Kith or Kin? Familiarity as a Cue to Kinship in Social Birds

© Copyright © 2020 Leedale, Li and Hatchwell. Interacting with relatives provides opportunities for fitness benefits via kin-selected cooperation, but also creates potential costs through kin competition and inbreeding. Therefore, a mechanism for the discrimination of kin from non-kin is likely to be critical for individuals of many social species to maximize their inclusive fitness. Evidence suggests that genetic cues to kinship are rare and that learned or environmental cues offer a more parsimonious explanation for kin recognition in most contexts. This is particularly true among cooperatively breeding birds, where recognition of familiar individuals is usually regarded as the most plausible mechanism for kin discrimination. In this article, we first review the evidence that familiarity provides an effective decision rule for discrimination of kin from non-kin in social birds. We then consider some of the complexities of familiarity as a cue to kinship, especially the problems of how individuals become familiar, and how familiar individuals are recognized. We conclude that while familiarity as a mechanism for kin recognition may be more parsimonious and widespread than genetic mechanisms, its apparent simplicity as a decision rule governing social interactions may be deceptive. Finally, we identify directions for future research on familiarity as a kin recognition mechanism in social birds and other taxa

A dynamic, climate-driven model of Rift Valley fever

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information

Helping decisions and kin recognition in long-tailed tits: is call similarity used to direct help towards kin?

Most cooperative breeders live in discrete family groups, but in a minority, breeding populations comprise extended social networks of conspecifics that vary in relatedness. Selection for effective kin recognition may be expected for more related individuals in such kin neighbourhoods to maximize indirect fitness. Using a long-term social pedigree, molecular genetics, field observations and acoustic analyses, we examine how vocal similarity affects helping decisions in the long-tailed tit Aegithalos caudatus. Long-tailed tits are cooperative breeders in which help is typically redirected by males that have failed in their own breeding attempts towards the offspring of male relatives living within kin neighbourhoods. We identify a positive correlation between call similarity and kinship, suggesting that vocal cues offer a plausible mechanism for kin discrimination. Furthermore, we show that failed breeders choose to help males with calls more similar to their own. However, although helpers fine-tune their provisioning rates according to how closely related they are to recipients, their effort was not correlated with their vocal similarity to helped breeders. We conclude that although vocalizations are an important part of the recognition system of long-tailed tits, discrimination is likely to be based on prior association and may involve a combination of vocal and non-vocal cues. This article is part of the theme issue 'Signal detection theory in recognition systems: from evolving models to experimental tests'

In silico-guided optimisation of oxygen gradients in hepatic spheroids

One of the key advantages of assessing the hepatotoxic potential of xenobiotics in spheroids rather than monolayer cell culture is the existence of a more physiologically relevant testing environment. Three-dimensional cultures support spatial gradients in nutrients such as oxygen that can be exploited to better represent in vivo gradients that exist along a fundamental sub-unit of liver microarchitecture, the liver sinusoid. The physical and physiological processes that result in the establishment of such gradients can be described mathematically. Quantification of the rates governing these processes and optimisation of cell culture conditions can be performed in silico to better inform experimental design. In this study, we take into account cell line-specific physiological properties, spheroid size and the impact of experimental equipment geometries in order to demonstrate how mathematical models can be optimised to achieve specific in vivo-like features in different scenarios. Furthermore, the sensitivity of such optimised gradients is analysed with respect to culture conditions and considerations are given to prevent the emergence of hypoxic regions in the spheroid. The methodology presented provides an enhanced understanding of the mechanisms of the system within this simulated in vitro framework such that experimental design can be more carefully calibrated when conducting experiments using hepatic spheroids. © 2019 Elsevier B.V

A combined in vitro/in silico approach to identifying off-target receptor toxicity

Many xenobiotics can bind to off-target receptors and cause toxicity via the dysregulation of downstream transcription factors. Identification of subsequent off-target toxicity in these chemicals has often required extensive chemical testing in animal models. An alternative, integrated in vitro/in silico approach for predicting toxic off-target functional responses is presented to refine in vitro receptor identification and reduce the burden on in vivo testing. As part of the methodology, mathematical modelling is used to mechanistically describe processes that regulate transcriptional activity following receptor-ligand binding informed by transcription factor signalling assays. Critical reactions in the signalling cascade are identified to highlight potential perturbation points in the biochemical network that can guide and optimise additional in vitro testing. A physiologically-based pharmacokinetic model provides information on the timing and localisation of different levels of receptor activation informing whole-body toxic potential resulting from off-target binding

A mathematical investigation into the uptake kinetics of nanoparticles in vitro

Nanoparticles have the potential to increase the efficacy of anticancer drugs whilst reducing off-target side effects. However, there remain uncertainties regarding the cellular uptake kinetics of nanoparticles which could have implications for nanoparticle design and delivery. Polymersomes are nanoparticle candidates for cancer therapy which encapsulate chemotherapy drugs. Here we develop a mathematical model to simulate the uptake of polymersomes via endocytosis, a process by which polymersomes bind to the cell surface before becoming internalised by the cell where they then break down, releasing their contents which could include chemotherapy drugs. We focus on two in vitro configurations relevant to the testing and development of cancer therapies: a well-mixed culture model and a tumour spheroid setup. Our mathematical model of the well-mixed culture model comprises a set of coupled ordinary differential equations for the unbound and bound polymersomes and associated binding dynamics. Using a singular perturbation analysis we identify an optimal number of ligands on the polymersome surface which maximises internalised polymersomes and thus intracellular chemotherapy drug concentration. In our mathematical model of the spheroid, a multiphase system of partial differential equations is developed to describe the spatial and temporal distribution of bound and unbound polymersomes via advection and diffusion, alongside oxygen, tumour growth, cell proliferation and viability. Consistent with experimental observations, the model predicts the evolution of oxygen gradients leading to a necrotic core. We investigate the impact of two different internalisation functions on spheroid growth, a constant and a bond dependent function. It was found that the constant function yields faster uptake and therefore chemotherapy delivery. We also show how various parameters, such as spheroid permeability, lead to travelling wave or steady-state solutions

A mathematical investigation into the uptake kinetics of nanoparticles in vitro.

Nanoparticles have the potential to increase the efficacy of anticancer drugs whilst reducing off-target side effects. However, there remain uncertainties regarding the cellular uptake kinetics of nanoparticles which could have implications for nanoparticle design and delivery. Polymersomes are nanoparticle candidates for cancer therapy which encapsulate chemotherapy drugs. Here we develop a mathematical model to simulate the uptake of polymersomes via endocytosis, a process by which polymersomes bind to the cell surface before becoming internalised by the cell where they then break down, releasing their contents which could include chemotherapy drugs. We focus on two in vitro configurations relevant to the testing and development of cancer therapies: a well-mixed culture model and a tumour spheroid setup. Our mathematical model of the well-mixed culture model comprises a set of coupled ordinary differential equations for the unbound and bound polymersomes and associated binding dynamics. Using a singular perturbation analysis we identify an optimal number of ligands on the polymersome surface which maximises internalised polymersomes and thus intracellular chemotherapy drug concentration. In our mathematical model of the spheroid, a multiphase system of partial differential equations is developed to describe the spatial and temporal distribution of bound and unbound polymersomes via advection and diffusion, alongside oxygen, tumour growth, cell proliferation and viability. Consistent with experimental observations, the model predicts the evolution of oxygen gradients leading to a necrotic core. We investigate the impact of two different internalisation functions on spheroid growth, a constant and a bond dependent function. It was found that the constant function yields faster uptake and therefore chemotherapy delivery. We also show how various parameters, such as spheroid permeability, lead to travelling wave or steady-state solutions

Modelling changes in glutathione homeostasis as a function of quinone redox metabolism

Redox cycling is an understated mechanism of toxicity associated with a plethora of xenobiotics, responsible for preventing the effective treatment of serious conditions such as malaria and cardiomyopathy. Quinone compounds are notorious redox cyclers, present in drugs such as doxorubicin, which is used to treat a host of human cancers. However, the therapeutic index of doxorubicin is undermined by dose-dependent cardiotoxicity, which may be a function of futile redox cycling. In this study, a doxorubicin-specific in silico quinone redox metabolism model is described. Doxorubicin-GSH adduct formation kinetics are thermodynamically estimated from 26 its reduction potential, while the remainder of the model is parameterised using oxygen consumption rate data, indicative of hydroquinone auto oxidation. The model is then combined with a comprehensive glutathione metabolism model, facilitating the simulation of quinone redox cycling, and adduct-induced GSH depletion. Simulations suggest that glutathione pools are most sensitive to exposure duration at pharmacologically and supra-pharmacologically relevant doxorubicin concentrations. The model provides an alternative method of investigating and quantifying redox cycling induced oxidative stress, circumventing the experimental difficulties of measuring and tracking radical species. This in silico framework provides a platform from which GSH depletion can be explored as a function of a compound’s physicochemical properties

Modelling the impact of changes in the extracellular environment on the cytosolic free NAD+/NADH ratio during cell culture.

Cancer cells depend on glucose metabolism via glycolysis as a primary energy source, despite the presence of oxygen and fully functioning mitochondria, in order to promote growth, proliferation and longevity. Glycolysis relies upon NAD+ to accept electrons in the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) reaction, linking the redox state of the cytosolic NAD+ pool to glycolytic rate. The free cytosolic NAD+/NADH ratio is involved in over 700 oxidoreductive enzymatic reactions and as such, the NAD+/NADH ratio is regarded as a metabolic readout of overall cellular redox state. Many experimental techniques that monitor or measure total NAD+ and NADH are unable to distinguish between protein-bound and unbound forms. Yet total NAD+/NADH measurements yield little information, since it is the free forms of NAD+ and NADH that determine the kinetic and thermodynamic influence of redox potential on glycolytic rate. Indirect estimations of free NAD+/NADH are based on the lactate/pyruvate (L/P) ratio at chemical equilibrium, but these measurements are often undermined by high lability. To elucidate the sensitivity of the free NAD+/NADH ratio to changes in extracellular substrate, an in silico model of hepatocarcinoma glycolysis was constructed and validated against in vitro data. Model simulations reveal that over experimentally relevant concentrations, changes in extracellular glucose and lactate concentration during routine cancer cell culture can lead to significant deviations in the NAD+/NADH ratio. Based on the principles of chemical equilibrium, the model provides a platform from which experimentally challenging situations may be examined, suggesting that extracellular substrates play an important role in cellular redox and bioenergetic homeostasis

Preparation of Primary Rat Hepatocyte Spheroids Utilizing the Liquid-Overlay Technique.

Herein, we describe a protocol for the preparation and analysis of primary isolated rat hepatocytes in a 3D cell culture format described as spheroids. The hepatocyte cells spontaneously self-aggregate into spheroids without the need for synthetic extracellular matrices or hydrogels. Primary rat hepatocytes (PRHs) are a readily available source of primary differentiated liver cells and therefore conserve many of the required liver-specific functional markers, and elicit the natural in vivo phenotype when compared with common hepatic cells lines. We describe the liquid-overlay technique which provides an ultra-low attachment surface on which PRHs can be cultured as spheroids. © 2019 The Authors. Basic Protocol 1: Preparation of agarose-coated plates Basic Protocol 2: Primary rat hepatocyte isolation procedure Basic Protocol 3: Primary rat hepatocyte spheroid culture Basic Protocol 4: Immunofluorescent analysis of PRH spheroids