Narratives of crisis: From affective structures to adaptive functions.

This commentary focuses on affective structures and the main adaptive functions of shared narratives to fill the gaps of the Conviction Narrative Theory. The transmission of narratives among individuals in highly uncertain situations is irrevocably tainted by affects and anchored in collective memory. Narratives have important evolutionary functions for human beings under threat and act as the social glue that creates and strengthens social bonds among individuals.

Human Genes Involved in the Interaction between Host and Gut Microbiome: Regulation and Pathogenic Mechanisms.

INTRODUCTION: The umbrella term "human gut microbiota" describes the complex ecosystem harboring our gut. It includes bacteria, viruses, protozoa, archaea, fungi, and yeasts. This taxonomic classification does not describe its functions, which encompass nutrients digestion and absorption, immune system regulation, and host metabolism. "Gut microbiome" indicates instead the genome belonging to these "microbes" actively involved in these functions. However, the interaction between the host genome and the microbial ones determines the fine functioning of our organism. METHODS: We reviewed the data available in the scientific literature on the definition of gut microbiota, gut microbiome, and the data on human genes involved in the interaction with the latter. We consulted the main medical databases using the following keywords, acronyms, and their associations: gut microbiota, gut microbiome, human genes, immune function, and metabolism. RESULTS: Candidate human genes encoding enzymes, inflammatory cytokines, and proteins show similarity with those included in the gut microbiome. These findings have become available through newer artificial intelligence (AI) algorithms allowing big data analysis. From an evolutionary point of view, these pieces of evidence explain the strict and sophisticated interaction at the basis of human metabolism and immunity regulation in humans. They unravel more and more physiopathologic pathways included in human health and disease. DISCUSSION: Several lines of evidence also obtained through big data analysis support the bi-directional role of gut microbiome and human genome in host metabolism and immune system regulation.

Genome-based survey of the SARS-CoV-2 BF.7 variant from Asia.

The SARS-CoV-2 BF.7 variant represents one of the most recent subvariant under monitoring. At the beginning of the 2023 it caused several concerns especially in Asia because of a resurge in COVID-19 cases. Here we perform a genome-based integrative approach on SARS-CoV-2 BF.7 to shed light on this emerging lineage and produce some consideration on its real dangerousness. Both genetic and structural data suggest that this new variant currently does not show evidence of an high expansion capability. It is very common in Asia, but it appears less virulent than other Omicron variants as proved by its relatively low evolutionary rate (5.62 × 10-4 subs/sites/years). The last plateau has been reached around December 14, 2022 and then the genetic variability, and thus the viral population size, no longer increased. As already seen for several previous variants, the features that may be theoretically related to advantages are due to genetic drift that allows to the virus a constant adaptability to the host, but is not strictly connected to a fitness advantage. These results have further pointed that the genome-based monitoring must continue uninterruptedly to be prepared and well documented on the real situation.

New findings on the evolution of turtles: A symposium in honor of Marcelo S. de la Fuente.

With their particular body plan within amniotes and their amazing fossil record, turtles represent a great interest for both neontologists and paleontologists with a strong anatomical background. The Turtle Evolution Symposia are regular international meetings that gather scientists working with different aspects related to the evolutionary history of turtles, from their origin and early evolution until recent times. The latest edition of the Turtle Evolution Symposium was organized in 2021 amidst the COVID-19 outbreak and held virtually from the facilities of the Museo Paleontológico Egidio Feruglio in Trelew (Patagonia, Chubut, Argentina). More than 75 scientists from 25 countries presented their latest advances on topics related to turtle evolution, some of which are published in this Special Volume of The Anatomical Record. Both the Turtle Evolution Symposium 2021 and this Special Volume are dedicated to Marcelo S. de la Fuente who was the first researcher who specialized in the study of extinct turtles in South America, and his studies have an important regional and international impact.

Timeline of changes in spike conformational dynamics in emergent SARS-CoV-2 variants reveal progressive stabilization of trimer stalk with altered NTD dynamics.

SARS-CoV-2 emergent variants are characterized by increased viral fitness and each shows multiple mutations predominantly localized to the spike (S) protein. Here, amide hydrogen/deuterium exchange mass spectrometry has been applied to track changes in S dynamics from multiple SARS-CoV-2 variants. Our results highlight large differences across variants at two loci with impacts on S dynamics and stability. A significant enhancement in stabilization first occurred with the emergence of D614G S followed by smaller, progressive stabilization in subsequent variants. Stabilization preceded altered dynamics in the N-terminal domain, wherein Omicron BA.1 S showed the largest magnitude increases relative to other preceding variants. Changes in stabilization and dynamics resulting from S mutations detail the evolutionary trajectory of S in emerging variants. These carry major implications for SARS-CoV-2 viral fitness and offer new insights into variant-specific therapeutic development.

SARS-CoV-2 Molecular Evolutionary Dynamics in the Greater Accra Region, Ghana.

To assess dynamics of SARS-CoV-2 in Greater Accra Region, Ghana, we analyzed SARS-CoV-2 genomic sequences from persons in the community and returning from international travel. The Accra Metropolitan District was a major origin of virus spread to other districts and should be a primary focus for interventions against future infectious disease outbreaks.

Disease-causing human viruses: novelty and legacy.

About 270 viruses are known to infect humans. Some of these viruses have been known for centuries, whereas others have recently emerged. During their evolutionary history, humans have moved out of Africa to populate the world. In historical times, human migrations resulted in the displacement of large numbers of people. All these events determined the movement and dispersal of human-infecting viruses. Technological advances have resulted in the characterization of the genetic variability of human viruses, both in extant and in archaeological samples. Field studies investigated the diversity of viruses hosted by other animals. In turn, these advances provided insight into the evolutionary history of human viruses back in time and defined the key events through which they originated and spread.

SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations.

Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a 'wet bench' machine learning tool for predicting likely future mutations based on previous mutations.

Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia.

Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity.

Evolutionary plasticity of zoonotic porcine Deltacoronavirus (PDCoV): genetic characteristics and geographic distribution.

The emergence and rapid spread of the acute respiratory syndrome coronavirus-2 have confirmed that animal coronaviruses represent a potential zoonotic source. Porcine deltacoronavirus is a worldwide evolving enteropathogen of swine, detected first in Hong Kong, China, before its global identification. Following the recent detection of PDCoV in humans, we attempted in this report to re-examine the status of PDCoV phylogenetic classification and evolutionary characteristics. A dataset of 166 complete PDCoV genomes was analyzed using the Maximum Likelihood method in IQ-TREE with the best-fitting model GTR + F + I + G4, revealing two major genogroups (GI and GII), with further seven and two sub-genogroups, (GI a-g) and (GII a-b), respectively. PDCoV strains collected in China exhibited the broadest genetic diversity, distributed in all subgenotypes. Thirty-one potential natural recombination events were identified, 19 of which occurred between China strains, and seven involved at least one China strain as a parental sequence. Importantly, we identified a human Haiti PDCoV strain as recombinant, alarming a possible future spillover that could become a critical threat to human health. The similarity and recombination analysis showed that PDCoV spike ORF is highly variable compared to ORFs encoding other structural proteins. Prediction of linear B cell epitopes of the spike glycoprotein and the 3D structural mapping of amino acid variations of two representative strains of GI and GII showed that the receptor-binding domain (RBD) of spike glycoprotein underwent a significant antigenic drift, suggesting its contribution in the genetic diversity and the wider spread of PDCoV.

L-shaped distribution of the relative substitution rate (c/µ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate.

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Genetic and Structural Data on the SARS-CoV-2 Omicron BQ.1 Variant Reveal Its Low Potential for Epidemiological Expansion.

The BQ.1 SARS-CoV-2 variant, also known as Cerberus, is one of the most recent Omicron descendant lineages. Compared to its direct progenitor BA.5, BQ.1 has some additional spike mutations in some key antigenic sites, which confer further immune escape ability over other circulating lineages. In such a context, here, we perform a genome-based survey aimed at obtaining a complete-as-possible nuance of this rapidly evolving Omicron subvariant. Genetic data suggest that BQ.1 represents an evolutionary blind background, lacking the rapid diversification that is typical of a dangerous lineage. Indeed, the evolutionary rate of BQ.1 is very similar to that of BA.5 (7.6 × 10-4 and 7 × 10-4 subs/site/year, respectively), which has been circulating for several months. The Bayesian Skyline Plot reconstruction indicates a low level of genetic variability, suggesting that the peak was reached around 3 September 2022. Concerning the affinity for ACE2, structure analyses (also performed by comparing the properties of BQ.1 and BA.5 RBD) indicate that the impact of the BQ.1 mutations may be modest. Likewise, immunoinformatic analyses showed moderate differences between the BQ.1 and BA5 potential B-cell epitopes. In conclusion, genetic and structural analyses on SARS-CoV-2 BQ.1 suggest no evidence of a particularly dangerous or high expansion capability. Genome-based monitoring must continue uninterrupted for a better understanding of its descendants and all other lineages.

Promoting validation and cross-phylogenetic integration in model organism research.

Model organism (MO) research provides a basic understanding of biology and disease due to the evolutionary conservation of the molecular and cellular language of life. MOs have been used to identify and understand the function of orthologous genes, proteins, cells and tissues involved in biological processes, to develop and evaluate techniques and methods, and to perform whole-organism-based chemical screens to test drug efficacy and toxicity. However, a growing richness of datasets and the rising power of computation raise an important question: How do we maximize the value of MOs? In-depth discussions in over 50 virtual presentations organized by the National Institutes of Health across more than 10 weeks yielded important suggestions for improving the rigor, validation, reproducibility and translatability of MO research. The effort clarified challenges and opportunities for developing and integrating tools and resources. Maintenance of critical existing infrastructure and the implementation of suggested improvements will play important roles in maintaining productivity and facilitating the validation of animal models of human biology and disease.

Ecological and evolutionary dynamics of multi-strain RNA viruses.

Potential interactions among co-circulating viral strains in host populations are often overlooked in the study of virus transmission. However, these interactions probably shape transmission dynamics by influencing host immune responses or altering the relative fitness among co-circulating strains. In this Review, we describe multi-strain dynamics from ecological and evolutionary perspectives, outline scales in which multi-strain dynamics occur and summarize important immunological, phylogenetic and mathematical modelling approaches used to quantify interactions among strains. We also discuss how host-pathogen interactions influence the co-circulation of pathogens. Finally, we highlight outstanding questions and knowledge gaps in the current theory and study of ecological and evolutionary dynamics of multi-strain viruses.

What is life? Active particles tools towards behavioral dynamics in social-biology and economics.

This review paper is devoted to study the conceptual difficulties that mathematics meets when attempting to describe the complexity of living matter focusing on the challenging perspective of developing a mathematical theory for living systems including mutations and selection. The quest starts with the identification of a number of common complexity features of living systems. Then, mathematical structures are derived to include these features, while mathematical models are derived by inserting in the structures models of individual based interactions. Three applications are examined by active particles methods, i.e., models of SARS2-CoV-2 pandemics, models of idiosyncratic learning in open markets and of the dynamics of prices accounting for human behaviors. A critical study, which pervades the whole paper, shows that also economics can be viewed as a behavioral science thus accounting for specific aspects typical of living systems.

Predation shifts coevolution toward higher host contact rate and parasite virulence.

Hosts can avoid parasites (and pathogens) by reducing social contact, but such isolation may carry costs, e.g. increased vulnerability to predators. Thus, many predator-host-parasite systems confront hosts with a trade-off between predation and parasitism. Parasites, meanwhile, evolve higher virulence in response to increased host sociality and consequently, increased multiple infections. How does predation shift coevolution of host behaviour and parasite virulence? What if predators are selective, i.e. predators disproportionately capture the sickest hosts? We answer these questions with an eco-coevolutionary model parametrized for a Trinidadian guppy-Gyrodactylus spp. system. Here, increased predation drives host coevolution of higher grouping, which selects for higher virulence. Additionally, higher predator selectivity drives the contact rate higher and virulence lower. Finally, we show how predation and selectivity can have very different impacts on host density and prevalence depending on whether hosts or parasites evolve, or both. For example, higher predator selectivity led to lower prevalence with no evolution or only parasite evolution but higher prevalence with host evolution or coevolution. These findings inform our understanding of diverse systems in which host behavioural responses to predation may lead to increased prevalence and virulence of parasites.

Genomic epidemiological models describe pathogen evolution across fitness valleys.

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high-transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

Women amid the COVID-19 pandemic: Self-protection through the behavioral immune system.

Studies of the activation of the behavioral immune system triggered by the coronavirus disease-2019 pandemic have demonstrated that evolutionary explanations of individual differences in self-protection should not be based only on parental investment and sexual selection theory. An evolutionary model must also incorporate individual differences that arise within each sex as a result of life history strategies and attachment patterns.