Journal of Theoretical Biology最新文献

Marine mixotrophs combine phagotrophy and phototrophy to acquire the resources they need for growth. Metabolic plasticity, the ability for individuals to dynamically alter their relative investment between different metabolic processes, allows mixotrophs to efficiently exploit variable environmental conditions. Different mixotrophs may vary in how quickly they respond to environmental stimuli, with slow-responding mixotrophs exhibiting a significant lag between a change in the environment and the resulting change metabolic strategy. In this study, we develop a model of mixotroph metabolic strategy and explore how the rate of the plastic response affects the seasonality, competitive fitness, and biogeochemical role of mixotroph populations. Fast-responding mixotrophs are characterized by more efficient resource use and higher average growth rates than slow-responding mixotrophs because any lag in the plastic response following a change in environmental conditions creates a mismatch between the mixotroph’s metabolic requirements and their resource acquisition. However, this mismatch also results in increased storage of unused resources that support growth under future nutrient-limited conditions. As a result of this trade-off, mixotroph biomass and productivity are maximized at intermediate plastic response rates. Furthermore, the trade-off represents a mechanism for coexistence between fast-responding and slow-responding mixotrophs. In mixed communities, fast-responding mixotrophs are numerically dominant, but slow-responding mixotrophs persist at low abundance due to the provisioning effect that emerges as a result of their less efficient resource acquisition strategy. In addition to increased competitive ability, fast-responding mixotrophs are, on average, more autotrophic than slow-responding mixotrophs. Notably, these trade-offs associated with mixotroph response rate arise without including an explicit physiological cost associated with plasticity, a conclusion that may provide insight into evolutionary constraints of metabolic plasticity in mixotrophic organisms. When an explicit cost is added to the model, it alters the competitive relationships between fast- and slow-responding mixotrophs. Faster plastic response rates are favored by lower physiological costs as well as higher amplitude seasonal cycles.

Protein–protein interactions (PPIs) are crucial for various biological processes, and predicting PPIs is a major challenge. To solve this issue, the most common method is link prediction. Currently, the link prediction methods based on network Paths of Length Three (L3) have been proven to be highly effective. In this paper, we propose a novel link prediction algorithm, named SMS, which is based on L3 and protein similarities. We first design a mixed similarity that combines the topological structure and attribute features of nodes. Then, we compute the predicted value by summing the product of all similarities along the L3. Furthermore, we propose the Max Similarity Multiplied Similarity (maxSMS) algorithm from the perspective of maximum impact. Our computational prediction results show that on six datasets, including S. cerevisiae, H. sapiens, and others, the maxSMS algorithm improves the precision of the top 500, area under the precision–recall curve, and normalized discounted cumulative gain by an average of 26.99%, 53.67%, and 6.7%, respectively, compared to other optimal methods.

The Gaia hypothesis posits that the Earth and its biosphere function as a single self-stabilizing system, but a key challenge is explaining how this could have arisen through Darwinian evolution. One theory is that of “selection by differential survival,” in which a clade’s extinction probability decreases with age as it accumulates adaptations resisting environmental disturbances. While this is hard to assess during early Earth history, we can assess whether this process operated among marine animal genera throughout the Phanerozoic. To that end, we analyzed time ranges of 36,117 extinct animal genera using fossil occurrence data from the Paleobiology Database in order to calculate marine metazoan extinction age selectivity, extinction rates, and speciation rates over the Phanerozoic. We identify four signatures of selection by differential survival: lower extinction rates among older lineages, heritability and taxonomically nested propagation of extinction resistance, reduced age selectivity during rare environmental perturbations, and differential extinction rather than speciation as the primary driver of the phenomenon. Evidence for this process at lower taxonomic levels also implies its possibility for life as a whole – indeed, the possibility of Gaia.

This work introduces the concept of Variable Size Game Theory (VSGT), in which the number of players in a game is a strategic decision made by the players themselves. We start by discussing the main examples in game theory: dominance, coexistence, and coordination. We show that the same set of pay-offs can result in coordination-like or coexistence-like games depending on the strategic decision of each player type. We also solve an inverse problem to find a $d$-player game that reproduces the same fixation pattern of the VSGT. In the sequel, we consider a game involving prosocial and antisocial players, i.e., individuals who tend to play with large groups and small groups, respectively. In this game, a certain task should be performed, that will benefit one of the participants at the expense of the other players. We show that individuals able to gather large groups to perform the task may prevail, even if this task is costly, providing a possible scenario for the evolution of eusociality. The next example shows that different strategies regarding game size may lead to spontaneous separation of different types, a possible scenario for speciation without physical separation (sympatric speciation). In the last example, we generalize to three types of populations from the previous analysis and study compartmental epidemic models: in particular, we recast the SIRS model into the VSGT framework: Susceptibles play 2-player games, while Infectious and Removed play a 1-player game. The SIRS epidemic model is then obtained as the replicator equation of the VSGT. We finish with possible applications of VSGT to be addressed in the future.

In this paper, we are interested in the modeling of Alzheimer’s disease from the angle of the amyloid cascade hypothesis, where the pathogenic agent is the A$\beta$ protein in its oligomeric form. The formation dynamics of this pathogenic form is modeled by a Becker–Doring type model where APP (Amyloid Precursor Protein) protein, after cleavage by specific enzymes, forms monomeric A$\beta$ proteins, which, by polymerization and/or nucleation, lead to the formation of oligomeric A$\beta$. We propose an optimal control problem to estimate the rate of nucleation which seems to be at the base of this amyloid cascade hypothesis and for which no (experimental) measurement exists for the moment.

Obesity is a contributing factor to asthma severity; while it has long been understood that obesity is related to greater asthma burden, the mechanisms though which this occurs have not been fully elucidated. One common explanation is that obesity mechanically reduces lung volume through accumulation of adipose tissue external to the thoracic cavity. However, it has been recently demonstrated that there is substantial adipose tissue within the airway wall itself, and that the presence of adipose tissue within the airway wall is related to body mass index. This suggests the possibility of an additional mechanism by which obesity may worsen asthma, namely by altering the behaviour of the airways themselves. To this end, we modify Anafi & Wilson’s classic model of the bistable terminal airway to incorporate adipose tissue within the airway wall in order to answer the question of how much adipose tissue would be required in order to drive substantive functional changes. This analysis suggests that adipose tissue within the airway wall on the order of 1%–2% of total airway cross-sectional area could be sufficient to drive meaningful changes, and further that these changes may interact with volume effects to magnify the overall burden.

Fish schooling has the improvement in hydrodynamic propulsive efficiency through the interaction of flow field induced by fish bodies and tail beat. Such energy-saving behaviors due to flow interactions also occur with changes in the flow field caused by structures. We examined the differences between a live fish swimming around a streamlined hydrofoil model prepared to represent fish body and swimming alone in a flow tank. We observed that the fish can remain in the same place without tail beating. It called “drafting” behavior. The analysis of fish drafting showed that fish obtained thrust using a local pressure drop caused by the high velocity flow even in the vicinity of the hydrofoil model at an angle of attack α of 10° to 20°without flow separation, and fish balanced forces by using an α of fish body. This tendency was confirmed in the model experiment using a two-axis load cell, and the forces acting on the fish body was the smallest value when the fish model was placed in the same conditions as a live fish experiment. We also confirmed by simulation and found that the α of fish body generated lift force and counteract the suction force. Above results indicate that a fish can balance the anterior–posterior and lateral direction forces by using a local pressure drop around a hydrofoil model as suction force, and using angle of attack on its body, thereby realizing drafting.

The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modeling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms. In addition to synaptic plasticity and spike frequency adaptation, our model incorporates adult neurogenesis in the dentate gyrus as well as the difference in size between the neocortex and the hippocampus, that we associate with distance-dependent synaptic plasticity. We also take into account the interconnected spatial structure of the involved brain areas, by incorporating the above neurobiological mechanisms in a coupled neural field framework, where each area is represented by a separate neural field with intra- and inter-area connections. To our knowledge, this is the first attempt to apply neural fields to this process. Using numerical simulations and mathematical analysis, we explore the short-term and long-term dynamics of the model upon alternance of phases of hippocampal replay and retrieval cue of an external input. This external input is encodable as a memory pattern in the form of a multiple bump attractor pattern in the individual neural fields. In the model, hippocampal memory patterns become encoded first, before neocortical ones, because of the smaller distances between the bumps of the hippocampal memory patterns. As a result, retrieval of the input pattern in the neocortex at short time-scales necessitates the additional input delivered by the memory pattern of the hippocampus. Neocortical memory patterns progressively consolidate at longer times, up to a point where their retrieval does not need the support of the hippocampus anymore. At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex. Therefore, the dynamics of our model successfully reproduces the main features of the standard consolidation theory. This suggests that neurogenesis in the hippocampus and distance-dependent synaptic plasticity coupled to synaptic depression and spike frequency adaptation, are indeed critical neurobiological processes in memory consolidation.

In this paper we use simulation methods to study a hypothetical uncoupling agent as a therapy for dementia. We simulate the proliferation of mitochondrial deletion mutants amongst a population of wild-type in human neurons. Mitochondria play a key role in ATP generation. Clonal expansion can lead to the wild-type being overwhelmed by deletions such that a diminished population can no longer fulfil a cell’s energy requirement, eventually leading to its demise. The intention of uncoupling is to reduce the formation of deletion mutants by reducing mutation rate. However, a consequence of uncoupling is that the energy production efficacy is also reduced which in turn increases wild-type copy number in order to compensate for the energy deficit. The results of this paper showed that uncoupling reduced the severity of dementia, however, there was some increase in cognitive dysfunction pre-onset of dementia. The effectiveness of uncoupling was dependent upon the timing of intervention relative to the onset of dementia and would necessitate predicting its onset many years in advance.

In the current paper we analyse an extended SIRS epidemic model in which immunity at the individual level wanes gradually at exponential rate, but where the waning rate may differ between individuals, for instance as an effect of differences in immune systems. The model also includes vaccination schemes aimed to reach and maintain herd immunity. We consider both the informed situation where the individual waning parameters are known, thus allowing selection of vaccinees being based on both time since last vaccination as well as on the individual waning rate, and the more likely uninformed situation where individual waning parameters are unobserved, thus only allowing vaccination schemes to depend on time since last vaccination. The optimal vaccination policies for both the informed and uniformed heterogeneous situation are derived and compared with the homogeneous waning model (meaning all individuals have the same immunity waning rate), as well as to the classic SIRS model where immunity at the individual level drops from complete immunity to complete susceptibility in one leap. It is shown that the classic SIRS model requires least vaccines, followed by the SIRS with homogeneous gradual waning, followed by the informed situation for the model with heterogeneous gradual waning. The situation requiring most vaccines for herd immunity is the most likely scenario, that immunity wanes gradually with unobserved individual heterogeneity. For parameter values chosen to mimic COVID-19 and assuming perfect initial immunity and cumulative immunity of 12 months, the classic homogeneous SIRS epidemic suggests that vaccinating individuals every 15 months is sufficient to reach and maintain herd immunity, whereas the uninformed case for exponential waning with rate heterogeneity corresponding to a coefficient of variation being 0.5, requires that individuals instead need to be vaccinated every 4.4 months.