Social evolution of innate immunity evasion in a virus

Fractal networks: Topology, dimension, and complexity

Over the past two decades, the study of self-similarity and fractality in discrete structures, particularly complex networks, has gained momentum. This surge of interest is fueled by the theoretical developments within the theory of complex networks and the practical demands of real-world applications. Nonetheless, translating the principles of fractal geometry from the domain of general topology, dealing with continuous or infinite objects, to finite structures in a mathematically rigorous way poses a formidable challenge. In this paper, we overview such a theory that allows to identify and analyze fractal networks through the innate methodologies of graph theory and combinatorics. It establishes the direct graph-theoretical analogs of topological (Lebesgue) and fractal (Hausdorff) dimensions in a way that naturally links them to combinatorial parameters that have been studied within the realm of graph theory for decades. This allows to demonstrate that the self-similarity in networks is defined by the patterns of intersection among densely connected network communities. Moreover, the theory bridges discrete and continuous definitions by demonstrating how the combinatorial characterization of Lebesgue dimension via graph representation by its subsets (subgraphs/communities) extends to general topological spaces. Using this framework, we rigorously define fractal networks and connect their properties with established combinatorial concepts, such as graph colorings and descriptive complexity. The theoretical framework surveyed here sets a foundation for applications to real-life networks and future studies of fractal characteristics of complex networks using combinatorial methods and algorithms.

Quasispecies productivity

The quasispecies theory is a helpful concept in the explanation of RNA virus evolution and behaviour, with a relevant impact on methods used to fight viral diseases. It has undergone some adaptations to integrate new empirical data, especially the non-deterministic nature of mutagenesis, and the variety of behavioural motifs in cooperation, competition, communication, innovation, integration, and exaptation. Also, the consortial structure of quasispecies with complementary roles of memory genomes of minority populations better fits the empirical data than did the original concept of a master sequence and its mutant spectra. The high productivity of quasispecies variants generates unique sequences that never existed before and will never exist again. In the present essay, we underline that such sequences represent really new ontological entities, not just error copies of previous ones. Their primary unique property, the incredible variant production, is suggested here as quasispecies productivity, which replaces the error-replication narrative to better fit into a new relationship between mankind and living nature in the twenty-first century.

Dynamic altruistic cooperation within breast tumors

BACKGROUND

Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance.

METHODS

MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells.

RESULTS

Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKβ. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit.

CONCLUSIONS

Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.

Open questions in the social lives of viruses

Social interactions among viruses occur whenever multiple viral genomes infect the same cells, hosts, or populations of hosts. Viral social interactions range from cooperation to conflict, occur throughout the viral world, and affect every stage of the viral lifecycle. The ubiquity of these social interactions means that they can determine the population dynamics, evolutionary trajectory, and clinical progression of viral infections. At the same time, social interactions in viruses raise new questions for evolutionary theory, providing opportunities to test and extend existing frameworks within social evolution. Many opportunities exist at this interface: Insights into the evolution of viral social interactions have immediate implications for our understanding of the fundamental biology and clinical manifestation of viral diseases. However, these opportunities are currently limited because evolutionary biologists only rarely study social evolution in viruses. Here, we bridge this gap by (1) summarizing the ways in which viruses can interact socially, including consequences for social evolution and evolvability; (2) outlining some open questions raised by viruses that could challenge concepts within social evolution theory; and (3) providing some illustrative examples, data sources, and conceptual questions, for studying the natural history of social viruses.

Cellular and Natural Viral Engineering in Cognition-Based Evolution

Neo-Darwinism conceptualizes evolution as the continuous succession of predominately random genetic variations disciplined by natural selection. In that frame, the primary interaction between cells and the virome is relegated to host-parasite dynamics governed by selective influences. Cognition-Based Evolution regards biological and evolutionary development as a reciprocating cognition-based informational interactome for the protection of self-referential cells. To sustain cellular homeorhesis, cognitive cells collaborate to assess the validity of ambiguous biological information. That collective interaction involves coordinate measurement, communication, and active deployment of resources as Natural Cellular Engineering. These coordinated activities drive multicellularity, biological development, and evolutionary change. The virome participates as the vital intercessory among the cellular domains to ensure their shared permanent perpetuation. The interactions between the virome and the cellular domains represent active virocellular cross-communications for the continual exchange of resources. Modular genetic transfers between viruses and cells carry bioactive potentials. Those exchanges are deployed as nonrandom flexible tools among the domains in their continuous confrontation with environmental stresses. This alternative framework fundamentally shifts our perspective on viral-cellular interactions, strengthening established principles of viral symbiogenesis. Pathogenesis can now be properly appraised as one expression of a range of outcomes between cells and viruses within a larger conceptual framework of Natural Viral Engineering as a co-engineering participant with cells. It is proposed that Natural Viral Engineering should be viewed as a co-existent facet of Natural Cellular Engineering within Cognition-Based Evolution.

A hybrid discrete-continuum model of immune responses to SARS-CoV-2 infection in the lung alveolar region, with a focus on interferon induced innate response

We develop a lattice-based, hybrid discrete-continuum modeling framework for SARS-CoV-2 exposure and infection in the human lung alveolar region, or parenchyma, the massive surface area for gas exchange. COVID-19 pneumonia is alveolar infection by the SARS-CoV-2 virus significant enough to compromise gas exchange. The modeling framework orchestrates the onset and progression of alveolar infection, spatially and temporally, beginning with a pre-immunity baseline, upon which we superimpose multiple mechanisms of immune protection conveyed by interferons and antibodies. The modeling framework is tunable to individual profiles, focusing here on degrees of innate immunity, and to the evolving infection-replication properties of SARS-CoV-2 variant strains. The model employs partial differential equations for virion, interferon, and antibody concentrations governed by diffusion in the thin fluid coating of alveolar cells, species and lattice interactions corresponding to sources and sinks for each species, and multiple immune protections signaled by interferons. The spatial domain is a two-dimensional, rectangular lattice of alveolar type I (non-infectable) and type II (infectable) cells with a stochastic, species-concentration-governed, switching dynamics of type II lattice sites from healthy to infected. Once infected, type II cells evolve through three phases: an eclipse phase during which RNA copies (virions) are assembled; a shedding phase during which virions and interferons are released; and then cell death. Model simulations yield the dynamic spread of, and immune protection against, alveolar infection and viral load from initial sites of exposure. We focus in this paper on model illustrations of the diversity of outcomes possible from alveolar infection, first absent of immune protection, and then with varying degrees of four known mechanisms of interferon-induced innate immune protection. We defer model illustrations of antibody protection to future studies. Results presented reinforce previous recognition that interferons produced solely by infected cells are insufficient to maintain a high efficacy level of immune protection, compelling additional mechanisms to clear alveolar infection, such as interferon production by immune cells and adaptive immunity (e.g., T cells). This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

The conditional defector strategies can violate the most crucial supporting mechanisms of cooperation

Cooperation is essential for all domains of life. Yet, ironically, it is intrinsically vulnerable to exploitation by cheats. Hence, an explanatory necessity spurs many evolutionary biologists to search for mechanisms that could support cooperation. In general, cooperation can emerge and be maintained when cooperators are sufficiently interacting with themselves. This communication provides a kind of assortment and reciprocity. The most crucial and common mechanisms to achieve that task are kin selection, spatial structure, and enforcement (punishment). Here, we used agent-based simulation models to investigate these pivotal mechanisms against conditional defector strategies. We concluded that the latter could easily violate the former and take over the population. This surprising outcome may urge us to rethink the evolution of cooperation, as it illustrates that maintaining cooperation may be more difficult than previously thought. Moreover, empirical applications may support these theoretical findings, such as invading the cooperator population of pathogens by genetically engineered conditional defectors, which could be a potential therapy for many incurable diseases.

Cooperative Virus-Virus Interactions: An Evolutionary Perspective

Despite extensive evidence of virus-virus interactions, not much is known about their biological significance. Importantly, virus-virus interactions could have evolved as a form of cooperation or simply be a by-product of other processes. Here, we review and discuss different types of virus-virus interactions from the point of view of social evolution, which provides a well-established framework for interpreting the fitness costs and benefits of such traits. We also classify interactions according to their mechanisms of action and speculate on their evolutionary implications. As in any other biological system, the evolutionary stability of viral cooperation critically requires cheaters to be excluded from cooperative interactions. We discuss how cheater viruses exploit cooperative traits and how viral populations are able to counteract this maladaptive process.

Pseudorabies Virus Tegument Protein UL13 Suppresses RLR-Mediated Antiviral Innate Immunity through Regulating Receptor Transcription

Pseudorabies virus (PRV) has evolved various strategies to escape host antiviral immune responses. However, it remains unclear whether and how PRV-encoded proteins modulate the RIG-I-like receptor (RLR)-mediated signals for immune evasion. Here, we show that the PRV tegument protein UL13 functions as an antagonist of RLR-mediated antiviral responses via suppression of the transcription of RIG-I and MDA5, but not LGP2. UL13 overexpression significantly inhibits both the mRNA and protein levels of RIG-I and MDA5, along with RIG-I- or MDA5-mediated antiviral immune responses, whereas overexpression of RIG-I or MDA5 counteracts such UL13-induced suppression. Mechanistically, UL13 suppresses the expression of RIG-I and MDA5 by inhibiting activation of the transcription factor NF-κB. Consequently, overexpression of p65 promotes the activation of RIG-I and MDA5 promoters. Moreover, deletion of the p65-binding sites in the promoters of RIG-I or MDA5 abolishes the suppression role of UL13. As a result, mutant PRV lacking UL13 elicits stronger host antiviral immune responses than PRV-WT. Hence, our results provide a novel functional role of UL13-induced suppression of host antiviral immunity through modulating receptors’ transcription.

Opposite Outcomes of the Within-Host Competition between High- and Low-Pathogenic H5N8 Avian Influenza Viruses in Chickens Compared to Ducks

Highly pathogenic avian influenza viruses (HPAIV) emerge from low-pathogenic avian influenza viruses (LPAIV) through the introduction of basic amino acids at the hemagglutinin (HA) cleavage site. Following viral evolution, the newly formed HPAIV likely represents a minority variant within the index host, predominantly infected with the LPAIV precursor. Using reverse genetics-engineered H5N8 viruses differing solely at the HA cleavage, we tested the hypothesis that the interaction between the minority HPAIV and the majority LPAIV could modulate the risk of HPAIV emergence and that the nature of the interaction could depend on the host species. In chickens, we observed that the H5N8LP increased H5N8HP replication and pathogenesis. In contrast, the H5N8LP antagonized H5N8HP replication and pathogenesis in ducks. Ducks mounted a more potent antiviral innate immune response than chickens against the H5N8LP, which correlated with H5N8HP inhibition. These data provide experimental evidence that HPAIV may be more likely to emerge in chickens than in ducks and underscore the importance of within-host viral variant interactions in viral evolution. IMPORTANCE Highly pathogenic avian influenza viruses represent a threat to poultry production systems and to human health because of their impact on food security and because of their zoonotic potential. It is therefore crucial to better understand how these viruses emerge. Using a within-host competition model between high- and low-pathogenic avian influenza viruses, we provide evidence that highly pathogenic avian influenza viruses could be more likely to emerge in chickens than in ducks. These results have important implications for highly pathogenic avian influenza virus emergence prevention, and they underscore the importance of within-host viral variant interactions in virus evolution.

The evolution of cheating in viruses

The success of many viruses depends upon cooperative interactions between viral genomes. However, whenever cooperation occurs, there is the potential for 'cheats' to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, the evolutionary theory of cheating could help us understand and manipulate viral dynamics, while viruses also offer new opportunities to study the evolution of cheating.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

The Social Life of Viruses

Despite their simplicity, viruses exhibit certain types of social interactions. Situations in which a given virus achieves higher fitness in combination with other members of the viral population have been described at the level of transmission, replication, suppression of host immune responses, and host killing, enabling the evolution of viral cooperation. Although cellular coinfection with multiple viral particles is the typical playground for these interactions, cooperation between viruses infecting different cells is also established through cellular and viral-encoded communication systems. In general, the stability of cooperation is compromised by cheater genotypes, as best exemplified by defective interfering particles. As predicted by social evolution theory, cheater invasion can be avoided when cooperators interact preferentially with other cooperators, a situation that is promoted in spatially structured populations. Processes such as transmission bottlenecks, organ compartmentalization, localized spread of infection foci, superinfection exclusion, and even discrete intracellular replication centers promote multilevel spatial structuring in viruses. Expected final online publication date for the Annual Review of Virology, Volume 8 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Experimental virus evolution in cancer cell monolayers, spheroids, and tissue explants

Viral laboratory evolution has been used for different applications, such as modeling viral emergence, drug-resistance prediction, and therapeutic virus optimization. However, these studies have been mainly performed in cell monolayers, a highly simplified environment, raising concerns about their applicability and relevance. To address this, we compared the evolution of a model virus in monolayers, spheroids, and tissue explants. We performed this analysis in the context of cancer virotherapy by performing serial transfers of an oncolytic vesicular stomatitis virus (VSV-Δ51) in 4T1 mouse mammary tumor cells. We found that VSV-Δ51 gained fitness in each of these three culture systems, and that adaptation to the more complex environments (spheroids or explants) correlated with increased fitness in monolayers. Most evolved lines improved their ability to suppress β-interferon secretion compared to the VSV-Δ51 founder, suggesting that the selective pressure exerted by antiviral innate immunity was important in the three systems. However, system-specific patterns were also found. First, viruses evolved in monolayers remained more oncoselective that those evolved in spheroids, since the latter showed concomitant adaptation to non-tumoral mouse cells. Second, deep sequencing indicated that viral populations evolved in monolayers or explants tended to be more genetically diverse than those evolved in spheroids. Finally, we found highly variable outcomes among independent evolutionary lines propagated in explants. We conclude that experimental evolution in monolayers tends to be more reproducible than in spheroids or explants, and better preserves oncoselectivity. Our results also suggest that monolayers capture at least some relevant selective pressures present in more complex systems.

Genetic diversity through social heterosis can increase virulence in RNA viral infections and cancer progression

In viral infections and cancer tumours, negative health outcomes often correlate with increasing genetic diversity. Possible evolutionary processes for such relationships include mutant lineages escaping host control or diversity, per se, creating too many immune system targets. Another possibility is social heterosis where mutations and replicative errors create clonal lineages varying in intrinsic capability for successful dispersal; improved environmental buffering; resource extraction or effective defence against immune systems. Rather than these capabilities existing in one genome, social heterosis proposes complementary synergies occur across lineages in close proximity. Diverse groups overcome host defences as interacting 'social genomes' with group genetic tool kits exceeding limited individual plasticity. To assess the possibility of social heterosis in viral infections and cancer progression, we conducted extensive literature searches for examples consistent with general and specific predictions from the social heterosis hypothesis. Numerous studies found supportive patterns in cancers across multiple tissues and in several families of RNA viruses. In viruses, social heterosis mechanisms probably result from long coevolutionary histories of competition between pathogen and host. Conversely, in cancers, social heterosis is a by-product of recent mutations. Investigating how social genomes arise and function in viral quasi-species swarms and cancer tumours may lead to new therapeutic approaches.

Cleavage of TANK-Binding Kinase 1 by HIV-1 Protease Triggers Viral Innate Immune Evasion

Type-I interferons (IFN-I) are the innate immune system’s principal defense against viral infections. Human immunodeficiency virus-1 (HIV-1) has evolved several ways to suppress or evade the host’s innate immunity in order to survive and replicate to sustain infection. Suppression of IFN-I is one among the multiple escape strategies used by HIV-1 to prevent its clearance. HIV-1 protease which helps in viral maturation has also been observed to cleave host cellular protein kinases. In this study we performed a comprehensive screening of a human kinase library using AlphaScreen assay and identified that TANK binding kinase-1 (TBK1) was cleaved by HIV-1 protease (PR). We demonstrate that PR cleaved TBK1 fails to phosphorylate IFN regulatory factor 3 (IRF3), thereby reducing the IFN-I promoter activity and further reveal that the PR mediated suppression of IFN-I could be counteracted by protease inhibitors (PI) in vitro. We have also revealed that mutations of HIV-1 PR that confer drug resistance to PIs reduce the enzyme’s ability to cleave TBK1. The findings of this study unearth a direct link between HIV-1 PR activity and evasion of innate immunity by the virus, the possible physiological relevance of which warrants to be determined.

Ten recent insights for our understanding of cooperation

Since Hamilton published his seminal papers in 1964, our understanding of the importance of cooperation for life on Earth has evolved beyond recognition. Early research was focused on altruism in the social insects, where the problem of cooperation was easy to see. In more recent years, research into cooperation has expanded across the entire tree of life, and has been revolutionized by advances in genetic, microbiological and analytical techniques. We highlight ten insights that have arisen from these advances, which have illuminated generalizations across different taxa, making the world simpler to explain. Furthermore, progress in these areas has opened up numerous new problems to solve, suggesting exciting directions for future research.

Common Dysregulation of Innate Immunity Pathways in Human Primary Astrocytes Infected With Chikungunya, Mayaro, Oropouche, and Zika Viruses

Arboviruses pose a major threat throughout the world and represent a great burden in tropical countries of South America. Although generally associated with moderate febrile illness, in more severe cases they can lead to neurological outcomes, such as encephalitis, Guillain-Barré syndrome, and Congenital Syndromes. In this context astrocytes play a central role in production of inflammatory cytokines, regulation of extracellular matrix, and control of glutamate driven neurotoxicity in the central nervous system. Here, we presented a comprehensive genome-wide transcriptome analysis of human primary astrocytes infected with Chikungunya, Mayaro, Oropouche, or Zika viruses. Analyses of differentially expressed genes (DEGs), pathway enrichment, and interactomes have shown that Alphaviruses up-regulated genes related to elastic fiber formation and N-glycosylation of glycoproteins, with down-regulation of cell cycle and DNA stability and chromosome maintenance genes. In contrast, Oropouche virus up-regulated cell cycle and DNA maintenance and condensation pathways while down-regulated extracellular matrix, collagen metabolism, glutamate and ion transporters pathways. Zika virus infection only up-regulated eukaryotic translation machinery while down-regulated interferon pathways. Reactome and integration analysis revealed a common signature in down-regulation of innate immune response, antiviral response, and inflammatory cytokines associated to interferon pathway for all arboviruses tested. Validation of interferon stimulated genes by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) corroborated our transcriptome findings. Altogether, our results showed a co-evolution in the mechanisms involved in the escape of arboviruses to antiviral immune response mediated by the interferon (IFN) pathway.

Autocrine and paracrine interferon signalling as 'ring vaccination' and 'contact tracing' strategies to suppress virus infection in a host

The innate immune response, particularly the interferon response, represents a first line of defence against viral infections. The interferon molecules produced from infected cells act through autocrine and paracrine signalling to turn host cells into an antiviral state. Although the molecular mechanisms of IFN signalling have been well characterized, how the interferon response collectively contribute to the regulation of host cells to stop or suppress viral infection during early infection remain unclear. Here, we use mathematical models to delineate the roles of the autocrine and the paracrine signalling, and show that their impacts on viral spread are dependent on how infection proceeds. In particular, we found that when infection is well-mixed, the paracrine signalling is not as effective; by contrast, when infection spreads in a spatial manner, a likely scenario during initial infection in tissue, the paracrine signalling can impede the spread of infection by decreasing the number of susceptible cells close to the site of infection. Furthermore, we argue that the interferon response can be seen as a parallel to population-level epidemic prevention strategies such as ‘contact tracing’ or ‘ring vaccination’. Thus, our results here may have implications for the outbreak control at the population scale more broadly.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections

Detection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. We studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected features measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. Distributions of the viral population features differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a machine learning classifier for the infection staging, which yielded a detection accuracy of 95.22 per cent, thus providing a higher accuracy than other genomic-based models. The detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, which could potentially complement and/or substitute standard laboratory assays.

OASL Triggered by Novel Goose Astrovirus via ORF2 Restricts Its Replication

Although astroviruses causes enteric diseases and encephalitis in humans and nephritis and hepatitis in poultry, astrovirus infection is thought to be self-limiting. However, little is known about its molecular mechanism. In this study, we found that a novel goose astrovirus (GAstV), GAstV-GD, and its open reading frame 2 (ORF2) could efficiently activate the innate immune response and induce a high level of OASL in vitro and in vivo The truncation assay for ORF2 further revealed that the P2 domain of ORF2 contributed to stimulating OASL, whereas the acidic C terminus of ORF2 attenuated such activation. Moreover, the overexpression and knockdown of OASL could efficiently restrict and promote the viral replication of GAstV-GD, respectively. Our data not only give novel insights for elucidating self-limiting infection by astrovirus but also provide virus and host targets for fighting against astroviruses.IMPORTANCE Astroviruses cause gastroenteritis and encephalitis in human, and nephritis, hepatitis, and gout disease in poultry. However, the host immune response activated by astrovirus is mostly unknown. Here, we found that a novel goose astrovirus, GAstV-GD, and its ORF2 protein could efficiently induce a high level of OASL in vitro and in vivo, which could feed back to restrict the replication of GAstV-GD, revealing novel innate molecules triggered by astroviruses and highlighting that the ORF2 of GAstV-GD and OASL can be potential antiviral targets for astroviruses.

Coronavirus hemagglutinin-esterase and spike proteins coevolve for functional balance and optimal virion avidity

Human coronaviruses OC43 and HKU1 are respiratory pathogens of zoonotic origin that have gained worldwide distribution. OC43 apparently emerged from a bovine coronavirus (BCoV) spillover. All three viruses attach to 9-O-acetylated sialoglycans via spike protein S with hemagglutinin-esterase (HE) acting as a receptor-destroying enzyme. In BCoV, an HE lectin domain promotes esterase activity toward clustered substrates. OC43 and HKU1, however, lost HE lectin function as an adaptation to humans. Replaying OC43 evolution, we knocked out BCoV HE lectin function and performed forced evolution-population dynamics analysis. Loss of HE receptor binding selected for second-site mutations in S, decreasing S binding affinity by orders of magnitude. Irreversible HE mutations led to cooperativity in virus swarms with low-affinity S minority variants sustaining propagation of high-affinity majority phenotypes. Salvageable HE mutations induced successive second-site substitutions in both S and HE. Apparently, S and HE are functionally interdependent and coevolve to optimize the balance between attachment and release. This mechanism of glycan-based receptor usage, entailing a concerted, fine-tuned activity of two envelope protein species, is unique among CoVs, but reminiscent of that of influenza A viruses. Apparently, general principles fundamental to virion-sialoglycan interactions prompted convergent evolution of two important groups of human and animal pathogens.

Graph fractal dimension and the structure of fractal networks

Fractals are geometric objects that are self-similar at different scales and whose geometric dimensions differ from so-called fractal dimensions. Fractals describe complex continuous structures in nature. Although indications of self-similarity and fractality of complex networks has been previously observed, it is challenging to adapt the machinery from the theory of fractality of continuous objects to discrete objects such as networks. In this article, we identify and study fractal networks using the innate methods of graph theory and combinatorics. We establish analogues of topological (Lebesgue) and fractal (Hausdorff) dimensions for graphs and demonstrate that they are naturally related to known graph-theoretical characteristics: rank dimension and product dimension. Our approach reveals how self-similarity and fractality of a network are defined by a pattern of overlaps between densely connected network communities. It allows us to identify fractal graphs, explore the relations between graph fractality, graph colourings and graph descriptive complexity, and analyse the fractality of several classes of graphs and network models, as well as of a number of real-life networks. We demonstrate the application of our framework in evolutionary biology and virology by analysing networks of viral strains sampled at different stages of evolution inside their hosts. Our methodology revealed gradual self-organization of intra-host viral populations over the course of infection and their adaptation to the host environment. The obtained results lay a foundation for studying fractal properties of complex networks using combinatorial methods and algorithms.

Single cell heterogeneity in influenza A virus gene expression shapes the innate antiviral response to infection

Viral infection outcomes are governed by the complex and dynamic interplay between the infecting virus population and the host response. It is increasingly clear that both viral and host cell populations are highly heterogeneous, but little is known about how this heterogeneity influences infection dynamics or viral pathogenicity. To dissect the interactions between influenza A virus (IAV) and host cell heterogeneity, we examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV virion. We observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at the single cell level. We show that human H1N1 and H3N2 strains differ significantly in patterns of both viral and host anti-viral gene transcriptional heterogeneity at the single cell level. Our analyses also reveal that semi-infectious particles that fail to express the viral NS can play a dominant role in triggering the innate anti-viral response to infection. Altogether, these data reveal how patterns of viral population heterogeneity can serve as a major determinant of antiviral gene activation.

A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract

Within the human respiratory tract (HRT), virus diffuses through the periciliary fluid (PCF) bathing the epithelium. But virus also undergoes advection: as the mucus layer sitting atop the PCF is pushed along by the ciliated cell's beating cilia, the PCF and its virus content are also pushed along, upwards towards the nose and mouth. While many mathematical models (MMs) have described the course of influenza A virus (IAV) infections in vivo, none have considered the impact of both diffusion and advection on the kinetics and localization of the infection. The MM herein represents the HRT as a one-dimensional track extending from the nose down towards the lower HRT, wherein stationary cells interact with IAV which moves within (diffusion) and along with (advection) the PCF. Diffusion was found to be negligible in the presence of advection which effectively sweeps away IAV, preventing infection from disseminating below the depth at which virus first deposits. Higher virus production rates (10-fold) are required at higher advection speeds (40 μm/s) to maintain equivalent infection severity and timing. Because virus is entrained upwards, upper parts of the HRT see more virus than lower parts. As such, infection peaks and resolves faster in the upper than in the lower HRT, making it appear as though infection progresses from the upper towards the lower HRT, as reported in mice. When the spatial MM is expanded to include cellular regeneration and an immune response, it reproduces tissue damage levels reported in patients. It also captures the kinetics of seasonal and avian IAV infections, via parameter changes consistent with reported differences between these strains, enabling comparison of their treatment with antivirals. This new MM offers a convenient and unique platform from which to study the localization and spread of respiratory viral infections within the HRT.

Social Bacteriophages

Despite their simplicity, viruses can display social-like interactions such as cooperation, communication, and cheating. Focusing on bacteriophages, here we review features including viral product sharing, cooperative evasion of antiviral defenses, prudent host exploitation, superinfection exclusion, and inter-phage peptide-mediated signaling. We argue that, in order to achieve a better understanding of these processes, their mechanisms of action need to be considered in the context of social evolution theory, paying special attention to key population-level factors such as genetic relatedness and spatial structure.

An M. tuberculosis Metabolic Enzyme Moonlights as an Anti-Inflammatory Effector Protein

The mechanisms by which Mycobacterium tuberculosis evades host immunity remain enigmatic. In a recent study in the journal Nature, Wang et al. report that an enzyme acting in the bacterial cytoplasm to degrade lipids also acts as an effector protein in the host cell cytoplasm to suppress inflammation.

The role of spatial structure in the evolution of viral innate immunity evasion: A diffusion-reaction cellular automaton model

Most viruses have evolved strategies for preventing interferon (IFN) secretion and evading innate immunity. Recent work has shown that viral shutdown of IFN secretion can be viewed as a social trait, since the ability of a given virus to evade IFN-mediated immunity depends on the phenotype of neighbor viruses. Following this idea, we investigate the role of spatial structure in the evolution of innate immunity evasion. For this, we model IFN signaling and viral spread using a spatially explicit approximation that combines a diffusion-reaction model and cellular automaton. Our results indicate that the benefits of preventing IFN secretion for a virus are strongly determined by spatial structure through paracrine IFN signaling. Therefore, innate immunity evasion can evolve as a cooperative or even altruistic trait based on indirect fitness effects that IFN shutdown exerts on other members of the viral population. We identify key factors determining whether evasion from IFN-mediated immunity should evolve, such as population bottlenecks occurring during viral transmission, the relative speed of cellular infection and IFN secretion, and the diffusion properties of the medium.

Virus population dynamics examined with experimental model systems

Experimental evolution permits exploring the effect of controlled environmental variables in virus evolution. Several designs in cell culture and in vivo have established basic concepts that can assist in the interpretation of evolutionary events in the field. Important information has come from cytolytic and persistent infections in cell culture that have unveiled the power of virus-cell coevolution in virus and cell diversification. Equally informative are comparisons of the response of viral populations when subjected to different passage régimens. In particular, plaque-to-plaque transfers in cell culture have revealed unusual genotypes and phenotypes that populate minority layers of viral quasispecies. Some of these viruses display properties that contradict features established in virology textbooks. Several hypotheses and principles of population genetics have found experimental confirmation in experimental designs with viruses. The possibilities of using experimental evolution to understand virus behavior are still largely unexploited.

Projective mechanisms subtending real world phenomena wipe away cause effect relationships

Causal relationships lie at the very core of scientific description of biophysical phenomena. Nevertheless, observable facts involving changes in system shape, dimension and symmetry may elude simple cause and effect inductive explanations. Here we argue that numerous physical and biological phenomena such as chaotic dynamics, symmetry breaking, long-range collisionless neural interactions, zero-valued energy singularities, and particle/wave duality can be accounted for in terms of purely topological mechanisms devoid of causality. We illustrate how simple topological claims, seemingly far away from scientific inquiry (e.g., "given at least some wind on Earth, there must at all times be a cyclone or anticyclone somewhere"; "if one stirs to dissolve a lump of sugar in a cup of coffee, it appears there is always a point without motion"; "at any moment, there is always a pair of antipodal points on the Earth's surface with equal temperatures and barometric pressures") reflect the action of non-causal topological rules. To do so, we introduce some fundamental topological tools and illustrate how phenomena such as double slit experiments, cellular mechanisms and some aspects of brain function can be explained in terms of geometric projections and mappings, rather than local physical effects. We conclude that unavoidable, passive, spontaneous topological modifications may lead to novel functional biophysical features, independent of exerted physical forces, thermodynamic constraints, temporal correlations and probabilistic a priori knowledge of previous cases.

Astrovirus replication in human intestinal enteroids reveals multi-cellular tropism and an intricate host innate immune landscape

Human astroviruses (HAstV) are understudied positive-strand RNA viruses that cause gastroenteritis mostly in children and the elderly. Three clades of astroviruses, classic, MLB-type and VA-type have been reported in humans. One limitation towards a better understanding of these viruses has been the lack of a physiologically relevant cell culture model that supports growth of all clades of HAstV. Herein, we demonstrate infection of HAstV strains belonging to all three clades in epithelium-only human intestinal enteroids (HIE) isolated from biopsy-derived intestinal crypts. A detailed investigation of infection of VA1, a member of the non-canonical HAstV-VA/HMO clade, showed robust replication in HIE derived from different patients and from different intestinal regions independent of the cellular differentiation status. Flow cytometry and immunofluorescence analysis revealed that VA1 infects several cell types, including intestinal progenitor cells and mature enterocytes, in HIE cultures. RNA profiling of VA1-infected HIE uncovered that the host response to infection is dominated by interferon (IFN)-mediated innate immune responses. A comparison of the antiviral host response in non-transformed HIE and transformed human colon carcinoma Caco-2 cells highlighted significant differences between these cells, including an increased magnitude of the response in HIE. Additional studies confirmed the sensitivity of VA1 to exogenous IFNs, and indicated that the endogenous IFN response of HIE to curtail the growth of strains from all three clades. Genotypic variation in the permissiveness of different HIE lines to HAstV could be overcome by pharmacologic inhibition of JAK/STAT signaling. Collectively, our data identify HIE as a universal infection model for HAstV and an improved model of the intestinal epithelium to investigate enteric virus-host interactions.

Human astroviruses (HAstV) are understudied positive-strand RNA viruses that typically cause gastroenteritis mostly in children and the elderly, but more recent studies also implicate them in neurological disease in immunocompromised patients. To better understand these viruses, a physiologically relevant cell culture model that supports growth of all clades of HAstV would be highly beneficial. Herein, we demonstrated robust infection of HAstV strains belonging to all three clades in epithelium-only human intestinal enteroids (HIE) isolated from biopsy-derived intestinal crypts from different patients and intestinal regions, making HIE a valuable model to study HAstV biology. Using this system, we identify for the first time that VA1 infects several cell types, including intestinal progenitor cells and mature enterocytes. Analysis of the antiviral host response to infection demonstrated that HIE respond to infection with a type I and III interferon response. This response reduced HAstV replication and when blocked resulted in increased infection. Establishment of the HIE system for HAstV research lays the foundation for future basic and translational discoveries.

Principles of Effective and Robust Innate Immune Response to Viral Infections: A Multiplex Network Analysis

The human innate immune response, particularly the type-I interferon (IFN) response, is highly robust and effective first line of defense against virus invasion. IFN molecules are produced and secreted from infected cells upon virus infection and recognition. They then act as signaling/communication molecules to activate an antiviral response in neighboring cells so that those cells become refractory to infection. Previous experimental studies have identified the detailed molecular mechanisms for the IFN signaling and response. However, the principles underlying how host cells use IFN to communicate with each other to collectively and robustly halt an infection is not understood. Here we take a multiplex network modeling approach to provide a theoretical framework to identify key factors that determine the effectiveness of the IFN response against virus infection of a host. In this approach, we consider the virus spread among host cells and the interferon signaling to protect host cells as a competition process on a two-layer multiplex network. We focused on two types of network topology, i.e., the Erdős-Rényi (ER) network and the Geometric Random (GR) network, which represent the scenarios when infection of cells is mostly well mixed (e.g., in the blood) and when infection is spatially segregated (e.g., in tissues), respectively. We show that in general, the IFN response works effectively to stop viral infection when virus infection spreads spatially (a most likely scenario for initial virus infection of a host at the peripheral tissue). Importantly, we show that the effectiveness of the IFN response is robust against large variations in the distance of IFN diffusion as long as IFNs diffuse faster than viruses and they can effectively induce antiviral responses in susceptible host cells. This suggests that the effectiveness of the IFN response is insensitive to the specific arrangement of host cells in peripheral tissues. Thus, our work provides a quantitative explanation of why the IFN response can serve an effective and robust response in different tissue types to a wide range of viral infections of a host.