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.

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.

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.

Anticipation of ventricular tachyarrhythmias by a novel mathematical method: Further insights towards an early warning system in implantable cardioverter defibrillators

Implantable cardioverter defibrillators (ICD) are the most effective therapy to terminate malignant ventricular arrhythmias (VA) and therefore to prevent sudden cardiac death. Until today, there is no way to predict the onset of such VA. Our aim was to develop a mathematical model that could predict VA in a timely fashion. We analyzed the time series of R-R intervals from 3 groups. Two groups from the Spontaneous Ventricular Tachyarrhythmia Database (v 1.0) were analyzed from a set of 81 pairs of R-R interval time series records from patients, each pair containing one record before the VT episode (Dataset 1A) and one control record which was obtained during the follow up visit (Dataset 1B). A third data set was composed of the R-R interval time series of 54 subjects without a significant arrhythmia heart disease (Dataset 2). We developed a new method to transform a time series into a network for its analysis, the ε-regular graphs. This novel approach transforms a time series into a network which is sensitive to the quantitative properties of the time series, it has a single parameter (ε) to be adjusted, and it can trace long-range correlations. This procedure allows to use graph theory to extract the dynamics of any time series. The average of the difference between the VT and the control record graph degree of each patient, at each time window, reached a global minimum value of -2.12 followed by a drastic increase of the average graph until reaching a local maximum of 5.59. The global minimum and the following local maxima occur at the windows 276 and 393, respectively. This change in the connectivity of the graphs distinguishes two distinct dynamics occurring during the VA, while the states in between the 276 and 393, determine a transitional state. We propose this change in the dynamic of the R-R intervals as a measurable and detectable "early warning" of the VT event, occurring an average of 514.625 seconds (8:30 minutes) before the onset of the VT episode. It is feasible to detect retrospectively early warnings of the VA episode using their corresponding ε-regular graphs, with an average of 8:30 minutes before the ICD terminates the VA event.

The Ancient History of Peptidyl Transferase Center Formation as Told by Conservation and Information Analyses

The peptidyl transferase center (PTC) is the catalytic center of the ribosome and forms part of the 23S ribosomal RNA. The PTC has been recognized as the earliest ribosomal part and its origins embodied the First Universal Common Ancestor (FUCA). The PTC is frequently assumed to be highly conserved along all living beings. In this work, we posed the following questions: (i) How many 100% conserved bases can be found in the PTC? (ii) Is it possible to identify clusters of informationally linked nucleotides along its sequence? (iii) Can we propose how the PTC was formed? (iv) How does sequence conservation reflect on the secondary and tertiary structures of the PTC? Aiming to answer these questions, all available complete sequences of 23S ribosomal RNA from Bacteria and Archaea deposited on GenBank database were downloaded. Using a sequence bait of 179 bp from the PTC of Thermus termophilus, we performed an optimum pairwise alignment to retrieve the PTC region from 1424 filtered 23S rRNA sequences. These PTC sequences were multiply aligned, and the conserved regions were assigned and observed along the primary, secondary, and tertiary structures. The PTC structure was observed to be more highly conserved close to the adenine located at the catalytical site. Clusters of interrelated, co-evolving nucleotides reinforce previous assumptions that the PTC was formed by the concatenation of proto-tRNAs and important residues responsible for its assembly were identified. The observed sequence variation does not seem to significantly affect the 3D structure of the PTC ribozyme.

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.

Phenotypic Graphs and Evolution Unfold the Standard Genetic Code as the Optimal

In this work, we explicitly consider the evolution of the Standard Genetic Code (SGC) by assuming two evolutionary stages, to wit, the primeval RNY code and two intermediate codes in between. We used network theory and graph theory to measure the connectivity of each phenotypic graph. The connectivity values are compared to the values of the codes under different randomization scenarios. An error-correcting optimal code is one in which the algebraic connectivity is minimized. We show that the SGC is optimal in regard to its robustness and error-tolerance when compared to all random codes under different assumptions.

A unified model of the standard genetic code

The Rodin-Ohno (RO) and the Delarue models divide the table of the genetic code into two classes of aminoacyl-tRNA synthetases (aaRSs I and II) with recognition from the minor or major groove sides of the tRNA acceptor stem, respectively. These models are asymmetric but they are biologically meaningful. On the other hand, the standard genetic code (SGC) can be derived from the primeval RNY code (R stands for purines, Y for pyrimidines and N any of them). In this work, the RO-model is derived by means of group actions, namely, symmetries represented by automorphisms, assuming that the SGC originated from a primeval RNY code. It turns out that the RO-model is symmetric in a six-dimensional (6D) hypercube. Conversely, using the same automorphisms, we show that the RO-model can lead to the SGC. In addition, the asymmetric Delarue model becomes symmetric by means of quotient group operations. We formulate isometric functions that convert the class aaRS I into the class aaRS II and vice versa. We show that the four polar requirement categories display a symmetrical arrangement in our 6D hypercube. Altogether these results cannot be attained, neither in two nor in three dimensions. We discuss the present unified 6D algebraic model, which is compatible with both the SGC (based upon the primeval RNY code) and the RO-model.

On the Uniqueness of the Standard Genetic Code

In this work, we determine the biological and mathematical properties that are sufficient and necessary to uniquely determine both the primeval RNY (purine-any base-pyrimidine) code and the standard genetic code (SGC). These properties are: the evolution of the SGC from the RNY code; the degeneracy of both codes, and the non-degeneracy of the assignments of aminoacyl-tRNA synthetases (aaRSs) to amino acids; the wobbling property; the consideration that glycine was the first amino acid; the topological and symmetrical properties of both codes.

Symmetrical and Thermodynamic Properties of Phenotypic Graphs of Amino Acids Encoded by the Primeval RNY Code

The 12 different types of graphs of the 8 amino acids encoded by the presumably primeval RNY code are derived. The symmetry groups of these graphs are analyzed and coincide with the corresponding values of polar requirement for each amino acid. The symmetry groups at the codon level are partially carried over as a group or subgroup at the amino acid level. Measures of centrality of the 12 graphs indicate that all amino acids were equally relevant irrespective of its chronological order of its appearance. The elimination of any amino acid would be strongly selected against and therefore the genetic code at this stage was already frozen.