A Proposal for the RNAome at the Dawn of the Last Universal Common Ancestor.

From the most ancient RNAs, which followed an RNY pattern and folded into small hairpins, modern RNA molecules evolved by two different pathways, dubbed Extended Genetic Code 1 and 2, finally conforming to the current standard genetic code. Herein, we describe the evolutionary path of the RNAome based on these evolutionary routes. In general, all the RNA molecules analysed contain portions encoded by both genetic codes, but crucial features seem to be better recovered by Extended 2 triplets. In particular, the whole Peptidyl Transferase Centre, anti-Shine-Dalgarno motif, and a characteristic quadruplet of the RNA moiety of RNAse-P are clearly unveiled. Differences between bacteria and archaea are also detected; in most cases, the biological sequences are more stable than their controls. We then describe an evolutionary trajectory of the RNAome formation, based on two complementary evolutionary routes: one leading to the formation of essentials, while the other complemented the molecules, with the cooperative assembly of their constituents giving rise to modern RNAs.

A Proposal of the Ur-RNAome.

It is widely accepted that the earliest RNA molecules were folded into hairpins or mini-helixes. Herein, we depict the 2D and 3D conformations of those earliest RNA molecules with only RNY triplets, which Eigen proposed as the primeval genetic code. We selected 26 species (13 bacteria and 13 archaea). We found that the free energy of RNY hairpins was consistently lower than that of their corresponding shuffled controls. We found traces of the three ribosomal RNAs (16S, 23S, and 5S), tRNAs, 6S RNA, and the RNA moieties of RNase P and the signal recognition particle. Nevertheless, at this stage of evolution there was no genetic code (as seen in the absence of the peptidyl transferase centre and any vestiges of the anti-Shine-Dalgarno sequence). Interestingly, we detected the anticodons of both glycine (GCC) and threonine (GGU) in the hairpins of proto-tRNA.

Groups of Symmetries of the Two Classes of Synthetases in the Four-Dimensional Hypercubes of the Extended Code Type II.

Aminoacyl-tRNA synthetases (aaRSs) originated from an ancestral bidirectional gene (mirror symmetry), and through the evolution of the genetic code, the twenty aaRSs exhibit a symmetrical distribution in a 6-dimensional hypercube of the Standard Genetic Code. In this work, we assume a primeval RNY code and the Extended Genetic RNA code type II, which includes codons of the types YNY, YNR, and RNR. Each of the four subsets of codons can be represented in a 4-dimensional hypercube. Altogether, these 4 subcodes constitute the 6-dimensional representation of the SGC. We identify the aaRSs symmetry groups in each of these hypercubes. We show that each of the four hypercubes contains the following sets of symmetries for the two known Classes of synthetases: RNY: dihedral group of order 4; YNY: binary group; YNR: amplified octahedral group; and RNR: binary group. We demonstrate that for each hypercube, the group of symmetries in Class 1 is the same as the group of symmetries in Class 2. The biological implications of these findings are discussed.

Symmetrical distributions of aminoacyl-tRNA synthetases during the evolution of the genetic code.

In this work, we formulate the following question: How the distribution of aminoacyl-tRNA synthetases (aaRSs) went from an ancestral bidirectional gene (mirror symmetry) to the symmetrical distribution of aaRSs in a six-dimensional hypercube of the Standard Genetic Code (SGC)? We assume a primeval RNY code, two Extended Genetic RNA codes type 1 and 2, and the SGC. We outline the types of symmetries of the distribution of aaRSs in each code. The symmetry groups of aaRSs in each code are described, until the symmetries of the SGC display a mirror symmetry. Considering both Extended RNA codes the 20 aaRSs were already present before the Last Universal Ancestor. These findings reveal intricacies in the diversification of aaRSs accompanied by the evolution of the genetic code.

Natural History of DNA-Dependent DNA Polymerases: Multiple Pathways to the Origins of DNA.

One of the major evolutionary transitions that led to DNA replacing RNA as the primary informational molecule in biological systems is still the subject of an intense debate in the scientific community. DNA polymerases are currently split into various families. Families A, B, and C are the most significant. In bacteria and some types of viruses, enzymes from families A and C predominate, whereas family B enzymes are more common in Archaea, Eukarya, and some types of viruses. A phylogenetic analysis of these three families of DNA polymerase was carried out. We assumed that reverse transcriptase was the ancestor of DNA polymerases. Our findings suggest that families A and C emerged and organized themselves when the earliest bacterial lineages had diverged, and that these earliest lineages had RNA genomes that were in transition-that is, the information was temporally stored in DNA molecules that were continuously being produced by reverse transcription. The origin of DNA and the apparatus for its replication in the mitochondrial ancestors may have occurred independently of DNA and the replication machinery of other bacterial lineages, according to these two alternate modes of genetic material replication. The family C enzymes emerged in a particular bacterial lineage before being passed to viral lineages, which must have functioned by disseminating this machinery to the other lineages of bacteria. Bacterial DNA viruses must have evolved at least twice independently, in addition to the requirement that DNA have arisen twice in bacterial lineages. We offer two possible scenarios based on what we know about bacterial DNA polymerases. One hypothesis contends that family A was initially produced and spread to the other lineages through viral lineages before being supplanted by the emergence of family C and acquisition at that position of the principal replicative polymerase. The evidence points to the independence of these events and suggests that the viral lineage's acquisition of cellular replicative machinery was crucial for the establishment of a DNA genome in the other bacterial lineages, since these viral lineages may have served as a conduit for the machinery's delivery to other bacterial lineages that diverged with the RNA genome. Our data suggest that family B initially established itself in viral lineages and was transferred to ancestral Archaea lineages before the group diversified; thus, the DNA genome must have emerged first in this cellular lineage. Our data point to multiple evolutionary steps in the origins of DNA polymerase, having started off at least twice in the bacterial lineage and once in the archaeal lineage. Given that viral lineages are implicated in a significant portion of the distribution of DNA replication equipment in both bacterial (families A and C) and Archaeal lineages (family A), our data point to a complex scenario.

Human Coronavirus Cell Receptors Provide Challenging Therapeutic Targets.

Coronaviruses interact with protein or carbohydrate receptors through their spike proteins to infect cells. Even if the known protein receptors for these viruses have no evolutionary relationships, they do share ontological commonalities that the virus might leverage to exacerbate the pathophysiology. ANPEP/CD13, DPP IV/CD26, and ACE2 are the three protein receptors that are known to be exploited by several human coronaviruses. These receptors are moonlighting enzymes involved in several physiological processes such as digestion, metabolism, and blood pressure regulation; moreover, the three proteins are expressed in kidney, intestine, endothelium, and other tissues/cell types. Here, we spot the commonalities between the three enzymes, the physiological functions of the enzymes are outlined, and how blocking either enzyme results in systemic deregulations and multi-organ failures via viral infection or therapeutic interventions is addressed. It can be difficult to pinpoint any coronavirus as the target when creating a medication to fight them, due to the multiple processes that receptors are linked to and their extensive expression.

Prebiotic chemical refugia: multifaceted scenario for the formation of biomolecules in primitive Earth.

The origin of life was a cosmic event happened on primitive Earth. A critical problem to better understand the origins of life in Earth is the search for chemical scenarios on which the basic building blocks of biological molecules could be produced. Classic works in pre-biotic chemistry frequently considered early Earth as an homogeneous atmosphere constituted by chemical elements such as methane (CH4), ammonia (NH3), water (H2O), hydrogen (H2) and hydrogen sulfide (H2S). Under that scenario, Stanley Miller was capable to produce amino acids and solved the question about the abiotic origin of proteins. Conversely, the origin of nucleic acids has tricked scientists for decades once nucleotides are complex, though necessary molecules to allow the existence of life. Here we review possible chemical scenarios that allowed not only the formation of nucleotides but also other significant biomolecules. We aim to provide a theoretical solution for the origin of biomolecules at specific sites named "Prebiotic Chemical Refugia." Prebiotic chemical refugium should therefore be understood as a geographic site in prebiotic Earth on which certain chemical elements were accumulated in higher proportion than expected, facilitating the production of basic building blocks for biomolecules. This higher proportion should not be understood as static, but dynamic; once the physicochemical conditions of our planet changed periodically. These different concentration of elements, together with geochemical and astronomical changes along days, synodic months and years provided somewhat periodic changes in temperature, pressure, electromagnetic fields, and conditions of humidity, among other features. Recent and classic works suggesting most likely prebiotic refugia on which the main building blocks for biological molecules might be accumulated are reviewed and discussed.

The Spike Protein of SARS-CoV-2 Is Adapting Because of Selective Pressures.

The global scale of the COVID-19 pandemic has demonstrated the evolution of SARS-CoV-2 and the clues of adaptation. After two years and two months since the declaration of the pandemic, several variants have emerged and become fixed in the human population thanks to extrinsic selective pressures but also to the inherent mutational capacity of the virus. Here, we applied a neutral substitution evolution test to the spike (S) protein of Omicron's protein and compared it to the others' variant of concern (VOC) neutral evolution. We carried out comparisons among the interactions between the S proteins from the VOCs (Alpha, Beta, Gamma, Delta and Omicron) and the receptor ACE2. The shared amino acids among all the ACE2 binding S proteins remain constant, indicating that these amino acids are essential for the accurate binding to the receptor. The complexes of the RBD for every variant with the receptor were used to identify the amino acids involved in the protein-protein interaction (PPI). The RBD of Omicron establishes 82 contacts, compared to the 74 of the Wuhan original viral protein. Hence, the mean number of contacts per residue is higher, making the contact thermodynamically more stable. The RBDs of the VOCs are similar in sequence and structure; however, Omicron's RBD presents the largest deviation from the structure by 1.11 Å RMSD, caused by a set of mutations near the glycosylation N343. The chemical properties and structure near the glycosylation N343 of the Omicron S protein are different from the original protein, which provoke reduced recognition by the neutralizing antibodies. Our results hint that selective pressures are induced by mass vaccination throughout the world and by the persistence of recurrent infections in immunosuppressed individuals, who did not eliminate the infection and ended up facilitating the selection of viruses whose characteristics are different from the previous VOCs, less pathogenic but with higher transmissibility.

Structural Computational Analysis of the Natural History of Class I aminoacyl-tRNA Synthetases Suggests their Role in Establishing the Genetic Code.

The evolutionary history of Class I aminoacyl-tRNA synthetases (aaRS) through the reconstruction of ancestral sequences is presented. From structural molecular modeling, we sought to understand its relationship with the acceptor arms and the tRNA anticodon loop, how this relationship was established, and the possible implications in determining the genetic code and the translation system. The results of the molecular docking showed that in 7 out 9 aaRS, the acceptor arm and the anticodon loop bond practically in the same region. Domain accretion process in aaRS and repositioning of interactions between tRNAs and aaRS are illustrated. Based on these results, we propose that the operational code and the anticodon code coexisted, competing for the aaRS catalytic region, while consequently contributed to the stabilization of these proteins.

Neutral evolution test of the spike protein of SARS-CoV-2 and its implications in the binding to ACE2.

As the SARS-CoV-2 has spread and the pandemic has dragged on, the virus continued to evolve rapidly resulting in the emergence of new highly transmissible variants that can be of public health concern. The evolutionary mechanisms that drove this rapid diversity are not well understood but neutral evolution should open the first insight. The neutral theory of evolution states that most mutations in the nucleic acid sequences are random and they can be fixed or disappear by purifying selection. Herein, we performed a neutrality test to better understand the selective pressures exerted over SARS-CoV-2 spike protein from homologue proteins of Betacoronavirus, as well as to the spikes from human clinical isolates of the virus. Specifically, Tyr and Asn have higher occurrence rates on the Receptor Binding Domain (RBD) and in the overall sequence of spike proteins of Betacoronavirus, whereas His and Arg have lower occurrence rates. The in vivo evolutionary phenomenon of SARS-CoV-2 shows that Glu, Lys, Phe, and Val have the highest probability of occurrence in the emergent viral particles. Amino acids that have higher occurrence than the expected by the neutral control, are favorable and are fixed in the sequence while the ones that have lower occurrence than expected, influence the stability and/or functionality of the protein. Our results show that most unique mutations either for SARS-CoV-2 or its variants of health concern are under selective pressures, which could be related either to the evasion of the immune system, increasing the virus' fitness or altering protein - protein interactions with host proteins. We explored the consequences of those selected mutations in the structure and protein - protein interaction with the receptor. Altogether all these forces have shaped the spike protein and the continually evolving variants.

From RNA to DNA: Insights about the transition of informational molecule in the biological systems based on the structural proximity between the polymerases.

Structural relations in an evolutionary context of polymerases is crucial to gain insights into the transition from an RNA world to a Ribonucleoprotein world. Herein, we present a structural proximity tree for the polymerases, from which we observe that the enzymes that have RNA as substrate are more homogeneous than the group with DNA as substrate. The homogeneity observed in enzymes with RNA as a substrate, may be because they performed all steps in information processing. In this sense, the emergence of the DNA molecule posed new challenges to the biological systems, where several parts of the informational flow were individualized by the emergence of enzymes for each step. From the data presented, we propose a polymerase diversification model, in which we have RNA-dependent RNA polymerases as an ancestor and all other polymerases diverged directly from this group by a radiation process.

Origin of the 16S Ribosomal Molecule from Ancestor tRNAs.

We tested the hypothesis that concatemers of ancestral tRNAs gave rise to the 16S ribosomal RNA. We built an ancestral sequence of proto-tRNAs that showed a significant identity of 51.69% and a percentage of structural identity of 0.941 with the 3' upper domain of 16S ribosomal molecule. We also propose a hypothesis in which the small ribosomal subunit emerged by proto-tRNA fusion and worked as a point to bind RNAs in an open structure configuration. In this context, the two ribosomal subunits initially worked independently, and that the subunit junction, with consequent primitive ribosome formation, was mediated by interactions with tRNA molecules during the primordial genetic code formation.

Multiple Origins of Extracellular DNA Traps.

Extracellular DNA traps (ETs) are evolutionarily conserved antimicrobial mechanisms present in protozoa, plants, and animals. In this review, we compare their similarities in species of different taxa, and put forward the hypothesis that ETs have multiple origins. Our results are consistent with a process of evolutionary convergence in multicellular organisms through the application of a congruency test. Furthermore, we discuss why multicellularity is related to the presence of a mechanism initiating the formation of ETs.

Novel gene signatures for stage classification of the squamous cell carcinoma of the lung.

The squamous cell carcinoma of the lung (SCLC) is one of the most common types of lung cancer. As GLOBOCAN reported in 2018, lung cancer was the first cause of death and new cases by cancer worldwide. Typically, diagnosis is made in the later stages of the disease with few treatment options available. The goal of this work was to find some key components underlying each stage of the disease, to help in the classification of tumor samples, and to increase the available options for experimental assays and molecular targets that could be used in treatment development. We employed two approaches. The first was based in the classic method of differential gene expression analysis, network analysis, and a novel concept known as network gatekeepers. The second approach was using machine learning algorithms. From our combined approach, we identified two sets of genes that could function as a signature to identify each stage of the cancer pathology. We also arrived at a network of 55 nodes, which according to their biological functions, they can be regarded as drivers in this cancer. Although biological experiments are necessary for their validation, we proposed that all these genes could be used for cancer development treatments.

The Theory of Chemical Symbiosis: A Margulian View for the Emergence of Biological Systems (Origin of Life).

The theory of chemical symbiosis (TCS) suggests that biological systems started with the collaboration of two polymeric molecules existing in early Earth: nucleic acids and peptides. Chemical symbiosis emerged when RNA-like nucleic acid polymers happened to fold into 3D structures capable to bind amino acids together, forming a proto peptidyl-transferase center. This folding catalyzed the formation of quasi-random small peptides, some of them capable to bind this ribozyme structure back and starting to form an initial layer that would produce the larger subunit of the ribosome by accretion. TCS suggests that there is no chicken-and-egg problem into the emergence of biological systems as RNAs and peptides were of equal importance to the origin of life. Life has initially emerged when these two macromolecules started to interact in molecular symbiosis. Further, we suggest that life evolved into progenotes and cells due to the emergence of new layers of symbiosis. Mutualism is the strongest force in biology, capable to create novelties by emergent principles; on which the whole is bigger than the sum of the parts. TCS aims to apply the Margulian view of biology into the origins of life field.

Information theory unveils the evolution of tRNA identity elements in the three domains of life.

We determined the identity elements of each tRNA isoacceptor for the three domains of life: Eubacteria, Archaea, and Eukarya. Our analyses encompass the most updated and curated available databases using an information theory approach. We obtained a collection of identity clusters for each of the isoacceptors of the 20 canonical amino acids for the three major domains of life. The identity clusters for all isoacceptors are compared within and among the three domains to determine their pattern of differentiation and to shed light on the evolution of the identity elements.

A neutral evolution test derived from a theoretical amino acid substitution model.

A neutral evolution model that explicitly considers codons, amino acids, and the degeneracy of the genetic code is developed. The model is built from nucleotides up to amino acids, and it represents a refinement of the neutral theory of molecular evolution. The model is based on a stochastic process that leads to a stationary probability distribution of amino acids. The latter is used as a neutral test of evolution. We provide some examples for assessing the neutrality test for a small set of protein sequences. The Jukes-Cantor model is generalized to deal with amino acids and it is compared with our neutral model, along with the empirical BLOSUM62 substitution model. The neutral test provides a baseline to which the evolution of any protein can be analyzed, and it clearly helps in discerning putative amino acids with unexpected frequencies that might be under positive or negative selection. Our model and neutral test are as universal as the standard genetic code.

How to eliminate taeniasis/cysticercosis: porcine vaccination and human chemotherapy (Part 2).

BACKGROUND: The application of effective vaccines against pig cysticercosis and mass chemotherapy against pig cysticercosis and human taeniasis have shown the feasibility of interrupting the parasite's life cycle in endemic areas. METHODS: A mathematical model that divides the population into susceptible, infected, and vaccinated individuals is formulated. The model is based upon the life cycle of the parasite. Computer numerical simulation experiments to evaluate the impact of pig vaccination under different vaccination schedules, and combined intervention strategies including pig vaccination and anthelmintic treatment against human taeniasis are carried out. RESULTS: Vaccination against either pig cysticercosis or against human taeniasis will influence the transmission dynamics not only among vaccinees but also the dynamics of the other hosts as well. When the protective efficacy and/or the coverage rate is less than 100%, different mass interventions like vaccinating the pig population twice in combination with chemotherapeutic treatment against human taeniasis, the elimination of the infection in both pigs and humans can also be achieved. CONCLUSIONS: Our mathematical model has the potential for planning, and designing effective intervention strategies including both mass vaccination and/or chemotherapeutic treatment to eliminate pig cysticercosis, human taeniasis and human neurocysticercosis. The model can be adapted to any given community with mild, moderate endemicity, or even in hyperendemic regions.

Mathematical model of the life cycle of taenia-cysticercosis: transmission dynamics and chemotherapy (Part 1).

BACKGROUND: Taenia solium is the aetiological agent of human taeniasis, pig cysticercosis and human neurocysticercosis, which are serious public health problems, especially in developing countries. METHODS: A mathematical model of the transmission dynamics of taeniasis-cysticercosis is formulated. The model consists of a coupled system of differential equations, which are density-dependent equations for describing the flow of the parasite through the life cycle. The model is hybrid since it comprises deterministic equations with stochastic elements which describe changes in the mean parasite burden and incorporates the overall pattern of the parasites' distribution. RESULTS: Sensitivity and bifurcation analyses were carried out to determine the range of values of the model. The model can reproduce the observed epidemiological patterns of human taeniasis, pig and human cysticercosis. For example, for a wide range of parameter values, the mean intensity of adult worms tends to rapidly stabilize in one parasite per individual host. From this model, we also derived a Susceptible-Infected model to describe the prevalence of infection in humans and pigs. Chemotherapeutic interventions against pig cysticercosis or human taeniasis may reduce rapidly and effectively the mean intensity of human taeniasis, pig cysticercosis and human cysticercosis. This effect can be achieved even if the protective efficacy of the drug is of the order of 90% and the coverage rate is 90%. This means that health in humans infected either with adult worms or cysticerci may be achieved by the application of anthelmintic drugs against pig cysticercosis. However, treatment against human cysticercosis alone, does not influence neither human teniasis nor pig cysticercosis. This is because human cysticercosis infection does not influence the value of the basic reproductive number (Ro). CONCLUSIONS: Even coverage of 100% in the administration of anthelmintics did not eliminate the infection. Then elimination of the infection in all hosts does not seem a feasible goal to achieve by administering only chemotherapeutic interventions. Throughout the manuscript a discussion of our model in the context of other models of taeniasis-cysticercosis is presented.

Multivariate Entropy Characterizes the Gene Expression and Protein-Protein Networks in Four Types of Cancer.

There is an important urgency to detect cancer at early stages to treat it, to improve the patients' lifespans, and even to cure it. In this work, we determined the entropic contributions of genes in cancer networks. We detected sudden changes in entropy values in melanoma, hepatocellular carcinoma, pancreatic cancer, and squamous lung cell carcinoma associated to transitions from healthy controls to cancer. We also identified the most relevant genes involved in carcinogenic process of the four types of cancer with the help of entropic changes in local networks. Their corresponding proteins could be used as potential targets for treatments and as biomarkers of cancer.