude that identification and modelling of the GRN provide insights into the prognosis of HCC and the mechanisms by which tumor-promoting genes impact on HCC development. LAY SUMMARY: Hepatocellular carcinoma (HCC) is a heterogeneous disease driven by the concomitant deregulation of several genes functionally organized as networks. Here, we identified a gene regulatory network involved in a subset of HCCs. This subset is characterized by increased proliferation and poor prognosis. We developed a mathematical model which uncovers the dynamics of the network and allows us to predict the impact of a therapeutic agent, not only on its specific target but on all the genes belonging to the network.

Predicting the cumulative effect of multiple disturbances on seagrass connectivity.

The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non-foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average >245 km, about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules; therefore, management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful.

Investigating the link between the Port of Miami dredging and the onset of the stony coral tissue loss disease epidemics.

Since 2014, the stony coral tissue loss disease (SCTLD) has been decimating corals in the Caribbean. Although the trigger of this outbreak remains elusive, evidence suggests waterborne sediment-mediated disease transmission. The outbreak reportedly initiated in September 2014 at a reef site off Virginia Key (VKR), during extensive dredging operations at the Port of Miami. Here we use a high-resolution ocean model to identify the potential driver of the outbreak by simulating the dispersal of dredged sediments, wastewater plumes and disease agents. Our results suggest that VKR could have been impacted by fine sediments produced by dredging operations, especially those involving non-conventional rock-chopping techniques. Wastewater contamination was unlikely. Additionally, our connectivity analysis indicates potential disease transmission from other affected reefs to VKR. Our results therefore suggest that dredging operations might be responsible for the onset of the epidemics. This underscores the need for stricter operational guidelines in future dredging projects.

Land reclamation and its consequences: A 40-year analysis of water residence time in Doha Bay, Qatar.

Qatar's rapid industrialization, notably in its capital city Doha, has spurred a surge in land reclamation projects, leading to a constriction of the entrance to Doha Bay. By reducing and deflecting the ocean circulation, land reclamation projects have reduced the effective dispersion of wastewater introduced into the bay and hence degraded the water quality. Here, we assess fluctuations in water residence time across three distinct eras (1980, 2000, and 2020) to gauge the impact of successive land reclamation developments. To do this, we couple the multi-scale ocean model SLIM with a Lagrangian model for water residence time within Doha's coastal area. We consider three different topographies of Doha's shoreline to identify which artificial structures contributed the most to increase water residence time. Our findings reveal that the residual ocean circulation in Doha Bay was predominantly impacted by northern developments post-2000. Between 1980 and 2000, the bay's residence time saw a modest rise, of about one day on average. However, this was followed by a substantial surge, of three to six days on average, between 2000 and 2020, which is mostly attributable to The Pearl mega artificial island development. Certain regions of the bay witnessed a tripling of water residence time. Given the ongoing population expansion along the coast, it is anticipated that the growth of artificial structures and coastal reclamation will persist, thereby exacerbating the accumulation of pollutants in the bay. Our findings suggest that artificial offshore structures can exert far-reaching, non-local impacts on water quality, which need to be properly assessed during the planning stages of such developments.

How to avoid unbounded drug accumulation with fractional pharmacokinetics.

A number of studies have shown that certain drugs follow an anomalous kinetics that can hardly be represented by classical models. Instead, fractional-order pharmacokinetics models have proved to be better suited to represent the time course of these drugs in the body. Unlike classical models, fractional models can represent memory effects and a power-law terminal phase. They give rise to a more complex kinetics that better reflects the complexity of the human body. By doing so, they also spotlight potential issues that were ignored by classical models. Among those issues is the accumulation of drug that carries on indefinitely when the infusion rate is constant and the elimination flux is fractional. Such an unbounded accumulation could have important clinical implications and thus requires a solution to reach a steady state. We have considered a fractional one-compartment model with a continuous intravenous infusion and studied how the infusion rate influences the total amount of drug in the compartment. By taking an infusion rate that decays like a power law, we have been able to stabilize the amount of drug in the compartment. In the case of multiple dosing administration, we propose recurrence relations for the doses and the dosing times that also prevent drug accumulation. By introducing a numerical discretization of the model equations, we have been able to consider a more realistic two-compartment model with both continuous infusion and multiple dosing administration. That numerical model has been applied to amiodarone, a drug known to have an anomalous kinetics. Numerical results suggest that unbounded drug accumulation can again be prevented by using a drug input function that decays as a power law.

Biophysical models resolution affects coral connectivity estimates.

Estimating connectivity between coral reefs is essential to inform reef conservation and restoration. Given the vastness of coral reef ecosystems, connectivity can only be simulated with biophysical models whose spatial resolution is often coarser than the reef scale. Here, we assess the impact of biophysical models resolution on connectivity estimates by comparing the outputs of five different setups of the same model with resolutions ranging from 250 m to 4 km. We show that increasing the model resolution around reefs yields more complex and less directional dispersal patterns. With a fine-resolution model, connectivity graphs have more connections but of weaker strength. The resulting community structure therefore shows larger clusters of well-connected reefs. Virtual larvae also tend to stay longer close to their source reef with a fine-resolution model, leading to an increased local retention and self-recruitment for species with a short pre-competency period. Overall, only about half of the reefs with the largest connectivity indicator values are similar for the finest and coarsest resolution models. Our results suggest that reef management recommendations should only be made at scales coarser than the model resolution. Reef-scale recommendations can hence only be made with models not exceeding about 500 m resolution.

Seychelles Plateau's oil spill vulnerability.

Small Island Developing States, such as Seychelles, are highly susceptible to oil pollution incidents, with limited infrastructure for detection and mitigation. While an oil spill could significantly impact Seychelle's tourism industry, contributing to ~40% of its GDP, the archipelago's vulnerability remains largely unknown. Here, we developed a high-resolution ocean circulation model for Seychelles Plateau, simulating currents over three years (2018-2020) to model oil spill dispersal to six ecologically and economically significant coastal areas. Our findings reveal distinct seasonality in offshore risk distribution, driven by seasonal fluctuations in atmospheric and oceanic circulations. We show that an oil spill originating from any part of the plateau could potentially impact a sensitive coastal site in less than five days. By identifying high-risk areas, including the major north-south shipping route, we emphasize the importance of close satellite and airborne monitoring for early warnings to protect Seychelles' coastal ecosystems and tourism industry.

Front dynamics in a two-species competition model driven by Lévy flights.

A number of recent studies suggest that many biological species follow a Lévy random walk in their search for food. Such a strategy has been shown to be more efficient than classical Brownian motion when resources are scarce. However, current diffusion-reaction models used to describe many ecological systems do not account for the superdiffusive spread of populations due to Lévy flights. We have developed a model to simulate the spatial spread of two species competing for the same resources and driven by Lévy flights. The model is based on the Lotka-Volterra equations and has been obtained by replacing the second-order diffusion operator by a fractional-order one. Consistent with previous known results, theoretical developments and numerical simulations show that fractional-order diffusion leads to an exponential acceleration of the population fronts and a power-law decay of the fronts' leading tail. Depending on the skewness of the fractional derivative, we derive catch-up conditions for different types of fronts. Our results indicate that second-order diffusion-reaction models are not well-suited to simulate the spatial spread of biological species that follow a Lévy random walk as they are inclined to underestimate the speed at which these species propagate.

Front dynamics in fractional-order epidemic models.

A number of recent studies suggest that human and animal mobility patterns exhibit scale-free, Lévy-flight dynamics. However, current reaction-diffusion epidemics models do not account for the superdiffusive spread of modern epidemics due to Lévy flights. We have developed a SIR model to simulate the spatial spread of a hypothetical epidemic driven by long-range displacements in the infective and susceptible populations. The model has been obtained by replacing the second-order diffusion operator by a fractional-order operator. Theoretical developments and numerical simulations show that fractional-order diffusion leads to an exponential acceleration of the epidemic's front and a power-law decay of the front's leading tail. Our results indicate the potential of fractional-order reaction-diffusion models to represent modern epidemics.

Modelling of Epithelial Growth, Fission and Lumen Formation During Embryonic Thyroid Development: A Combination of Computational and Experimental Approaches.

Organogenesis is the phase of embryonic development leading to the formation of fully functional organs. In the case of the thyroid, organogenesis starts from the endoderm and generates a multitude of closely packed independent spherical follicular units surrounded by a dense network of capillaries. Follicular organisation is unique and essential for thyroid function, i.e. thyroid hormone production. Previous in vivo studies showed that, besides their nutritive function, endothelial cells play a central role during thyroid gland morphogenesis. However, the precise mechanisms and biological parameters controlling the transformation of the multi-layered thyroid epithelial primordium into a multitude of single-layered follicles are mostly unknown. Animal studies used to improve understanding of organogenesis are costly and time-consuming, with recognised limitations. Here, we developed and used a 2-D vertex model of thyroid growth, angiogenesis and folliculogenesis, within the open-source Chaste framework. Our in silico model, based on in vivo images, correctly simulates the differential growth and proliferation of central and peripheral epithelial cells, as well as the morphogen-driven migration of endothelial cells, consistently with our experimental data. Our simulations further showed that reduced epithelial cell adhesion was critical to allow endothelial invasion and fission of the multi-layered epithelial mass. Finally, our model also allowed epithelial cell polarisation and follicular lumen formation by endothelial cell abundance and proximity. Our study illustrates how constant discussion between theoretical and experimental approaches can help us to better understand the roles of cellular movement, adhesion and polarisation during thyroid embryonic development. We anticipate that the use of in silico models like the one we describe can push forward the fields of developmental biology and regenerative medicine.

A Lévy-flight diffusion model to predict transgenic pollen dispersal.

The containment of genetically modified (GM) pollen is an issue of significant concern for many countries. For crops that are bee-pollinated, model predictions of outcrossing rates depend on the movement hypothesis used for the pollinators. Previous work studying pollen spread by honeybees, the most important pollinator worldwide, was based on the assumption that honeybee movement can be well approximated by Brownian motion. A number of recent studies, however, suggest that pollinating insects such as bees perform Lévy flights in their search for food. Such flight patterns yield much larger rates of spread, and so the Brownian motion assumption might significantly underestimate the risk associated with GM pollen outcrossing in conventional crops. In this work, we propose a mechanistic model for pollen dispersal in which the bees perform truncated Lévy flights. This assumption leads to a fractional-order diffusion model for pollen that can be tuned to model motion ranging from pure Brownian to pure Lévy. We parametrize our new model by taking the same pollen dispersal dataset used in Brownian motion modelling studies. By numerically solving the model equations, we show that the isolation distances required to keep outcrossing levels below a certain threshold are substantially increased by comparison with the original predictions, suggesting that isolation distances may need to be much larger than originally thought.