Modeling cell populations metabolism and competition under maximum power constraints.

Ecological interactions are fundamental at the cellular scale, addressing the possibility of a description of cellular systems that uses language and principles of ecology. In this work, we use a minimal ecological approach that encompasses growth, adaptation and survival of cell populations to model cell metabolisms and competition under energetic constraints. As a proof-of-concept, we apply this general formulation to study the dynamics of the onset of a specific blood cancer-called Multiple Myeloma.

Identification of Conserved Epitopes in SARS-CoV-2 Spike and Nucleocapsid Protein.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus that first occurred in Wuhan in December 2019. The spike glycoproteins and nucleocapsid proteins are the most common targets for the development of vaccines and antiviral drugs.

Objective: We herein analyze the rate of evolution along with the sequences of spike and nucleocapsid proteins in relation to the spatial locations of their epitopes, previously suggested to contribute to the immune response caused by SARS-CoV-2 infections.

Temporal evolution and adaptation of SARS-CoV-2 codon usage.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first occurred in Wuhan (China) in December of 2019. Since the outbreak, it has accumulated mutations on its coding sequences to optimize its adaptation to the human host. The identification of its genetic variants has become crucial in tracking and evaluating their spread across the globe.

Evolutionary pressures and codon bias in low complexity regions of plasmodia.

The biological meaning of low complexity regions in the proteins of Plasmodium species is a topic of discussion in evolutionary biology. There is a debate between selectionists and neutralists, who either attribute or do not attribute an effect of low-complexity regions on the fitness of these parasites, respectively. In this work, we comparatively study 22 Plasmodium species to understand whether their low complexity regions undergo a neutral or, rather, a selective and species-dependent evolution.

Bacterial Protein Interaction Networks: Connectivity is Ruled by Gene Conservation, Essentiality and Function.

Background: Protein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work, we relate conservation, essentiality and functional repertoire of a gene to the connectivity ( the number of interactions, links) of the corresponding protein in the PPI network.

Methods: On a set of 42 bacterial genomes of different sizes, and with reasonably separated evolutionary trajectories, we investigate three issues: i) whether the distribution of connectivities changes between PPI subnetworks of essential and nonessential genes; ii) how gene conservation, measured both by the evolutionary retention index (ERI) and by evolutionary pressures, is related to the connectivity of the corresponding protein; iii) how PPI connectivities are modulated by evolutionary and functional relationships, as represented by the Clusters of Orthologous Genes (COGs).

Codon usage bias and environmental adaptation in microbial organisms.

In each genome, synonymous codons are used with different frequencies; this general phenomenon is known as codon usage bias. It has been previously recognised that codon usage bias could affect the cellular fitness and might be associated with the ecology of microbial organisms. In this exploratory study, we investigated the relationship between codon usage bias, lifestyles (thermophiles vs.

Co-evolution between codon usage and protein-protein interaction in bacteria.

We study the correlation between the codon usage bias of genetic sequences and the network features of protein-protein interaction (PPI) in bacterial species. We use PCA techniques in the space of codon bias indices to show that genes with similar patterns of codon usage have a significantly higher probability that their encoded proteins are functionally connected and interacting. Importantly, this signal emerges when multiple aspects of codon bias are taken into account at the same time.

Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December of 2019, causes a severe acute respiratory illness with a high mortality rate, and has spread around the world. To gain an understanding of the evolution of the newly emerging SARS-CoV-2, we herein analyzed the codon usage pattern of SARS-CoV-2. For this purpose, we compared the codon usage of SARS-CoV-2 with that of other viruses belonging to the subfamily of .

Codon usage bias in radioresistant bacteria.

The relationship between patterns of codon usage bias (CUB), the preferential usage of synonimous nucleotide triplets encoding the same amino acid, and radioresistance was investigated int he genomes of 16 taxonomically distinct radioresistant prokaryotic organisms and in a control set of 11 non-radioresistant bacteria. The radioresistant species were found to be strongly biased towards G and C in the third synonimous codon position. ENC and neutrality plots also sugest that CUB in radioresistant bacteria is mainly affected by mutational bias.

Mutations in disordered proteins as early indicators of nucleic acid changes triggering speciation.

In this study, we analyze the role of different structural variants of proteins in the speciation processes. We separate human and mouse proteomes (taken as a reference) into three previously defined variants of disorder: ordered proteins (ORDPs), structured proteins with intrinsically disordered protein regions (IDPRs), and intrinsically disordered proteins (IDPs). Then, using the representation we call here Forsdyke plot, we study the correlation of DNA divergence with the corresponding protein (phenotypic) divergence in the three variants, comparing human and mouse coding sequences with their homologs from 26 eukaryotes.

Evolutionary Forces and Codon Bias in Different Flavors of Intrinsic Disorder in the Human Proteome.

In this study, we perform a systematic analysis of evolutionary forces (i.e., mutational bias and natural selection) that shape the codon usage bias of human genes encoding proteins characterized by different flavors of intrinsic disorder.

Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell.

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole.

Information Thermodynamics for Time Series of Signal-Response Models.

The entropy production in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. Such a connection was formalized for bipartite (or multipartite) systems with an integral fluctuation theorem in [Phys. Rev.

Essentiality, conservation, evolutionary pressure and codon bias in bacterial genomes.

Essential genes constitute the core of genes which cannot be mutated too much nor lost along the evolutionary history of a species. Natural selection is expected to be stricter on essential genes and on conserved (highly shared) genes, than on genes that are either nonessential or peculiar to a single or a few species. In order to further assess this expectation, we study here how essentiality of a gene is connected with its degree of conservation among several unrelated bacterial species, each one characterised by its own codon usage bias.

Causal influence in linear Langevin networks without feedback.

The intuition of causation is so fundamental that almost every research study in life sciences refers to this concept. However, a widely accepted formal definition of causal influence between observables is still missing. In the framework of linear Langevin networks without feedback (linear response models) we propose a measure of causal influence based on a new decomposition of information flows over time.

Molecular Dissection Using Array Comparative Genomic Hybridization and Clinical Evaluation of An Infertile Male Carrier of An Unbalanced Y;21 Translocation: A Case Report and Review of The Literature.

Chromosomal defects are relatively frequent in infertile men however, translocations between the Y chromosome and autosomes are rare and less than 40 cases of Y-autosome translocation have been reported. In particular, only three individuals has been described with a Y;21 translocation, up to now. We report on an additional case of an infertile man in whom a Y;21 translocation was associated with the deletion of a large part of the Y chromosome long arm.

Codon Bias Patterns of E. coli's Interacting Proteins.

Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms.

The challenge of increasing Pfam coverage of the human proteome.

It is a worthy goal to completely characterize all human proteins in terms of their domains. Here, using the Pfam database, we asked how far we have progressed in this endeavour. Ninety per cent of proteins in the human proteome matched at least one of 5494 manually curated Pfam-A families.

Tuning the precision of predictors to reduce overestimation of protein disorder over large datasets.

This is a study on the precision of four known protein disorder predictors, ranked among the best-performing ones: DISOPRED2, PONDR VSL2B, IUPred and ESpritz. We address here the problem of a systematic overestimation of the number of disordered proteins recognized through the use of these predictors, considered as a standard. Some of these predictors, used with their default setting, have a low precision, implying a tendency to overestimate the occurrence of disordered proteins in genome-wide surveys.

Predictors of natively unfolded proteins: unanimous consensus score to detect a twilight zone between order and disorder in generic datasets.

Background: Natively unfolded proteins lack a well defined three dimensional structure but have important biological functions, suggesting a re-assignment of the structure-function paradigm. To assess that a given protein is natively unfolded requires laborious experimental investigations, then reliable sequence-only methods for predicting whether a sequence corresponds to a folded or to an unfolded protein are of interest in fundamental and applicative studies. Many proteins have amino acidic compositions compatible both with the folded and unfolded status, and belong to a twilight zone between order and disorder.

Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: A comparative structural analysis by the ScrewFit algorithm.

The viral surface glycoprotein neuraminidase (NA) allows the influenza virus penetration and the egress of virions. NAs are classified as A, B, and C. Type-A NAs from influenza virus are subdivided into two phylogenetically distinct families, group-1 and group-2.

Dynamical phase transitions in long-range Hamiltonian systems and Tsallis distributions with a time-dependent index.

We study dynamical phase transitions in systems with long-range interactions, using the Hamiltonian mean field model as a simple example. These systems generically undergo a violent relaxation to a quasistationary state (QSS) before relaxing towards Boltzmann equilibrium. In the collisional regime, the out-of-equilibrium one-particle distribution function (DF) is a quasistationary solution of the Vlasov equation, slowly evolving in time due to finite- N effects.

Long-time behavior of quasistationary states of the Hamiltonian mean-field model.

The Hamiltonian mean-field model has been investigated, since its introduction about a decade ago, to study the equilibrium and dynamical properties of long-range interacting systems. Here we study the long-time behavior of long-lived, out-of-equilibrium, quasistationary dynamical states, whose lifetime diverges in the thermodynamic limit. The nature of these states has been the object of a lively debate in the recent past.

A fine functional homology between chitinases from host and parasite is relevant for malaria transmissibility.

High levels of plasma chitotriosidase are a marker of macrophage activation in several pathologies and, in particular, in human malaria. Plasmodium falciparum, during its maturative cycle in the midgut of the Anopheles mosquito, secretes a chitinase to disrupt the peritrophic membrane, a necessary step in the migration of the parasite from the midgut to the salivary glands of malaria's vector. The cooperation between human chitotriosidase (Chit) and the chitinase from P.

Asymptotic states and topological structure of an activation-deactivation chemical network.

The influence of the topology on the asymptotic states of a network of interacting chemical species has been studied by simulating its time evolution. Random and scale-free networks have been designed to support relevant features of activation-deactivation reactions networks (mapping signal transduction networks) and the system of ordinary differential equations associated to the dynamics has been numerically solved. We analysed stationary states of the dynamics as a function of the network's connectivity and of the distribution of the chemical species on the network; we found important differences between the two topologies in the regime of low connectivity.