Theory in Biosciences最新文献

Despite being a powerful tool to model ecological interactions, traditional evolutionary game theory can still be largely improved in the context of population dynamics. One of the current challenges is to devise a cohesive theoretical framework for ecological games with density-dependent (or concentration-dependent) evolution, especially one defined by individual-level events. In this work, I use the notation of reaction networks as a foundation to propose a framework and show that classic two-strategy games are a particular case of the theory. The framework exhibits a strong versatility and provides a standardized language for model design, and I demonstrate its use through a simple example of mating dynamics and parental care. In addition, reaction networks provide a natural connection between stochastic and deterministic dynamics and therefore are suitable to model noise effects on small populations, also allowing the use of stochastic simulation algorithms such as Gillespie's with game models. The methods I present can help to bring evolutionary game theory to new reaches in ecology, facilitate the process of model design, and put different models on a common ground.

Can mathematical proofs be employed for the solution of fundamental molecular-level problems in biology? Recently, I mathematically tackled complex mechanistic problems arising during the synthesis of the universal biological currency, adenosine triphosphate (ATP) by the F_OF₁-ATP synthase, nature's smallest rotary molecular motor, using graph-theoretical and combinatorial approaches for the membrane-bound F_O and water-soluble F₁ domains of this fascinating molecule (see Nath in Theory Biosci 141:249‒260, 2022 and Theory Biosci 143:217‒227, 2024). In the third part of this trilogy, I investigate another critical aspect of the molecular mechanism-that of coupling between the F_O and F₁ domains of the ATP synthase mediated by the central γ-subunit of $\sim 1$ nanometer diameter. According to Nath's torsional mechanism of energy transduction and ATP synthesis the γ-subunit twists during ATP synthesis and the release of stored torsional energy in the central γ-stalk causes conformational changes in the catalytic sites that lead to ATP synthesis, with 1 ATP molecule synthesized per discrete 120° rotation. The twisted γ-subunit breaks the symmetry of the molecule, and its residual torsional strain is shown to readily accommodate any symmetry mismatch existing between F_O and F₁. A mathematical number theory proof is developed to quantify the extent of symmetry mismatch at any angular position during rotation and derive the conditions for the regaining of symmetry at the end of a 360° rotation. The many chemical and biological implications of the mechanism and the mathematical proof are discussed in detail. Finally, suggestions for further mathematical development of the subject based on ideas from symmetry and group theory have been made. In sum, the answer to the question posed at the beginning of the Abstract is a resounding YES. There exists new, relatively unexplored territory at the interface of mathematics and molecular biology, especially at the level of molecular mechanism. It is hoped that more mathematicians and scientists interested in interdisciplinary work are encouraged to include in their research program approaches of this type-a mathematical proofs-inspired molecular biology-that have the power to lead to new vistas. Such molecular-scale mechanistic problems in biology have proved extraordinarily difficult to solve definitively using conventional experimental, theoretical, and computational approaches.

Circular codes, which are considered as putative remnants of primaeval comma-free codes, have recently become a focal point of research. These codes constitute a secondary type of genetic code, primarily tasked with detecting and preserving the normal reading frame within protein-coding sequences. The identification of a universal code present across various species has sparked numerous theoretical and experimental inquiries. Among these, the exploration of the class of 216 self-complementary $C^3$ -codes of maximum size 20 has garnered significant attention. However, the origin of the number 216 lacks a satisfactory explanation, and the mathematical construction of these codes remains elusive. This paper introduces a new software designed to facilitate the construction of self-complementary $C^3$ -codes (of maximum size). The approach involves a systematic exclusion of codons, guided by two fundamental mathematical theorems. These theorems demonstrate how codons can be automatically excluded from consideration when imposing requirements such as self-complementarity, circularity or maximality. By leveraging these theorems, our software provides a novel and efficient means to construct these intriguing circular codes, shedding light on their mathematical foundations and contributing to a deeper understanding of their biological significance.

In biology, the concept of "living organism" has traditionally been based on the smallest level of organization comprising all the necessary and essential characteristics of life: the cell. Today, this concept is being challenged by the analysis of ambiguous biological entities, located both below and above the level of the living cell, which exhibit some of the characteristics of living organisms. This situation has given rise to an epistemological pluralism of the concepts of "organism", "individual" and "living", for which no clear and unanimous definition has yet been accepted. The aim of this manuscript is to explore new ideas and perspectives for defining the concept of "living organism", in order to eliminate a certain level of pluralism that could generate confusion, particularly in the pragmatic context of biological research. First, I expose the dualism of the concepts of "organism" and "individual" and suggest a fusion of these concepts in order to eliminate a certain level of pluralism. In doing so, I develop a symbiotic and holistic definition of the concept of "living organism", which includes different structural levels of the organism: molecular, cellular and ecosystems. Second, I present the epistemological problem of the concept of "living", which is closely related to the concepts of "organism" and "individual", by analyzing the list and gradational types of definition. In doing so, I propose a new symbiotic, holistic and gradualist model of the concept of "living organism", using a gradation of several properties of the living applied to the different structural levels of the organism developed previously (molecular, cellular, ecosystems).

The tumor microenvironment constitutes a complex system shaped by the intricate interactions among tumor cells, immune cells, and cytokines. Within this environment, the interplay between immune cells and cytokines is crucial in influencing tumor growth and progression. Despite advancements in clinical tumor immunotherapy, there remains a gap in comprehensive simulations of tumor immune responses, particularly regarding cytokine-driven processes. This study aims to address this gap by investigating the regulatory interactions among tumor cells, immune cells, and cytokines to simulate the complexities of tumor immunotherapy. We develop a comprehensive modeling and computational framework incorporating PD-1 inhibitors and interleukin-10 (IL-10) antibodies. Through detailed mathematical analysis, we elucidate the impact of changes in the immune microenvironment on tumor cells number. Our findings highlight the significant therapeutic effect of anti-PD-1 and IL-10 inhibitors, with increased drug dosage correlating with a reduction in tumor burden. Furthermore, combination therapy demonstrates a marked extension of survival with reduced dosages compared to monotherapy. Based on model simulations, we proposed prognostic predictions by assessing the microenvironmental status before treatment. The findings indicate a promising method for enhancing treatment effectiveness and offering potential advantages to patients receiving tumor immunotherapy.

The conflict between individual and collective interests makes fostering cooperation in human societies a challenging task, requiring drastic measures such as the establishment of sanctioning institutions. These institutions are costly because they have to be maintained regardless of the presence or absence of offenders. Here, we revisit some improvements to the standard N-person prisoner's dilemma formulation with institutional punishment in a well-mixed population, namely the elimination of overpunishment, the requirement of a minimum number of contributors to establish the sanctioning institution, and the sharing of its maintenance costs once this minimum number is reached. In addition, we focus on large groups or communities for which sanctioning institutions are ubiquitous. Using the replicator equation framework for an infinite population, we find that by sufficiently fining players who fail to contribute either to the public good or to the sanctioning institution, a population of contributors immune to invasion by these free riders can be established, provided that the contributors are sufficiently numerous. In a finite population, we use finite-size scaling to show that, for some parameter settings, demographic noise helps to fixate the strategy that contributes to the public good but not to the sanctioning institution even for infinitely large populations when, somewhat counterintuitively, its proportion in the initial population vanishes with a small power of the population size.

Understanding the ecological and evolutionary dynamics of populations is critical for both basic and applied purposes in a variety of biological contexts. Although several modeling frameworks have been developed to simulate eco-evolutionary dynamics, many fewer address how to model structured populations. In a prior paper, we put forth the first modeling approach to simulate eco-evolutionary dynamics in structured populations under the G function modeling framework. However, this approach does not allow for accurate simulation under fluctuating environmental conditions. To address this limitation, we draw on the study of periodic differential equations to propose a modified approach that uses a different definition of fitness more suitable for fluctuating environments. We illustrate this method with a simple toy model of life history trade-offs. The generality of this approach allows it to be used in a variety of biological contexts.

A fundamental problem in biology is how cells obtain the reproducible, coherent phenotypes needed for natural selection to act or, put differently, how cells manage to limit their exploration of the vastness of phenotype space. A subset of this problem is how they regulate their cell cycle. Bacteria, like eukaryotic cells, are highly structured and contain scores of hyperstructures or assemblies of molecules and macromolecules. The existence and functioning of certain of these hyperstructures depend on phase transitions. Here, I propose a conceptual framework to facilitate the development of water-clock hypotheses in which cells use water to generate phenotypes by living 'on the edge of phase transitions'. I give an example of such a hypothesis in the case of the bacterial cell cycle and show how it offers a relatively novel 'view from here' that brings together a range of different findings about hyperstructures, phase transitions and water and that can be integrated with other hypotheses about differentiation, metabolism and the origins of life.

In recent discussions, the widespread conviction that scientific individuation practices are governed by theories and concepts of biological individuality has been challenged, particularly by advocates of practice-based approaches. This discussion raises questions about the relationship between individuation practices and concepts of individuality. In this paper, I discuss four studies of host–parasite systems and analyze the respective individuation practices to see whether they correspond to established concepts of biological individuality. My analysis suggests that scientists individuate biological systems on different levels of organization and that the researchers’ respective emphasis on one of the levels depends on the explanandum and research context as well as epistemic aims and purposes. It thus makes sense to use different concepts of individuality to account for different individuation practices. However, not all individuation practices are represented equally well by concepts of biological individuality. To account for this observation, I propose that concepts of individuality should be understood as abstracted, idealized, or simplified models that represent only certain aspects of scientific practice. A modeling account suggests a pluralistic view of concepts of biological individuality that not only allows the coexistence of different kinds of individuality (e.g., evolutionary individuality, immunological individuality, ecological individuality) but also of normative and descriptive concepts.