Assessment of mycoviral diversity in Pakistani fungal isolates revealed infection by 11 novel viruses of a single strain of Fusarium mangiferae isolate SP1

An extensive screening survey was conducted on Pakistani filamentous fungal isolates for the identification of viral infections. A total of 396 fungal samples were screened, of which 36 isolates were found double-stranded (ds) RNA positive with an overall frequency of 9% when analysed by a classical dsRNA isolation method. One of 36 dsRNA-positive strains, strain SP1 of a plant pathogenic fungus Fusarium mangiferae, was subjected to virome analysis. Next-generation sequencing and subsequent completion of the entire genome sequencing by a classical Sanger sequencing method showed the SP1 strain to be co-infected by 11 distinct viruses, at least seven of which should be described as new taxa at the species level according to the ICTV (International Committee on Taxonomy of Viruses) species demarcation criteria. The newly identified F. mangiferae viruses (FmVs) include two partitivirids, one betapartitivirus (FmPV1) and one gammapartitivirus (FmPV2); six mitovirids, three unuamitovirus (FmMV2, FmMV4, FmMV6), one duamitovirus (FmMV5), and two unclassified mitovirids (FmMV1, FmMV3); and three botourmiavirids, two magoulivirus (FmBOV1, FmBOV3) and one scleroulivirus (FmBOV2). The number of coinfecting viruses is among the largest ones of fungal coinfections. Their molecular features are thoroughly described here. This represents the first large virus survey in the Indian sub-continent.

Structures and Functional Diversities of ASFV Proteins

African swine fever virus (ASFV), the causative pathogen of the recent ASF epidemic, is a highly contagious double-stranded DNA virus. Its genome is in the range of 170~193 kbp and encodes 68 structural proteins and over 100 non-structural proteins. Its high pathogenicity strains cause nearly 100% mortality in swine. Consisting of four layers of protein shells and an inner genome, its structure is obviously more complicated than many other viruses, and its multi-layered structures play different kinds of roles in ASFV replication and survival. Each layer possesses many proteins, but very few of the proteins have been investigated at a structural level. Here, we concluded all the ASFV proteins whose structures were unveiled, and explained their functions from the view of structures. Those structures include ASFV AP endonuclease, dUTPases (E165R), pS273R protease, core shell proteins p15 and p35, non-structural proteins pA151R, pNP868R (RNA guanylyltransferase), major capsid protein p72 (gene B646L), Bcl-2-like protein A179L, histone-like protein pA104R, sulfhydryl oxidase pB119L, polymerase X and ligase. These novel structural features, diverse functions, and complex molecular mechanisms promote ASFV to escape the host immune system easily and make this large virus difficult to control.

s-aligner: a greedy algorithm for non-greedy de novo genome assembly

Genome assembly is a fundamental tool for biological research. Particularly, in microbiology, where budgets per sample are often scarce, it can make the difference between an inconclusive result and a fully valid conclusion. Identifying new strains or estimating the relative abundance of quasi-species in a sample are some example tasks that can’t be properly accomplished without previously generating assemblies with little structure ambiguity and covering most of the genome. In this work, we present a new genome assembly tool based on a greedy strategy. We compare the results obtained applying this tool to the results obtained with previously existing software. We find that, when applied to viral studies, comparatively, the software we developed often gets far larger contigs and higher genome fraction coverage than previous software. We also find a significant advantage when applied to exceptionally large virus genomes.

Quarantine for COVID-19 its Laws and Limitations

The Coronavirus disease began back in December 2019 as pneumonia without a definitive causative organism in the city of Wuhan, in Hubei province of China. This is the second pandemic that China has given birth to, the former being in 2003. Since the beginning of this pandemic, the Centre for Disease Control and Prevention (CDC) announced that this is primarily a droplet infection. Studies have also shown that show that the large virus-laden droplets are the main focus of infection and the CDC advices to maintain at least a two-meter distance between people and personal hygiene. Although quarantine carries a paradoxical history, a virus whose predominant mode of spread being respiratory droplets can be contained by simply staying indoors. The strategy of quarantine has its own demerits. Unless carried out meticulously, it involves the mingling of individuals who might have been exposed which undoubtedly increases the risk of diseases transmission. This in itself, is an act of negligence by the medical fraternity unless provided with proper facilities. Restricting the movement of populations is also an essential part of a strategy which comes at the cost of paralyzing the economy. Hospitals and other institutional quarantine facilities open up all over the globe in attempts to curb the spread of the novel coronavirus. Nevertheless, quarantine a strategy is a controversy because such a strict yet systemic approach can cause political, economic and socio-ethical unrest within a nation.

COVID-19 Spread in India: Dynamics, Modeling, and Future Projections

COVID-19 is an extremely infectious disease with a relatively large virus incubation period in the affected people who may be asymptomatic. Therefore, to reduce the transmission of this pathogen, several countries have taken many intervention measures. In this paper, we show that the impact of these measures in India is different from several other countries. It is shown that an early lockdown in late March 2020 changed the initial exponential growth curve of COVID-19 to a linear one, but a surge in the number of cases from late April 2020 brought India back to a quadratic trajectory. A regional analysis shows the disparate impact of the intervention in different states. It is further shown that the number of reported infections correlates with the number of tests, and therefore regions with limited diagnostics resources may not have a realistic estimate of the virus spread. This insufficiency of diagnostic test data is also reflected in an increasing positivity rate for India nearly 2.5 months after the lockdown, inconsistent with the trends observed for other geographical regions. Nonetheless, future projections are made using different epidemiological models based on the available data, and a comparative study is presented. In the absence of a reliable estimate of the true number of infections, these projections will have a limited accuracy: with that limitation, the most optimistic prediction suggests a continuing virus transmission through September 2020.

WisdomNet: Prognosis of COVID-19 with Slender Prospect of False Negative Cases and Vaticinating the Probability of Maturation to ARDS using Posteroanterior Chest X-Rays

Coronavirus is a large virus family consisting of diverse viruses, some of which disseminate among mammals and others cause sickness among humans. COVID-19 is highly contagious and is rapidly spreading, rendering its early diagnosis of preeminent status. Researchers, medical specialists and organizations all over the globe have been working tirelessly to combat this virus and help in its containment. In this paper, a novel neural network called WisdomNet has been proposed, for the diagnosis of COVID-19 using chest X-rays. The WisdomNet uses the concept of ‘Wisdom of Crowds’ as its founding idea. It is a two-layered convolutional Neural Network (CNN), which takes chest x-ray images as input. Both layers of the proposed neural network consist of a number of neural networks each. The dataset used for this study consists of chest x-ray images of COVID-19 positive patients, compiled and shared by Dr. Cohen on GitHub, and the chest x-ray images of healthy lungs and lungs affected by viral and bacterial pneumonia were obtained from Kaggle. The network not only pinpoints the presence of COVID-19, but also gives the probability of the disease maturing into Acute Respiratory Distress Syndrome (ARDS). Thus, predicting the progression of the disease in the COVID-19 positive patients. The network also slender the occurrences of false negative cases by employing a high threshold value, thus aids in curbing the spread of the disease and gives an accuracy of 100% for successfully predicting COVID-19 among the chest x-rays of patients affected with COVID-19, bacterial and viral pneumonia.

Tracking infection dynamics at single-cell level reveals highly resolved expression programs of a large virus infecting algal blooms

Nucleocytoplasmic large DNA viruses have the largest genomes among all viruses and infect diverse eukaryotes across various ecosystems, but their expression regulation and infection strategies are not well understood. We profiled single-cell transcriptomes of the worldwide-distributed microalga Emiliania huxleyi and its specific coccolithovirus responsible for massive bloom demise. Heterogeneity in viral transcript levels detected among single cells was used to reconstruct the viral transcriptional trajectory and to map cells along a continuum of infection states. This enabled identification of novel viral genetic programs, which are composed of five kinetic classes with distinct promoter elements. The infection substantially changed the host transcriptome, causing rapid shutdown of protein-encoding nuclear transcripts at the onset of infection, while the plastid and mitochondrial transcriptomes persisted to mid- and late stages, respectively. Single-cell transcriptomics thereby opens the way for tracking host-pathogen infection dynamics at high resolution within microbial communities in the marine environment.

Mathematical Analysis of a Mathematical Model of Chemovirotherapy: Effect of Drug Infusion Method

A mathematical model for the treatment of cancer using chemovirotherapy is developed with the aim of determining the efficacy of three drug infusion methods: constant, single bolus, and periodic treatments. The model is in the form of ODEs and is further extended into DDEs to account for delays as a result of the infection of tumor cells by the virus and chemotherapeutic drug responses. Analysis of the model is carried out for each of the three drug infusion methods. Analytic solutions are determined where possible and stability analysis of both steady state solutions for the ODEs and DDEs is presented. The results indicate that constant and periodic drug infusion methods are more efficient compared to a single bolus injection. Numerical simulations show that with a large virus burst size, irrespective of the drug infusion method, chemovirotherapy is highly effective compared to either treatments. The simulations further show that both delays increase the period within which a tumor can be cleared from body tissue.

Base-By-Base Version 3: New Comparative Tools for Large Virus Genomes

Base-By-Base is a comprehensive tool for the creation and editing of multiple sequence alignments that is coded in Java and runs on multiple platforms. It can be used with gene and protein sequences as well as with large viral genomes, which themselves can contain gene annotations. This report describes new features added to Base-By-Base over the last 7 years. The two most significant additions are: (1) The recoding and inclusion of “consensus-degenerate hybrid oligonucleotide primers” (CODEHOP), a popular tool for the design of degenerate primers from a multiple sequence alignment of proteins; and (2) the ability to perform fuzzy searches within the columns of sequence data in multiple sequence alignments to determine the distribution of sequence variants among the sequences. The intuitive interface focuses on the presentation of results in easily understood visualizations and providing the ability to annotate the sequences in a multiple alignment with analytic and user data.