Equus roundworms (Parascaris univalens) are undergoing rapid divergence due to host and environment factors

Background The evolution of parasites is often directly affected by the host's environment. Studies on the evolution of the same parasites in different hosts are extremely attractive and highly relevant to our understanding of divergence and speciation. Methods Here we performed whole genome sequencing of Parascaris univalens from different Equus hosts (horses, zebras and donkeys). Phylogenetic and selection analysis was performed to study the divergence and adaptability of P. univalens. Results At the genetic level, multiple lines of evidence support that P. univalens were mainly separated into two clades (Horse-derived and Zebra & Donkey-derived). This divergence began at 300-1000 years ago, and we found that most of the key enzymes related to glycolysis were under strong positive selection in zebra & donkey-derived roundworms, but lipid related metabolism system was under positive selection in the horse-derived roundworms, indicating that the adaptive evolution of metabolism may drive the divergence in past few centuries. In addition, we found that some drug-related genes have a significantly higher degree of selection in different populations. Conclusions This work reports evidence that the host’s diet drives the divergence of roundworms for the first time, and also supports that divergence is a continuous and dynamic process, and continuous monitoring of the effects of differences in nutritional and drug history on rapid evolution of roundworms are conducive to further understanding host-parasite interactions.

Creatine utilization as a sole nitrogen source in Pseudomonas putida KT2440 is transcriptionally regulated by CahR

Glutamine amidotransferase-1 domain-containing AraC-family transcriptional regulators (GATRs) are present in the genomes of many bacteria, including all Pseudomonas species. The involvement of several characterized GATRs in amine-containing compound metabolism has been determined, but the full scope of GATR ligands and regulatory networks are still unknown. Here, we characterize Pseudomonas putida's detection of the animal-derived amine compound, creatine, a compound particularly enriched in muscle and ciliated cells by a creatine-specific GATR, PP_3665, here named CahR (Creatine amidohydrolase Regulator). cahR is necessary for transcription of the gene encoding creatinase (PP_3667/creA) in the presence of creatine and is critical for P. putida's ability to utilize creatine as a sole source of nitrogen. The CahR/creatine regulon is small and electrophoretic mobility shift demonstrates strong and specific CahR binding only at the creA promoter, supporting the conclusion that much of the regulon is dependent on downstream metabolites. Phylogenetic analysis of creA orthologs associated with cahR orthologs highlights a strain distribution and organization supporting likely horizontal gene transfer, particularly evident within the genus Acinetobacter. This study identifies and characterizes the GATR that transcriptionally controls P. putida metabolism of creatine, broadening the scope of known GATR ligands and suggesting GATR diversification during evolution of metabolism for aliphatic nitrogen compounds.

Formation of Thiophene under Simulated Volcanic Hydrothermal Conditions on Earth—Implications for Early Life on Extraterrestrial Planets?

Thiophene was detected on Mars during the Curiosity mission in 2018. The compound was even suggested as a biomarker due to its possible origin from diagenesis or pyrolysis of biological material. In the laboratory, thiophene can be synthesized at 400 °C by reacting acetylene and hydrogen sulfide on alumina. We here show that thiophene and thiophene derivatives are also formed abiotically from acetylene and transition metal sulfides such as NiS, CoS and FeS under simulated volcanic, hydrothermal conditions on Early Earth. Exactly the same conditions were reported earlier to have yielded a plethora of organic molecules including fatty acids and other components of extant metabolism. It is therefore tempting to suggest that thiophenes from abiotic formation could indicate sites and conditions well-suited for the evolution of metabolism and potentially for the origin-of-life on extraterrestrial planets.

Tracing Molecular Properties Throughout Evolution: A Chemoinformatic Approach.

<p>Evolution of metabolism is a longstanding yet unresolved question, and several hypotheses were proposed to address this complex process from a Darwinian point of view. Modern statistical bioinformatic approaches targeted to the comparative analysis of genomes are being used to detect signatures of natural selection at the gene and population level, as an attempt to understand the origin of primordial metabolism and its expansion. These studies, however, are still mainly centered on genes and the proteins they encode, somehow neglecting the small organic chemicals that support life processes. In this work, we selected steroids as an ancient family of metabolites widely distributed in all eukaryotes and applied unsupervised machine learning techniques to reveal the traits that natural selection has imprinted on molecular properties throughout the evolutionary process. Our results clearly show that sterols, the primal steroids that first appeared, have more conserved properties and that, from then on, more complex compounds with increasingly diverse properties have emerged, suggesting that chemical diversification parallels the expansion of biological complexity. In a wider context, these findings highlight the worth of chemoinformatic approaches to a better understanding the evolution of metabolism.</p>

Tracing Molecular Properties Throughout Evolution: A Chemoinformatic Approach.

<p>Evolution of metabolism is a longstanding yet unresolved question, and several hypotheses were proposed to address this complex process from a Darwinian point of view. Modern statistical bioinformatic approaches targeted to the comparative analysis of genomes are being used to detect signatures of natural selection at the gene and population level, as an attempt to understand the origin of primordial metabolism and its expansion. These studies, however, are still mainly centered on genes and the proteins they encode, somehow neglecting the small organic chemicals that support life processes. In this work, we selected steroids as an ancient family of metabolites widely distributed in all eukaryotes and applied unsupervised machine learning techniques to reveal the traits that natural selection has imprinted on molecular properties throughout the evolutionary process. Our results clearly show that sterols, the primal steroids that first appeared, have more conserved properties and that, from then on, more complex compounds with increasingly diverse properties have emerged, suggesting that chemical diversification parallels the expansion of biological complexity. In a wider context, these findings highlight the worth of chemoinformatic approaches to a better understanding the evolution of metabolism.</p>

Tracing Molecular Properties Throughout Evolution: A Chemoinformatic Approach.

<p>Evolution of metabolism is a longstanding yet unresolved question, and several hypotheses were proposed to address this complex process from a Darwinian point of view. Modern statistical bioinformatic approaches targeted to the comparative analysis of genomes are being used to detect signatures of natural selection at the gene and population level, as an attempt to understand the origin of primordial metabolism and its expansion. These studies, however, are still mainly centered on genes and the proteins they encode, somehow neglecting the small organic chemicals that support life processes. In this work, we selected steroids as an ancient family of metabolites widely distributed in all eukaryotes and applied unsupervised machine learning techniques to reveal the traits that natural selection has imprinted on molecular properties throughout the evolutionary process. Our results clearly show that sterols, the primal steroids that first appeared, have more conserved properties and that, from then on, more complex compounds with increasingly diverse properties have emerged, suggesting that chemical diversification parallels the expansion of biological complexity. In a wider context, these findings highlight the worth of chemoinformatic approaches to a better understanding the evolution of metabolism.</p>

A Possible Primordial Acetyleno/Carboxydotrophic Core Metabolism

Carbon fixation, in addition to the evolution of metabolism, is a main requirement for the evolution of life. Here, we report a one-pot carbon fixation of acetylene (C2H2) and carbon monoxide (CO) by aqueous nickel sulfide (NiS) under hydrothermal (>100 °C) conditions. A slurry of precipitated NiS converts acetylene and carbon monoxide into a set of C2–4-products that are surprisingly representative for C2–4-segments of all four central CO2-fixation cycles of the domains Bacteria and Archaea, whereby some of the products engage in the same interconversions, as seen in the central CO2-fixation cycles. The results suggest a primordial, chemically predetermined, non-cyclic acetyleno/carboxydotrophic core metabolism. This metabolism is based on aqueous organo–metal chemistry, from which the extant central CO2-fixation cycles based on thioester chemistry would have evolved by piecemeal modifications.

A Computational Framework to Study the Primary Lifecycle Metabolism of Arabidopsis thaliana

Stoichiometric Models of metabolism have proven valuable tools for increased understanding of metabolism and accuracy of synthetic biology interventions to achieve desirable phenotypes. Such models have been used in conjunction with optimization-based and have provided “snapshot” views of organism metabolism at specific stages of growth, generally at exponential growth. This approach has limitations in that metabolic history of the modeled system cannot be studied. The inability to study the complete metabolic history has limited stoichiometric metabolic modeling only to the static investigations of an inherently dynamic process. In this work, we have sought to address this limitation by introducing an optimization-based computational framework and applying to a stoichiometric model of the model plant Arabidopsis thaliana of four linked sub-models of leaf, root, seed, and stem tissues which models the core carbon metabolism through the lifecycle of arabidopsis (named as p-ath780). Uniquely, this framework and model considers diurnal metabolism, changes in tissue mass, carbohydrate storage, and loss of plant mass to senescence and seed dispersal. p-ath780 provide “snapshots” of core-carbon metabolism at one hour intervals of growth, in order to show the evolution of metabolism and whole-plant growth across the lifecycle of a single representative plant. Further, it can simulate important growth stages including seed germination, leaf development, flower production, and silique ripening. The computational framework has shown broad agreement with published experimental data in tissue mass yield, maintenance cost, senescence cost, and whole-plant growth checkpoints. Having focused on core-carbon metabolism, it serves as a scaffold for lifecycle models of other plant systems, to further increase the sophistication of in silico metabolic modeling, and to increase the range of hypotheses which can be investigated in silico. As an example, we have investigated the effect of alternate growth objectives on this plant over the lifecycle.Author SummaryIn an attempt to study the evolution of metabolism across the lifecycle of plants, in this work we have created an optimization-based framework for the in silico modeling of plant metabolism across the lifecycle of a model plant. We then applied this framework to four core-carbon tissue-level (namely, leaf, root, seed, and stem) stoichiometric models of the model plant species Arabidopsis thaliana, and further informed this framework with a wide array of published in vivo data to increase model and framework accuracy. Unique to the p-ath780 model, comparted to other models of plant metabolism, is the simultaneous considerations of diurnal metabolism, carbohydrate storage, changes in tissue mass (including losses), and changes in metabolism with respect to plant growth stage. This provides a more complete picture of plant metabolism and allows for a wider array of future studies of plant metabolism, particularly since we have only modeled the core carbon metabolism of A. thaliana, allowing this work to serve as a framework for studies of other plant systems.

Phosphates as Energy Sources to Expand Metabolic Networks

Phosphates are essential for modern metabolisms. A recent study reported a phosphate-free metabolic network and suggested that thioesters, rather than phosphates, could alleviate thermodynamic bottlenecks of network expansion. As a result, it was considered that a phosphorus-independent metabolism could exist before the phosphate-based genetic coding system. To explore the origin of phosphorus-dependent metabolism, the present study constructs a protometabolic network that contains phosphates prebiotically available using computational systems biology approaches. It is found that some primitive phosphorylated intermediates could greatly alleviate thermodynamic bottlenecks of network expansion. Moreover, the phosphorus-dependent metabolic network exhibits several ancient features. Taken together, it is concluded that phosphates played a role as important as that of thioesters during the origin and evolution of metabolism. Both phosphorus and sulfur are speculated to be critical to the origin of life.