Journal of Molecular Evolution最新文献

Cold-active enzymes have recently gained popularity because of their high activity at lower temperatures than their mesophilic and thermophilic counterparts, enabling them to withstand harsh reaction conditions and enhance industrial processes. Cold-active lipases are enzymes produced by psychrophiles that live and thrive in extremely cold conditions. Cold-active lipase applications are now growing in the detergency, synthesis of fine chemicals, food processing, bioremediation, and pharmaceutical industries. The cold adaptation mechanisms exhibited by these enzymes are yet to be fully understood. Using phylogenetic analysis, and advanced deep learning-based protein structure prediction tool Alphafold2, we identified an evolutionary processes in which a conserved cold-active-like motif is presence in a distinct subclade of the tree and further predicted and simulated the three-dimensional structure of a putative cold-active lipase with the cold active motif, Glalip03, from Glaciozyma antarctica PI12. Molecular dynamics at low temperatures have revealed global stability over a wide range of temperatures, flexibility, and the ability to cope with changes in water and solvent entropy. Therefore, the knowledge we uncover here will be crucial for future research into how these low-temperature-adapted enzymes maintain their overall flexibility and function at lower temperatures.

We present a non-equilibrium thermodynamics approach to the multilevel theory of learning for the study of molecular evolution. This approach allows us to study the explicit time dependence of molecular evolutionary processes and their impact on entropy production. Interpreting the mathematical expressions, we can show that two main contributions affect entropy production of molecular evolution processes which can be identified as mutation and gene transfer effects. Accordingly, our results show that the optimal adaptation of organisms to external conditions in the context of evolutionary processes is driven by principles of minimum entropy production. Such results can also be interpreted as the basis of some previous postulates of the theory of learning. Although our macroscopic approach requires certain simplifications, it allows us to interpret molecular evolutionary processes using thermodynamic descriptions with reference to well-known biological processes.

Gene expression is an inherently noisy process that is constrained by natural selection. Yet the condition dependence of constraint on expression noise remains unclear. Here, we address this problem by studying constraint on expression noise of E. coli genes in eight diverse growth conditions. In particular, we use variation in expression noise as an analog for constraint, examining its relationships to expression level and to the number of regulatory inputs from transcription factors across and within conditions. We show that variation in expression noise is negatively associated with expression level, implicating constraint to minimize expression noise of highly expressed genes. However, this relationship is condition dependent, with the strongest constraint observed when E. coli are grown in the presence of glycerol or ciprofloxacin, which result in carbon or antibiotic stress, respectively. In contrast, we do not observe evidence of constraint on expression noise of highly regulated genes, suggesting that highly expressed and highly regulated genes represent distinct classes of genes. Indeed, we find that essential genes are often highly expressed but not highly regulated, with elevated expression noise in glycerol and ciprofloxacin conditions. Thus, our findings support the hypothesis that selective constraint on expression noise is condition dependent in E. coli, illustrating how it may play a critical role in ensuring expression stability of essential genes in unstable environments.

The theory of selection fluctuation between generations has been a topic with much activities in population genetics and molecular evolution in 1970's. Most studies suggested that, as the result of fluctuating selection between generations, the frequency of an (on average) neutral mutation may fluctuate around 0.5 during the long-term evolution before it was ultimately fixed or lost. However, this pattern can only be derived from a specific type Wright-Fisher additive model, coined by the Nei-Yokoyama puzzle. In this commentary, I revisited this issue and figured out a theoretical assumption that has never been claimed explicitly, the notion of reference phenotype. Consider one locus with two-alleles: A is the wildtype allele and A' is the mutation. The fluctuating selection model actually requires a constraint that one of three genotypes (AA, AA', or A'A') must maintain a constant fitness without fluctuating between generations. It appears that the balancing selection at a frequency of 0.5 emerges only when the heterozygote (AA') is the reference genotype. Because it is difficult to determine which genotype could be the reference genotype in a real population, a desirable population genetics model should take all three possibilities into account. To this end, I propose a mixture model, where each genotype has a certain chance to be the reference genotype. My analysis showed that the emergence of balancing selection depends on the relative proportions of three different reference genotypes.

Phylogenetics has been widely used in molecular biology to infer the evolutionary relationships among species. With the rapid development of sequencing technology, genomic data with thousands of sites become increasingly common in phylogenetic analysis, while heterogeneity among sites arises as one of the major challenges. A single homogeneous model is not sufficient to describe the evolution of all sites and partitioned models are often employed to model the evolution of heterogeneous sites by partitioning them into distinct groups and utilizing distinct evolutionary models for each group. It is crucial to determine the best partitioning, which greatly affects the reconstruction correctness of phylogeny. However, the best partitioning is usually intractable to obtain in practice. Traditional partitioning methods rely on heuristic algorithms or greedy search to determine the best ones in their solution space, are usually time consuming, and with no guarantee of optimality. In this study, we propose a novel partitioning approach, termed PsiPartition, based on the parameterized sorting indices of sites and Bayesian optimization. We apply our method to empirical datasets, and it performs significantly better compared to existing methods, in terms of Bayesian information criterion (BIC) and the corrected Akaike information criterion (AICc). We test PsiPartition on the simulated datasets with different site heterogeneity, alignment lengths, and number of loci. It is demonstrated that PsiPartition evidently and stably outperforms other methods in terms of the Robinson-Foulds (RF) distance between the true simulated trees and the reconstructed trees, especially on the data with more site heterogeneity. More importantly, our proposed Bayesian optimization-based method, for the first time, provides a new general framework to efficiently determine the optimal number of partitions. The corresponding reproducible source code and data are available at http://github.com/xu-shi-jie/PsiPartition .

Locations of DNA replication initiation in prokaryotes, called "origins of replication", are well-characterized. However, a mechanistic understanding of the sequence dependence of the local unzipping of double-stranded DNA, the first step towards replication initiation, is lacking. Here, utilizing a Markov chain model that was created to address the directional nature of DNA unzipping and replication, we model the sequence dependence of local melting of double-stranded linear DNA segments. We show that generalized palindromic sequences with high nucleotide skews have a low kinetic barrier for local melting near melting temperatures. This allows for such sequences to function as potential replication origins. We support our claim with evidence for high-skew palindromic sequences within the replication origins of mitochondrial DNA, bacteria, archaea and plasmids.

The tropical eastern Pacific (TEP) is a biogeographic region with a substantial set of isolated oceanic islands and mainland shoreline habitat barriers, as well as complex oceanographic dynamics due to major ocean currents, upwelling areas, eddies, and thermal instabilities. These characteristics have shaped spatial patterns of biodiversity between and within species of reef and shore fishes of the region, which has a very high rate of endemism. Scorpaenodes xyris, a small ecologically cryptic reef-dwelling scorpionfish, is widely distributed throughout the TEP, including all the mainland reef areas and all the oceanic islands. This wide distribution and its ecological characteristics make this species a good model to study the evolutionary history of this type of reef fish across the breadth of a tropical biogeographical region. Our evaluation of geographic patterns of genetic (mitochondrial and nuclear) variation shows that S. xyris comprises two highly differentiated clades (A and B), one of which contains four independent evolutionary subunits. Clade A includes four sub-clades: 1. The Cortez mainland Province; 2. The Revillagigedo Islands; 3. Clipperton Atoll; and 4. The Galapagos Islands. Clade B, in contrast, comprises a single unit that includes the Mexican and Panamic mainland provinces, plus Cocos Island. This geographical arrangement largely corresponds to previously indicated regionalization of the TEP. Oceanic distances isolating the islands have produced much of that evolutionary pattern, although oceanographic processes likely have also contributed.

Hemoglobin and red blood cells (erythrocytes) have been studied extensively from the perspective of life and biomedical sciences. However, no analysis of hemoglobin and red blood cells from the perspective of chemical thermodynamics has been reported in the literature. Such an analysis would provide an insight into their structure and turnover from the aspect of biothermodynamics and bioenergetics. In this paper, a biothermodynamic analysis was made of hemoglobin and red blood cells. Molecular formulas, empirical formulas, biosynthesis reactions, and thermodynamic properties of formation and biosynthesis were determined for the alpha chain, beta chain, heme B, hemoglobin and red blood cells. Empirical formulas and thermodynamic properties of hemoglobin were compared to those of other biological macromolecules, which include proteins and nucleic acids. Moreover, the energetic requirements of biosynthesis of hemoglobin and red blood cells were analyzed. Based on this, a discussion was made of the specific structure of red blood cells (i.e. no nuclei nor organelles) and its role as an evolutionary adaptation for more energetically efficient biosynthesis needed for the turnover of red blood cells.