Prediction and prevention of the next pandemic zoonosis.

Most pandemics--eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza--originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption

Molecular bases and role of viruses in the human microbiome.

Viruses are dependent biological entities that interact with the genetic material of most cells on the planet, including the trillions within the human microbiome. Their tremendous diversity renders analysis of human viral communities ("viromes") to be highly complex. Because many of the viruses in humans are bacteriophage, their dynamic interactions with their cellular hosts add greatly to the complexities observed in examining human microbial ecosystems. We are only beginning to be able to study human viral communities on a large scale, mostly as a result of recent and continued advancements in sequencing and bioinformatic technologies. Bacteriophage community diversity in humans not only is inexorably linked to the diversity of their cellular hosts but also is due to their rapid evolution, horizontal gene transfers, and intimate interactions with host nucleic acids. There are vast numbers of observed viral genotypes on many body surfaces studied, including the oral, gastrointestinal, and respiratory tracts, and even in the human bloodstream, which previously was considered a purely sterile environment. The presence of viruses in blood suggests that virome members can traverse mucosal barriers, as indeed these communities are substantially altered when mucosal defenses are weakened. Perhaps the most interesting aspect of human viral communities is the extent to which they can carry gene functions involved in the pathogenesis of their hosts, particularly antibiotic resistance. Persons in close contact with each other have been shown to share a fraction of oral virobiota, which could potentially have important implications for the spread of antibiotic resistance to healthy individuals. Because viruses can have a large impact on ecosystem dynamics through mechanisms such as the transfers of beneficial gene functions or the lysis of certain populations of cellular hosts, they may have both beneficial and detrimental roles that affect human health, including improvements in microbial resilience to disturbances, immune evasion, maintenance of physiologic processes, and altering the microbial community in ways that promote or prevent pathogen colonization

Mapping of the Coronavirus Circulating in Asia Based on Sequence of Gene Spike and Membrane Protein Used MEGA-X Aplication

Coronavirus are viruses that can be transmitted to human and animals. Severe acute respiratory syndrome, middle east respiratory syndrome, and Coronavirus disease 2019 are disease can be caused by several subtypes of coronavirus.  The aims of this study were to mapping of the coronavirus circulating in Asia based on sequence of gene spike and membrane protein virus. Totally of 67 coronavirus spike protein and membrane gene sequence were accessed via GenBank® (www.ncbi.nlm.nih.gov/genbank/) matched with the ClustalW Method MEGA-X. The result of the study are 20 groups of coronavirus were found based on spike protein gene sequences and 27 groups of coronavirus were found based on membrane protein gene sequences which were different with the first group of coronavirus found in Wuhan. Therefore, it can be concluded that the coronavirus circulate in several Asian countries had been mutate on gene spike and membrane protein. Keywords: Asia, Coronavirus, MEGA-X, Membrane Protein, Spike Protei

Phylogenetic Tests of Models of Viral Transmission

The hunt for the immediate non-human host of SARS-CoV-2 has centered on bats of the genus Rhinolophus. We explored the phylogenetic predictions of two models of viral transmission, the SpilloverModel and the CirculationModel and suggest that the Spillover Model can be eliminated. The Circulation Model suggests that viral transmission occurs among susceptible hosts irrespective of their phylogenetic relationships. Susceptibility could be mediated by the ACE2 gene (important for viral docking) and we constructed a phylogeny of this gene for 159 mammal species, finding a phylogenetic pattern consistent with established mammalian relationships. The tree indicates that viral transfer occurs over large evolutionary distances. Although lacking consensus, some studies identify a virus from a particular R. affinis individual (RaTG13) as being most closely related phylogenetically to human SARS-CoV-2. However, other R. affinis harbor viruses that are relatively unrelated to human viruses, and viruses found in this species exhibit sequence differences of up to 20%, suggesting multiple transfers over time. There is little correspondence between viral and host (bat) species limits or phylogenetic relationships. An ACE2 phylogeny for Rhinolophus followed species limits, unlike the pattern in the viral phylogeny indicating that phylogenetic similarity of ACE2 is not a predictor of viral transmission at the bat species level. The Circulation Model could be modified to apply to any individual of any species of Rhinolophus; more individuals and species must be examined

Genetic Relationship between SARS-CoV-2 and Other Coronaviruses

News coverage about the COVID-19 pandemic has often compared SARS-CoV-2, the virus that causes this disease, to other coronaviruses that have made the species jump to humans, such as SARS-CoV of the 2003 SARS outbreak, MERS-CoV of the 2012 MERS outbreak, and the coronaviruses that cause the flu and common cold. Though the comparison of SARS-CoV-2 to the common cold has been weaponized for political reasons, it is important for the study of SARS-CoV-2 and the coronavirus classification, the development of an effective arsenal against this virus and the global pandemic, and the effective implementation of public health measures. In order to tackle these broad areas of research, the genetic makeup of SARS-CoV-2 must be analyzed and compared to that of other human coronaviruses. Research about SARS-CoV-2 and COVID-19 has been conducted extremely rapidly, with the demand for new and groundbreaking information growing more and more each day as we aim to end the global pandemic. The research that has been conducted approaches the virus and the pandemic from many different angles and fields, such as epidemiology, medicine, economics, psychology, and much more; however, there is an enormous information gap in the medicine, biochemistry, and genetics of SARS-CoV-2 and COVID-19. In this research endeavor, I will determine how genetically related SARS-CoV-2, SARS-CoV, and other coronaviruses are, and how these variations effect observed differences in epidemiology, symptoms, and severity, among others

Virus Evolution: How Does an Enveloped Virus Make a Regular Structure?

The evolution of viruses has been an exciting area of study, albeit an area that is fraught with difficulties be- cause of the lack of a fossil record and because of the rapid sequence divergence exhibited by viruses. All viruses in collections available for study in the laboratory have been isolated within the last 70 years. Studies of the rate of sequence divergence in viruses over this period of time, all of which have focused on RNA viruses, have given estimates of 10^2 to 10^4 changes per nucleotide per year (Takeda et al., 1994; Weaver et al., 1997). Although these rates for the fixation of mutations of necessity assay changes in only the most variable positions in the viral genome, and there are clearly positions that change much more slowly, it is nonetheless clear that it is difficult to establish relationships between two viruses that last had a common ancestor, for example, a million years ago, based solely on sequence relation- ships. Furthermore, it has become increasingly clear in the last two decades that extensive recombination over the ages has complicated the evolutionary relationships among viruses belonging to different families (Strauss et al., 1996). To ascertain distant relationships among viruses, structural studies are of increasing importance, because the structure of a protein changes much less rapidly than does the amino acid sequence that forms the structure (Rossmann et al., 1974)

Molecular features similarities between SARS-CoV-2, SARS, MERS and key human genes could favour the viral infections and trigger collateral effects

In December 2019, rising pneumonia cases caused by a novel β-coronavirus (SARS-CoV-2) occurred in Wuhan, China, which has rapidly spread worldwide, causing thousands of deaths. The WHO declared the SARS-CoV-2 outbreak as a public health emergency of international concern, since then several scientists are dedicated to its study. It has been observed that many human viruses have codon usage biases that match highly expressed proteins in the tissues they infect and depend on the host cell machinery for the replication and co-evolution. In this work, we analysed 91 molecular features and codon usage patterns for 339 viral genes and 463 human genes that consisted of 677,873 codon positions. Hereby, we selected the highly expressed genes from human lung tissue to perform computational studies that permit to compare their molecular features with those of SARS, SARS-CoV-2 and MERS genes. The integrated analysis of all the features revealed that certain viral genes and overexpressed human genes have similar codon usage patterns. The main pattern was the A/T bias that together with other features could propitiate the viral infection, enhanced by a host dependant specialization of the translation machinery of only some of the overexpressed genes. The envelope protein E, the membrane glycoprotein M and ORF7 could be further benefited. This could be the key for a facilitated translation and viral replication conducting to different comorbidities depending on the genetic variability of population due to the host translation machinery. This is the first codon usage approach that reveals which human genes could be potentially deregulated due to the codon usage similarities between the host and the viral genes when the virus is already inside the human cells of the lung tissues. Our work leaded to the identification of additional highly expressed human genes which are not the usual suspects but might play a role in the viral infection and settle the basis for further research in the field of human genetics associated with new viral infections. To identify the genes that could be deregulated under a viral infection is important to predict the collateral effects and determine which individuals would be more susceptible based on their genetic features and comorbidities associated.Fil: Maldonado, Lucas Luciano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Mendoza Bertelli, Andrea Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Kamenetzky, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biociencias, Biotecnología y Biología Traslacional; Argentin

Multiscale statistical physics of the pan-viral interactome unravels the systemic nature of SARS-CoV-2 infections

AbstractProtein–protein interaction networks have been used to investigate the influence of SARS-CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of COVID–19 and providing ground for applications, such as drug repurposing. Characterizing molecular (dis)similarities between SARS-CoV-2 and other viral agents allows one to exploit existing information about the alteration of key biological processes due to known viruses for predicting the potential effects of this new virus. Here, we compare the novel coronavirus network against 92 known viruses, from the perspective of statistical physics and computational biology. We show that regulatory spreading patterns, physical features and enriched biological pathways in targeted proteins lead, overall, to meaningful clusters of viruses which, across scales, provide complementary perspectives to better characterize SARS-CoV-2 and its effects on humans. Our results indicate that the virus responsible for COVID–19 exhibits expected similarities, such as to Influenza A and Human Respiratory Syncytial viruses, and unexpected ones with different infection types and from distant viral families, like HIV1 and Human Herpes virus. Taken together, our findings indicate that COVID–19 is a systemic disease with potential effects on the function of multiple organs and human body sub-systems

Nouvel algorithme pour évaluer l'influence environnementale du Coronavirus par le biais d'une analyse phylogéographique

Abstract: This thesis presents a comprehensive exploration of phylogeographic methodologies designed to unravel intricate interplays between divergence patterns within coronaviruses and relevant environmental attributes. The study encompasses the integration of genetic and climatic factors to discern the complex relationships underlying viral evolution and distribution. The research commences with the development of a Python-based phylogeographic analysis pipeline, facilitating the investigation of the relationship between genetic diversity and geographic distribution. The pipeline employs a sliding window approach to identify regions within viral genetic sequences aligning with regional climatic conditions. This unified system orchestrates a range of analytical operations and is cross-platform compatible, catering to various operating systems. Building upon this foundation, an application is developed, enhancing the reproducibility and accessibility of the analysis. Neo4j and Snakemake technologies are leveraged to empower researchers in data preprocessing, parameters tuning, results saving, and data visualizing. Real-world data, including genomic sequences, lineage information, population statistics, and climate data, are curated and integrated into the Neo4j graph database. To broaden the scope to encompass various Coronaviruses, the study incorporates Host-Virus cophylogeny analysis, horizontal gene transfer analysis, and other strategies, thereby enriching the research landscape. Moreover, the study addresses scalability and efficiency concerns, crucial for accommodating expanding datasets, and evolving research requirements. The enhanced workflow facilitates parallel task execution, significantly boosting performance. The outcomes highlight key fragments correlating with specific environmental factors, reinforcing the platform's utility in deciphering complex evolutionary dynamics. As a result, this research makes a substantial contribution to the field of phylogeography, providing researchers with a powerful toolkit for investigating species distribution patterns and environmental influences. The insights derived from this study have the potential to reveal fundamental principles governing the interplay between genetic variation and geographical attributes across various species.Ce mémoire présente une étude exhaustive des méthodologies phylogéographiques appliquées à la compréhension des schémas de divergence au sein des coronavirus et de leur relation avec les facteurs environnementaux pertinents. L’analyse intègre de manière systématique les aspects génétiques et climatiques dans le but d’éclaircir les relations complexes qui sous-tendent l’évolution et la répartition de ces agents viraux. L’approche méthodologique entreprise débute par la conception et l’implémentation d’un pipeline d’analyse phylogéographique, conçu en langage Python. Ce pipeline constitue une plateforme d’investigation destinée à scruter la corrélation entre la diversité génétique des coronavirus et leur distribution géographique. L’utilisation d’une technique de fenêtre glissante dans ce pipeline permet d’identifier les régions spécifiques au sein des séquences génétiques virales qui présentent des associations significatives avec les conditions climatiques propres à chaque région. Cette solution intégrée englobe une variété d’opérations analytiques, offrant une interopérabilité adaptable à différentes plates-formes et systèmes d’exploitation. Sur la base de ces fondements, une application a été élaborée en vue d’optimiser la reproductibilité et l’accessibilité des analyses scientifiques. Cette avancée s’appuie sur l’utilisation des technologies de pointe telles que Neo4j et Snakemake, permettant ainsi aux chercheurs d’exploiter la préparation des données, l’ajustement des paramètres, la sauvegarde des résultats et la visualisation des données. L’intégration de données du monde réel, incluant des séquences génomiques, des informations sur les lignées, des statistiques de population et des données climatiques, s’est effectuée avec une grande rigueur, ces données ayant été soigneusement sélectionnées puis intégrées dans la base de données graphique Neo4j. Afin d’étendre la portée de cette étude et d’englober différents types de coronavirus, l’analyse inclut également des investigations avancées telles que l’étude de la cophylogénie entre hôtes et virus, l’analyse des transferts horizontaux de gènes, ainsi que d’autres stratégies analytiques, contribuant ainsi de manière significative à l’enrichissement du paysage de la recherche scientifique. De plus, l’étude aborde les préoccupations de scalabilité et d’efficacité, essentielles pour accueillir des ensembles de données en expansion et des besoins de recherche. Le flux de travail amélioré prend en charge l’exécution parallèle des tâches, amplifiant les performances. Les résultats mettent en évidence des fragments clés corrélant avec des facteurs environnementaux spécifiques, renforçant l’utilité de la plateforme pour décoder les dynamiques évolutives complexes. En conséquence, cette recherche contribue au domaine de la phylogéographie, offrant aux chercheurs une boîte à outils solide pour explorer les schémas de distribution des espèces et les influences environnementales. Les conclusions tirées de cette étude ont le potentiel de révéler les principes fondamentaux sous-jacents à l’interaction entre la variation génétique et les attributs géographiques à travers les espèces