Modern vaccine strategies for emerging zoonotic viruses.

INTRODUCTION: The significant increase in the emergence of notable zoonotic viruses in the previous decades has become a serious concern to global public health. Ninety-nine percent of infectious diseases have originated from zoonotic viruses with immense potential for dissemination, infecting the susceptible population completely lacking herd immunity. AREAS COVERED: Zoonotic viruses appear in the last two decades as a major health threat either newly evolved or previously present with elevated prevalence in the last few years are selected to explain their current prophylactic measures. In this review, modern generation vaccines including viral vector vaccines, mRNA vaccines, DNA vaccines, synthetic vaccines, virus-like particles, and plant-based vaccines are discussed with their benefits and challenges. Moreover, the traditional vaccines and their efficacy are also compared with the latest vaccines. EXPERT OPINION: The emergence and reemergence of viruses that constantly mutate themselves have greatly increased the chance of transmission and immune escape mechanisms in humans. Therefore, the only possible solution to prevent viral infection is the use of vaccines with improved safety profile and efficacy, which becomes the basis of modern generation vaccines.

Major bat-borne zoonotic viral epidemics in Asia and Africa: A systematic review and meta-analysis.

Bats are the natural reservoir host for many pathogenic and non-pathogenic viruses, potentially spilling over to humans and domestic animals directly or via an intermediate host. The ongoing COVID-19 pandemic is the continuation of virus spillover events that have taken place over the last few decades, particularly in Asia and Africa. Therefore, these bat-associated epidemics provide a significant number of hints, including respiratory cellular tropism, more intense susceptibility to these cell types, and overall likely to become a pandemic for the next spillover. In this systematic review, we analysed data to insight, through bat-originated spillover in Asia and Africa. We used STATA/IC-13 software for descriptive statistics and meta-analysis. The random effect of meta-analysis showed that the pooled estimates of case fatality rates of bat-originated viral zoonotic diseases were higher in Africa (61.06%, 95%CI: 50.26 to 71.85, l2 % = 97.3, p < 0.001). Moreover, estimates of case fatality rates were higher in Ebola (61.06%; 95%CI: 50.26 to 71.85, l2 % = 97.3, p < 0.001) followed by Nipah (55.19%; 95%CI: 39.29 to 71.09, l2 % = 94.2, p < 0.001), MERS (18.49%; 95%CI: 8.19 to 28.76, l2 % = 95.4, p < 0.001) and SARS (10.86%; 95%CI: 6.02 to 15.71, l2 % = 85.7, p < 0.001) with the overall case fatality rates of 29.86 (95%CI: 29.97 to 48.58, l2 % = 99.0, p < 0.001). Bat-originated viruses have caused several outbreaks of deadly diseases, including Nipah, Ebola, SARS and MERS in Asia and Africa in a sequential fashion. Nipah virus emerged first in Malaysia, but later, periodic outbreaks were noticed in Bangladesh and India. Similarly, the Ebola virus was detected in the African continent with neurological disorders in humans, like Nipah, seen in the Asian region. Two important coronaviruses, MERS and SARS, were introduced, both with the potential to infect respiratory passages. This paper explores the dimension of spillover events within and/or between bat-human and the epidemiological risk factors, which may lead to another pandemic occurring. Further, these processes enhance the bat-originated virus, which utilises an intermediate host to jump into human species.

Unsupervised explainable AI for molecular evolutionary study of forty thousand SARS-CoV-2 genomes.

BACKGROUND: Unsupervised AI (artificial intelligence) can obtain novel knowledge from big data without particular models or prior knowledge and is highly desirable for unveiling hidden features in big data. SARS-CoV-2 poses a serious threat to public health and one important issue in characterizing this fast-evolving virus is to elucidate various aspects of their genome sequence changes. We previously established unsupervised AI, a BLSOM (batch-learning SOM), which can analyze five million genomic sequences simultaneously. The present study applied the BLSOM to the oligonucleotide compositions of forty thousand SARS-CoV-2 genomes. RESULTS: While only the oligonucleotide composition was given, the obtained clusters of genomes corresponded primarily to known main clades and internal divisions in the main clades. Since the BLSOM is explainable AI, it reveals which features of the oligonucleotide composition are responsible for clade clustering. Additionally, BLSOM also provided information concerning the special genomic region possibly undergoing RNA modifications. CONCLUSIONS: The BLSOM has powerful image display capabilities and enables efficient knowledge discovery about viral evolutionary processes, and it can complement phylogenetic methods based on sequence alignment.

The COVID-19 Pandemic, a Risk Management Approach

The coronavirus disease-2019 pandemic, one of many global threats to human health, provides an opportunity to analyze how to detect, minimize, and even prevent the spread of future viral zoonotic agents with pandemic potential. Such analysis can utilize existing risk assessment techniques that seek formally to define the hazard, assess the health risk, characterize the health threat, and estimate the probability of occurrence. © 2021 by Turkish Neurological Society.

Ranking the risk of animal-to-human spillover for newly discovered viruses.

The death toll and economic loss resulting from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are stark reminders that we are vulnerable to zoonotic viral threats. Strategies are needed to identify and characterize animal viruses that pose the greatest risk of spillover and spread in humans and inform public health interventions. Using expert opinion and scientific evidence, we identified host, viral, and environmental risk factors contributing to zoonotic virus spillover and spread in humans. We then developed a risk ranking framework and interactive web tool, SpillOver, that estimates a risk score for wildlife-origin viruses, creating a comparative risk assessment of viruses with uncharacterized zoonotic spillover potential alongside those already known to be zoonotic. Using data from testing 509,721 samples from 74,635 animals as part of a virus discovery project and public records of virus detections around the world, we ranked the spillover potential of 887 wildlife viruses. Validating the risk assessment, the top 12 were known zoonotic viruses, including SARS-CoV-2. Several newly detected wildlife viruses ranked higher than known zoonotic viruses. Using a scientifically informed process, we capitalized on the recent wealth of virus discovery data to systematically identify and prioritize targets for investigation. The publicly accessible SpillOver platform can be used by policy makers and health scientists to inform research and public health interventions for prevention and rapid control of disease outbreaks. SpillOver is a living, interactive database that can be refined over time to continue to improve the quality and public availability of information on viral threats to human health.

Human cell-dependent, directional, time-dependent changes in the mono- and oligonucleotide compositions of SARS-CoV-2 genomes.

BACKGROUND: When a virus that has grown in a nonhuman host starts an epidemic in the human population, human cells may not provide growth conditions ideal for the virus. Therefore, the invasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is usually prevalent in the bat population, into the human population is thought to have necessitated changes in the viral genome for efficient growth in the new environment. In the present study, to understand host-dependent changes in coronavirus genomes, we focused on the mono- and oligonucleotide compositions of SARS-CoV-2 genomes and investigated how these compositions changed time-dependently in the human cellular environment. We also compared the oligonucleotide compositions of SARS-CoV-2 and other coronaviruses prevalent in humans or bats to investigate the causes of changes in the host environment. RESULTS: Time-series analyses of changes in the nucleotide compositions of SARS-CoV-2 genomes revealed a group of mono- and oligonucleotides whose compositions changed in a common direction for all clades, even though viruses belonging to different clades should evolve independently. Interestingly, the compositions of these oligonucleotides changed towards those of coronaviruses that have been prevalent in humans for a long period and away from those of bat coronaviruses. CONCLUSIONS: Clade-independent, time-dependent changes are thought to have biological significance and should relate to viral adaptation to a new host environment, providing important clues for understanding viral host adaptation mechanisms.

Natural Products and Nutrients against Different Viral Diseases: Prospects in Prevention and Treatment of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a global pandemic and is posing a serious challenge to mankind. As per the current scenario, there is an urgent need for antiviral that could act as a protective and therapeutic against SARS-CoV-2. Previous studies have shown that SARS-CoV-2 is much similar to the SARS-CoV bat that occurred in 2002-03. Since it is a zoonotic virus, the exact source is still unknown, but it is believed bats may be the primary reservoir of SARS-CoV-2 through which it has been transferred to humans. In this review, we have tried to summarize some of the approaches that could be effective against SARS-CoV-2. Firstly, plants or plant-based products have been effective against different viral diseases, and secondly, plants or plant-based natural products have the minimum adverse effect. We have also highlighted a few vitamins and minerals that could be beneficial against SARS-CoV-2.

Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for candidates for advantageous mutations for growth in human cells.

We first conducted time-series analysis of mono- and dinucleotide composition for over 10,000 SARS-CoV-2 genomes, as well as over 1500 Zaire ebolavirus genomes, and found clear time-series changes in the compositions on a monthly basis, which should reflect viral adaptations for efficient growth in human cells. We next developed a sequence alignment free method that extensively searches for advantageous mutations and rank them in an increase level for their intrapopulation frequency. Time-series analysis of occurrences of oligonucleotides of diverse lengths for SARS-CoV-2 genomes revealed seven distinctive mutations that rapidly expanded their intrapopulation frequency and are thought to be candidates of advantageous mutations for the efficient growth in human cells.