Natural Evolution of Porcine Epidemic Diarrhea Viruses Isolated from Maternally Immunized Piglets

Simple SummaryDuring the long-term co-evolution of the virus and the host, even closely related vaccines may emerge with incomplete protective immunity due to the mutations or deletions of amino acids at specific antigenic sites. The mutation of PEDV was accelerated by the recombination of different strains and the mutation of the strains adapting to the environment. These mutations either cause immune escape from conventional vaccines or affect the virulence of the virus. Therefore, researching and developing new vaccines with cross-protection through continuous monitoring, isolation and sequencing are important to determine whether their genetic characteristics are changed and to evaluate the protective efficacy of current vaccines. The porcine epidemic diarrhea virus (PEDV) can cause severe piglet diarrhea or death in some herds. Genetic recombination and mutation facilitate the continuous evolution of the virus (PEDV), posing a great challenge for the prevention and control of porcine epidemic diarrhea (PED). Disease materials of piglets with PEDV vaccination failure in some areas of Shanxi, Henan and Hebei provinces of China were collected and examined to understand the prevalence and evolutionary characteristics of PEDV in these areas. Forty-seven suspicious disease materials from different litters on different farms were tested by multiplex PCR and screened by hematoxylin-eosin staining and immunohistochemistry. PEDV showed a positivity rate of 42.6%, infecting the small and large intestine and mesenteric lymph node tissues. The isolated strains infected Vero, PK-15 and Marc-145 multihost cells and exhibited low viral titers in all three cell types, as indicated by their growth kinetic curves. Possible putative recombination events in the isolates were identified by RDP4.0 software. Sequencing and phylogenetic analysis showed that compared with the classical vaccine strain, PEDV SX6 contains new insertion and mutations in the S region and belongs to genotype GIIa. Meanwhile, ORF3 has the complete amino acid sequence with aa80 mutated wild strains, compared to vaccine strains CV777, AJ1102, AJ1102-R and LW/L. These results will contribute to the development of new PEDV vaccines based on prevalent wild strains for the prevention and control of PED in China.

Bringing resilience together: On the co-evolutionary capacities of boundary organizations during the COVID-19 pandemic in Rotterdam.

For a city to maintain its vitality during a crisis like the COVID-19 pandemic, social resilience is pivotal. It is a manifestation of adaptive and transformative capacities in a city, through a multitude of interactions between initiatives and organizations, including local government. Resilience can take many forms: coping, adaptive, transformative; community-based, organizational, and institutional. Due to this hybridity and multiplicity, it remains to be seen how all forms of resilience interact and mutually benefit from one another in a city under crisis. Building further in the relational and dynamic dimensions of resilience, we conceptualize these mutual influences as co-evolution and hypothesise that for mutually beneficial co-evolution a city requires boundary organizations, i.e., organizations that facilitate collaboration and information-flow between differently organized societal domains. In our study of the activities of boundary organizations in the Dutch city Rotterdam during the COVID-19 pandemic, we found that boundary organizations were indeed supportive in building social and especially community resilience, but mainly coping and adaptive. Evidence for co-evolutions between various forms of resilience and institutional transformative resilience remained limited. Transformative potential seemed to get lost in procedural translations, was jeopardized by recentralization policies, and seemed only possible on the currents of already ongoing change.

Integrating the natural environment into tourism firms' business model for sustainability.

The link between the business model (BM) and sustainability is recognized in tourism research and practice, especially as far as its socioeconomic consequences are concerned. Moreover, prior studies have highlighted some key factors influencing the sustainable business models (SBMs) of tourism firms but have mainly done so by adopting static perspectives. Thus, how these firms can contribute to sustainability through their BMs with positive effects, particularly on natural resources, remains overlooked. Thus, we adopt coevolutionary lenses to explore the main processes surrounding tourism firms' SBM. Coevolution conceives the firm-environment relationship as both circular, with mutual influence and reciprocal changes, and dialectical. Accordingly, we analyze 28 Italian agritourism firms during the COVID-19 pandemic emergency period focusing on the dynamics of their relationship with various multilevel actors (including institutions, local communities, tourists) by considering internal and external factors influencing their SBM. The dialectical nature of this relationship is stressed. We find three new factors: sustainable tourism culture, tourist loyalty, and local natural resource setting. Moreover, from the coevolutionary analysis of the findings, we derive a framework that conceptualizes agritourism SBMs as a virtuous coevolutionary process through effective coadaptations between multilevel actors influenced by 12 factors. Tourism entrepreneurs and policy-makers should carefully consider the factors influencing SBMs and try to act upon them to effectively organize and manage relationships of mutual functionality in light of current challenges, especially environmental concerns.

Next Generation Sequencing Revolutionizes Organismal Biology Research in Bats.

The advent of next generation sequencing technologies (NGS) has greatly accelerated our understanding of critical aspects of organismal biology from non-model organisms. Bats form a particularly interesting group in this regard, as genomic data have helped unearth a vast spectrum of idiosyncrasies in bat genomes associated with bat biology, physiology, and evolution. Bats are important bioindicators and are keystone species to many eco-systems. They often live in proximity to humans and are frequently associated with emerging infectious diseases, including the COVID-19 pandemic. Nearly four dozen bat genomes have been published to date, ranging from drafts to chromosomal level assemblies. Genomic investigations in bats have also become critical towards our understanding of disease biology and host-pathogen coevolution. In addition to whole genome sequencing, low coverage genomic data like reduced representation libraries, resequencing data, etc. have contributed significantly towards our understanding of the evolution of natural populations, and their responses to climatic and anthropogenic perturbations. In this review, we discuss how genomic data have enhanced our understanding of physiological adaptations in bats (particularly related to ageing, immunity, diet, etc.), pathogen discovery, and host pathogen co-evolution. In comparison, the application of NGS towards population genomics, conservation, biodiversity assessment, and functional genomics has been appreciably slower. We reviewed the current areas of focus, identifying emerging topical research directions and providing a roadmap for future genomic studies in bats.

Misinformation Caused Increased Urban Mobility and the End of Social Confinement Before the Second Wave of COVID-19 in Amazonia.

Tendentious projections about COVID-19 in Brazil provided an appealing excuse for individuals and decision-makers to justify poor choices during a critical phase of the pandemic. The erroneous results likely contributed to premature resumption of in-person school classes and easing of restrictions on social contact, favoring the resurgence of COVID-19. In Manaus, the largest city in the Amazon region, the COVID-19 pandemic did not end in 2020 of its own accord, but rather rebounded in a disastrous second wave of the disease.

The coevolution of the spread of a disease and competing opinions in multiplex networks.

The COVID-19 pandemic has resulted in a proliferation of conflicting opinions on physical distancing across various media platforms, which has had a significant impact on human behavior and the transmission dynamics of the disease. Inspired by this social phenomenon, we present a novel UAP-SIS model to study the interaction between conflicting opinions and epidemic spreading in multiplex networks, in which individual behavior is based on diverse opinions. We distinguish susceptibility and infectivity among individuals who are unaware, pro-physical distancing and anti-physical distancing, and we incorporate three kinds of mechanisms for generating individual awareness. The coupled dynamics are analyzed in terms of a microscopic Markov chain approach that encompasses the aforementioned elements. With this model, we derive the epidemic threshold which is related to the diffusion of competing opinions and their coupling configuration. Our findings demonstrate that the transmission of the disease is shaped in a significant manner by conflicting opinions, due to the complex interaction between such opinions and the disease itself. Furthermore, the implementation of awareness-generating mechanisms can help to mitigate the overall prevalence of the epidemic, and global awareness and self-awareness can be interchangeable in certain instances. To effectively curb the spread of epidemics, policymakers should take steps to regulate social media and promote physical distancing as the mainstream opinion.

Exploring the Effect of Social Media and Spatial Characteristics During the COVID-19 Pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. © 2013 IEEE.

Revisiting the Faure report: Contemporary legacy and challenged legitimacy.

Since its publication in 1972, the Faure report has been regarded as a foundational text on the subject of lifelong learning, offering a plethora of ideas and repertoires. This article contemplates why and how the notions of self-fulfilment and self-learning are interrelated and profoundly important in understanding contemporary lifelong learning discourses, and how both have been appropriated by subsequent policy texts embedded in neoliberal thinking. The author argues that pursuing lifelong learning for self-fulfilment becomes voluntary self-exploitation as the individual's desire to learn unwittingly becomes driven by the instinct to survive and thrive in neoliberal socio-political environments. He also demonstrates that the ideas and repertoires provided in the Faure report function as a fertile ground for lifelong learning discourses, even though the abundant mix of ideas and propositions make it difficult to view the report as an ideologically coherent and conceptually tight-knit blueprint for the future of education. Nonetheless, the author argues that the legacy of the Faure report is still valid beyond its historical specificity. He points out that when read within the context of the unprecedented worldwide experience of COVID-19, the Faure report's proposition and reservations regarding mass media and cybernetics can shed light on the potential for contemporary technologies to strengthen emancipatory experiences of lifelong learning. Reflecting on this, he suggests that it is necessary to think collectively about how we can appreciate and harness technological innovation as an emancipatory tool to liberate ourselves from ignorance and prejudice through borderless and limitless connections to others, and to learn how to live with them.

Réétudier le rapport Faure : un héritage contemporain et une légitimité remise en question ­ Depuis sa publication en 1972, le rapport Faure fait figure de texte fondateur sur l'apprentissage tout au long de la vie au sujet duquel il offre pléthore d'idées et de répertoires. Le présent article examine non seulement pourquoi et comment les notions d'épanouissement personnel et d'autoapprentissage sont interdépendantes et profondément essentielles pour comprendre les discours sur l'apprentissage tout au long de la vie, mais aussi comment les textes politiques ultérieurs ancrés dans la pensée néolibérale se les sont appropriées. L'auteur affirme qu'apprendre tout au long de la vie dans une optique d'épanouissement personnel devient une autoexploitation volontaire étant donné que le souhait de la personne d'apprendre incidemment est mu par l'instinct de survie et de réussite dans des environnements sociopolitiques néolibéraux. Il démontre aussi que les idées et répertoires présentés dans le rapport Faure servent de terreau fertile aux discours sur l'apprentissage tout au long de la vie bien que la profusion d'idées et propositions rendent difficile de le considérer pour l'avenir de l'éducation comme un plan cohérent sur le plan idéologique et rigoureux du point de vue conceptuel. Néanmoins, l'auteur affirme que l'héritage du rapport Faure conserve sa validité au-delà de sa spécificité historique. Il indique que lu dans le contexte de la covid-19, une expérience sans précédent dans le monde entier, la proposition et les réserves du rapport Faure concernant les médias de masse et la cybernétique peuvent fournir un éclairage sur ce que les technologies contemporaines sont susceptibles d'apporter pour renforcer les expériences émancipatrices de l'apprentissage tout au long de la vie. En se penchant sur la question, il indique qu'il est nécessaire de réfléchir collectivement à la façon d'apprécier et d'exploiter les innovations technologiques en tant qu'outils émancipateurs pour nous affranchir de l'ignorance et des préjugés en créant des liens sans frontières et illimités avec les autres, et en apprenant comment vivre avec eux.

Interactomics: Dozens of Viruses, Co-evolving With Humans, Including the Influenza A Virus, may Actively Distort Human Aging.

Some viruses (e.g., human immunodeficiency virus 1 and severe acute respiratory syndrome coronavirus 2) have been experimentally proposed to accelerate features of human aging and of cellular senescence. These observations, along with evolutionary considerations on viral fitness, raised the more general puzzling hypothesis that, beyond documented sources in human genetics, aging in our species may also depend on virally encoded interactions distorting our aging to the benefits of diverse viruses. Accordingly, we designed systematic network-based analyses of the human and viral protein interactomes, which unraveled dozens of viruses encoding proteins experimentally demonstrated to interact with proteins from pathways associated with human aging, including cellular senescence. We further corroborated our predictions that specific viruses interfere with human aging using published experimental evidence and transcriptomic data; identifying influenza A virus (subtype H1N1) as a major candidate age distorter, notably through manipulation of cellular senescence. By providing original evidence that viruses may convergently contribute to the evolution of numerous age-associated pathways through co-evolution, our network-based and bipartite network-based methodologies support an ecosystemic study of aging, also searching for genetic causes of aging outside a focal aging species. Our findings, predicting age distorters and targets for anti-aging therapies among human viruses, could have fundamental and practical implications for evolutionary biology, aging study, virology, medicine, and demography.

Exploring the effect of social media and spatial characteristics during the COVID-19 pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. Author

Rapidly evolving viral motifs mostly target biophysically constrained binding pockets of host proteins.

Evolutionary changes in host-virus interactions can alter the course of infection, but the biophysical and regulatory constraints that shape interface evolution remain largely unexplored. Here, we focus on viral mimicry of host-like motifs that allow binding to host domains and modulation of cellular pathways. We observe that motifs from unrelated viruses preferentially target conserved, widely expressed, and highly connected host proteins, enriched with regulatory and essential functions. The interface residues within these host domains are more conserved and bind a larger number of cellular proteins than similar motif-binding domains that are not known to interact with viruses. In contrast, rapidly evolving viral-binding human proteins form few interactions with other cellular proteins and display high tissue specificity, and their interfaces have few inter-residue contacts. Our results distinguish between conserved and rapidly evolving host-virus interfaces and show how various factors limit host capacity to evolve, allowing for efficient viral subversion of host machineries.

Distinct evolutionary trajectories of SARS-CoV-2-interacting proteins in bats and primates identify important host determinants of COVID-19.

The coronavirus disease 19 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a coronavirus that spilled over from the bat reservoir. Despite numerous clinical trials and vaccines, the burden remains immense, and the host determinants of SARS-CoV-2 susceptibility and COVID-19 severity remain largely unknown. Signatures of positive selection detected by comparative functional genetic analyses in primate and bat genomes can uncover important and specific adaptations that occurred at virus-host interfaces. We performed high-throughput evolutionary analyses of 334 SARS-CoV-2-interacting proteins to identify SARS-CoV adaptive loci and uncover functional differences between modern humans, primates, and bats. Using DGINN (Detection of Genetic INNovation), we identified 38 bat and 81 primate proteins with marks of positive selection. Seventeen genes, including the ACE2 receptor, present adaptive marks in both mammalian orders, suggesting common virus-host interfaces and past epidemics of coronaviruses shaping their genomes. Yet, 84 genes presented distinct adaptations in bats and primates. Notably, residues involved in ubiquitination and phosphorylation of the inflammatory RIPK1 have rapidly evolved in bats but not primates, suggesting different inflammation regulation versus humans. Furthermore, we discovered residues with typical virus-host arms race marks in primates, such as in the entry factor TMPRSS2 or the autophagy adaptor FYCO1, pointing to host-specific in vivo interfaces that may be drug targets. Finally, we found that FYCO1 sites under adaptation in primates are those associated with severe COVID-19, supporting their importance in pathogenesis and replication. Overall, we identified adaptations involved in SARS-CoV-2 infection in bats and primates, enlightening modern genetic determinants of virus susceptibility and severity.

Strategies to prevent the new infectious diseases from an ecological perspective

Background: The coronavirus problem is an ecological problem stemming from a sud-den change in the relationship between parasites and hosts. Ecologists judge organisms that are established out of their original territory as exotic species. Unlike in their original habitat, these exotic species become very aggressive in their newly settled habitat. Coronavirus infection damage was bigger in Europe or the United States than that in the country of its origin, China, and its neighboring countries. Therefore, coronavirus infection damage resembles the damage due to the invasive species. Results: Exotic species are found in places with similar environmental conditions to those of their origin when introduced to other ecological regions. However, there are few ecological ill effects in their place of origin, while the damage is usually severe in the ecological regions in which it is introduced. According to historical records, exotic infectious diseases, such as European smallpox and measles, also showed a similar trend and caused great damage in newly established places. Therefore, it is expected that measures to manage exotic species could be used for the prevention of exotic infectious diseases such as the coronavirus. Conclusions: Prevention comes first in the management of exotic species, and in order to come up with preventive measures, it is important to collect information on the characteristics of related organisms and their preferred environment. In this respect, ecosystem management measures such as exotic species management measures could be used as a reference to prevent and suppress the spread. To put these measures into practice, it is urgently required to establish an international integrated information network for collect-ing and exchanging information between regions and countries. Furthermore, a system-atic ecosystem-management strategy in which natural and human environments could continue sustainable lives in their respective locations may serve as a countermeasure to prevent infectious diseases. © The Ecological Society of Korea in collaboration with The Korean Society of Limnology.

Co-evolution dynamics of epidemic and information under dynamical multi-source information and behavioral responses

In the absence of effective treatment programs and limited medical resources, multi-source information dynamically evolves with an epidemic and motivates people to adopt behavioral responses, which contributes much to reducing their infection risk and suppressing the epidemic spread. Here, we aim at studying the effects of dynamical multi-source information and behavioral responses on the co-evolution of epidemic and information in time-varying multiplex networks. We propose the UAU-SIS (unaware-aware-unaware susceptible-infected-susceptible) model with time-varying self-awareness and behavioral responses. Under the framework of time-varying multiplex networks and with a microscopic Markov chain approach, we analytically derive the epidemic thresholds for the proposed model. Experimental results for artificial networks show that time-varying behavioral responses can effectively suppress the epidemic spread with an increased epidemic threshold, while time-varying self-awareness can only reduce the scale of epidemic spread. In addition, the role of dynamical multi-source information in suppressing epidemic spread is limited. When the information transmission rate is beyond a certain critical value or the information efficiency is low, it will no longer affect the epidemic spread. Detailed analysis on the co-evolution of epidemic and information has to consider the heterogeneity of individuals in obtaining multi-source information and taking behavioral responses. Only when many people can obtain multi-source information and take behavioral responses, time-varying self-awareness and behavioral responses have a great impact on suppressing epidemic spread. Furthermore, we apply our proposed framework to two typical real-world networks and find that the results on real-world networks are consistent with those on artificial networks. Thus, the proposed method is expected to provide helpful guidance for coping with the COVID-19 or future emerging epidemics.

An integrated understanding of the evolutionary and structural features of the SARS-CoV-2 spike receptor binding domain (RBD).

Conventional drug development strategies typically use pocket in protein structures as drug-target sites. They overlook the plausible effects of protein evolvability and resistant mutations on protein structure which in turn may impair protein-drug interaction. In this study, we used an integrated evolution and structure guided strategy to develop potential evolutionary-escape resistant therapeutics using receptor binding domain (RBD) of SARS-CoV-2 spike-protein/S-protein as a model. Deploying an ensemble of sequence space exploratory tools including co-evolutionary analysis and deep mutational scans we provide a quantitative insight into the evolutionarily constrained subspace of the RBD sequence-space. Guided by molecular simulation and structure network analysis we highlight regions inside the RBD, which are critical for providing structural integrity and conformational flexibility. Using fuzzy C-means clustering we combined evolutionary and structural features of RBD and identified a critical region. Subsequently, we used computational drug screening using a library of 1615 small molecules and identified one lead molecule, which is expected to target the identified region, critical for evolvability and structural stability of RBD. This integrated evolution-structure guided strategy to develop evolutionary-escape resistant lead molecules have potential general applications beyond SARS-CoV-2.

COVID-19 and information coevolution in post-epidemic era

In this paper, a two-layer network on various immunization strategies in the post-epidemic era is constructed and an improved symbiotic evolutionary model of COVID-19 and information collaboration is proposed. The dynamic transformation probability is introduced to influence the virus information transmission coevolutionary process. The dynamic transformation probability is influenced by the immunization strategies and vertex characteristics. We quantify the effects of immunization strategy, node properties, global temperature, and collaborative information dissemination on new crown outbreaks. We simulated our model in a scale-free network to analyze the propagation. The evolutionary phenomenon of the network during propagation was investigated. We simulated the proven epidemic information coevolutionary model in a two-layer network, validated it with real data comparisons by proving that our proposed model fits the real situation. [ FROM AUTHOR] Copyright of Modern Physics Letters B is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Inclusive business. A biological metaphor model for the agricultural sector

The agricultural sector was one of the sectors that was most compromised during the confinements in the COVID-19 pandemic, guaranteeing the value chain and the necessary inputs. But even so, the problems of the sector are still evident: poverty, inequity, lack of rural and non-rural employment, low profit rates, lack of distribution chains and market development, among others. An alternative that is presented to achieve successful productive chains is that of inclusive businesses, for its better application and understanding, the application of a biological metaphor of coevolution and mutualism is presented in this document, noting that inclusive businesses should not occur. only on occasions of vulnerable producers, but to recognize in them their skills, knowledge, and capacities that they can share and put in favour of the integration model to achieve joint developments with the other organizations in the chain. The proposal focuses on strengthening inclusive models from the recognition of diversity and difference, and the development of management alternatives for the entire chain in general.

The co-evolution of knowledge management and business model transformation in the post-COVID-19 era: insights based on Chinese e-commerce companies

Purpose>This study aims to answer the question of how business models (BMs) maintain stability while coping with environmental uncertainties. This study proposes a dynamic co-evolution of knowledge management and business model transformation based on a comparative analysis of the focal firms’ BMs and their main partners in two e-commerce ecosystems in China.Design/methodology/approach>The open data of listed companies regarding the introduction of emerging topics on the transformation tendency of BMs in the post-COVID-19 business world is qualitatively analysed. The theoretical foundation is based on a critical review of the literature.Findings>Three aspects of the co-evolution between knowledge management and business model transformation are introduced. These three aspects are as follows: knowledge integration helps with multi-system business integration and decision-making collaborations;knowledge sharing helps to enhance cognitive ability and network value based on businesses;and the creation of new knowledge helps enrich the knowledge base and promote the transformation of BMs.Research limitations/implications>Solely attributing a firm’s ability to cope with environmental uncertainties to its business model weakens the importance of its knowledge management. This study argues that the co-evolution between knowledge management and business model transformation also plays a key role in a firm’s response to issues post-COVID-19.Originality/value>This study calls for the development of a normative theory of co-evolution between knowledge management and business model transformation, implying uncharted territories of knowledge management based on interaction with business model designs in e-business ecosystems.

Selection Analysis Identifies Clusters of Unusual Mutational Changes in Omicron Lineage BA.1 That Likely Impact Spike Function.

Among the 30 nonsynonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (1) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (2) interactions of Spike with ACE2 receptors, and (3) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any virus within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and, in combination with other mutations, adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron overall previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected.

Covid-19 management, treatment and vaccination strategies as the most efficient host manipulation by sars-cov-2: Reappraisal of a serious global public health crisis

We make a critical objective analysis of the different management, treatment and prevention strategies employed the world over to tackle the COVID-19 pandemic and try to bring some insight into the fact that they all may ultimately be efficient host manipulation by the SARS-CoV-2 virus for purposes of its unrestrained propagation. We discuss issues relating to long term implications of host-pathogen coevolution and viral pandemic periodicity.