Biosystems最新文献

Evolution of unicellular to multicellular organisms must resolve conflicts in reproductive interests between individual cells and the group. The social amoeba Dictyostelium discoideum is a soil-living eukaryote with facultative sociality. While cells grow in the presence of nutrients, cells aggregate under starvation to form fruiting bodies containing spores and altruistic stalk cells. Once cells socially committed, they complete formation of fruiting bodies, even if a new source of nutrients becomes available. The persistence of this social commitment raises questions as it inhibits individual cells from swiftly returning to solitary growth. I hypothesize that traits enabling premature de-commitment are hindered from being selected. Recent work has revealed outcomes of the premature de-commitment through forced refeeding; The de-committed cells take an altruistic prestalk-like position due to their reduced cohesiveness through interactions with socially committed cells. I constructed an evolutionary model assuming their division of labor. The results revealed a valley in the fitness landscape that prevented invasion of de-committing mutants, indicating evolutionary stability of the social commitment. The findings provide a general scheme that maintains multicellularity by evolving a specific division of labor, in which less cohesive individuals become altruists.

A simple theoretical model (or a demonstrative example) was developed to illustrate how the evolution of cooperation can be affected by the density-dependent survival competition, in which we assume that the fertility of an individual depends only on the pairwise interaction between him and other individuals based on Prisoner’s Dilemma game, while its viability is only related to the density-dependent survival competitiveness. Our results show that not only cooperation could be evolutionarily stable if the advantage of cooperators in viability can compensate for the cost they pay for their fertility, but also the long-term stable coexistence of cooperation and defection is possible if none of cooperation and defection is evolutionarily stable. Moreover, for the stochastic evolutionary dynamics in a finite population, our analysis shows that the increase (or decrease) of the survival competitiveness of cooperators (or defectors) should be conductive to the evolutionary emergence of cooperation.

This article proposes an evolutionary trajectory for the development of biological energy producing systems. Six main stages of energy producing system evolution are described, from early evolutionary pyrite-pulled mechanism through the Last Universal Common Ancestor (LUCA) to contemporary systems. We define the Last Pure Chemical Entity (LPCE) as the last completely non-enzymatic entity. LPCE could have had some life-like properties, but lacked genetic information carriers, thus showed greater instability and environmental dependence than LUCA. A double bubble model is proposed for compartmentalization and cellularization as a prerequisite to both highly efficient protein synthesis and transmembrane ion-gradient. The article finds that although LUCA predominantly functioned anaerobically, it was a non-exclusive anaerobe, and sulfur dominated metabolism preceded phosphate dominated one.

I analyzed the polyphyletic origin of glycyl-tRNA synthetase (GlyRS) and lysyl-tRNA synthetase (LysRS), making plausible the following implications. The fact that the genetic code needed to evolve aminoacyl-tRNA synthetases (ARSs) only very late would be in perfect agreement with a late origin, in the main phyletic lineages, of both GlyRS and LysRS. Indeed, as suggested by the coevolution theory, since the genetic code was structured by biosynthetic relationships between amino acids and as these occurred on tRNA-like molecules which were evidently already loaded with amino acids during its structuring, this made possible a late origin of ARSs. All this corroborates the coevolution theory of the origin of the genetic code to the detriment of theories which would instead predict an early intervention of the action of ARSs in organizing the genetic code. Furthermore, the assembly of the GlyRS and LysRS protein domains in main phyletic lineages is itself at least evidence of the possibility that ancestral genes were assembled using pieces of genetic material that coded these protein domains. This is in accordance with the exon theory of genes which postulates that ancestral exons coded for protein domains or modules that were assembled to form the first genes. This theory is exemplified precisely in the evolution of both GlyRS and LysRS which occurred through the assembly of protein domains in the main phyletic lineages, as analyzed here. Furthermore, this late assembly of protein domains of these proteins into the two main phyletic lineages, i.e. a polyphyletic origin of both GlyRS and LysRS, appears to corroborate the progenote evolutionary stage for both LUCA and at least the first part of the evolutionary stages of the ancestor of bacteria and that of archaea. Indeed, this polyphyletic origin would imply that the genetic code was still evolving because at least two ARSs, i.e. proteins that make the genetic code possible today, were still evolving. This would imply that the evolutionary stages involved were characterized not by cells but by protocells, that is, by progenotes because this is precisely the definition of a progenote. This conclusion would be strengthened by the observation that both GlyRS and LysRS originating in the phyletic lineages leading to bacteria and archaea, would demonstrate that, more generally, proteins were most likely still in rapid and progressive evolution. Namely, a polyphyletic origin of proteins which would qualify at least the initial phase of the evolutionary stage of the ancestor of bacteria and that of archaea as stages belonging to the progenote.

Over more than the past century, reports that chromosomes in Eukaryotes are linked have been published. Recently this has been confirmed by micromanipulation. The chromolinkers are DNAse sensitive, as has been previously reported. The arguments for and against chromolinkers have been reviewed, and a call for definitive research made, because if chromolinkers do exist, the whole basis for nuclear DNA genetics may require revision.

The prevailing consensus in scientific literature underscores the mutualistic bond between the microbiota and the human host, suggesting a finely tuned coevolutionary partnership that enhances the fitness of both parties. This symbiotic relationship has been extensively studied, with certain bacterial attributes being construed as hallmarks of natural selection favoring the benefit of the human host. Some scholars go as far as equating the intricate interplay between humans and their intestinal microbiota to that of endosymbiotic relationships, even conceptualizing microbiota as an integral human organ.

However, amidst the prevailing narrative of bacterial species being categorized as beneficial or detrimental to human health, a critical oversight often emerges – the inherent functional diversity within bacterial strains. Such reductionist perspectives risk oversimplifying the complex dynamics at play within the microbiome. Recent genomic analysis at the strain level is highly limited, which is surprising given that strain information provides critical data about selective pressures in the intestine. These pressures appear to focus more on the well-being of bacteria rather than human health. Connected to this is the extent to which animals depend on metabolic activity from intestinal bacteria, which varies widely across species. While omnivores like humans exhibit lower dependency, certain herbivores rely entirely on bacterial activity and have developed specialized compartments to house these bacteria.

In biological systems, solitary organisms or eusocial groups, the metabolic rate often scales allometrically with systems’ size, when they are inactive, and the scaling becomes nearly isometric when the systems are active. Here I propose a hypothesis attempting to offer a departing point for a general joint understanding of the difference in the scaling powers between inactive and active states. When the system is inactive, there exist inactive components, which consume less energy than the active ones, and the larger the system is, the larger the fraction of the inactive components, which leads to sublinear scaling. When the system is active, most inactive components are activated, which leads to nearly isometric scaling. I hypothesize that the disproportional fraction of the inactive components is caused by the diffusants screening in the complex transportation network. I.e., when metabolites or information diffuses in the system, due to the physical limitation of the network structure and the diffusant’s physical feature, not all the components can equally receive the diffusants so that these components are inactive. Using the mammalian pulmonary system, ant colonies, and other few systems as examples, I discuss how the screening leads to the allometric and isometric metabolic scaling powers in inactive and active states respectively. It is noteworthy that there are a few exceptions, in which the metabolic rate of the system has an isometric scaling relationship with size at rest. I show that these exceptions not only do not disapprove the hypothesis, but actually support it.

Building on and extending existing definitions of robustness and evolvability, we propose and utilize new formal definitions, with matching measures, of robustness and evolvability of systems with genotypes and corresponding phenotypes. We explain and show how these measures are more general and more representative of the concepts they stand for, than the commonly used/referenced measures originally proposed by Wagner. Further, a versatile digital modeling approach (BNK) is proposed that is inspired by NK systems. However, unlike NK systems, BNK incorporates a genotype and a phenotype, in addition to fitness. We develop and apply an Evolutionary Algorithm to a BNK-modeled system to find different types of perfect oscillators. We then map the resulting oscillating systems to possible genetic circuit realizations. Continuing with the synthetic biology theme, we also investigate the effect of noise in DNA synthesis on the predicted functionality of a DNA-based biosensor (i.e., its robustness), and we carry out a theoretical assessment of the evolvability of different types of ribozymes, undergoing directed evolution.

The pan-cancer initiative aims to study the origin patterns of cancer cell, the processes of carcinogenesis, and the signaling pathways from a perspective that spans across different types of cancer. The construction of the pan-cancer related gene regulatory network is helpful to excavate the commonalities in regulatory relationships among different types of cancers. It also aids in understanding the mechanisms behind cancer occurrence and development, which is of great scientific significance for cancer prevention and treatment. In light of the high dimension and large sample size of pan-cancer omics data, a causal pan-cancer gene regulation network inference algorithm based on stochastic complexity is proposed. With the network construction strategy of local first and then global, the stochastic complexity is used in the conditional independence test and causal direction inference for the candidate adjacent node set of the target nodes. This approach aims to decrease the time complexity and error rate of causal network learning. By applying this algorithm to the sample data of seven types of cancers in the TCGA database, including breast cancer, lung adenocarcinoma, and so on, the pan-cancer related causal regulatory networks are constructed, and their biological significance is verified. The experimental results show that this algorithm can eliminate the redundant regulatory relationships effectively and infer the pan-cancer regulatory network more accurately (https://github.com/LindeEugen/CNI-SC).

Fungal mycelium networks are large scale biological networks along which nutrients, metabolites flow. Recently, we discovered a rich spectrum of electrical activity in mycelium networks, including action-potential spikes and trains of spikes. Reasoning by analogy with animals and plants, where travelling patterns of electrical activity perform integrative and communicative mechanisms, we speculated that waves of electrical activity transfer information in mycelium networks. Using a new discrete space–time model with emergent radial spanning-tree topology, hypothetically comparable mycelial morphology and physically comparable information transfer, we provide physical arguments for the use of such a model, and by considering growing mycelium network by analogy with growing network of matter in the cosmic web, we develop mathematical models and theoretical concepts to characterise the parameters of the information transfer.