HIV-1 hypermethylated guanosine cap licenses specialized translation unaffected by mTOR

Appended to the 5′ end of nascent RNA polymerase II transcripts is 7-methyl guanosine (m7G-cap) that engages nuclear cap-binding complex (CBC) to facilitate messenger RNA (mRNA) maturation. Mature mRNAs exchange CBC for eIF4E, the rate-limiting translation factor that is controlled through mTOR. Experiments in immune cells have now documented HIV-1 incompletely processed transcripts exhibited hypermethylated m7G-cap and that the down-regulation of the trimethylguanosine synthetase-1–reduced HIV-1 infectivity and virion protein synthesis by several orders of magnitude. HIV-1 cap hypermethylation required nuclear RNA helicase A (RHA)/DHX9 interaction with the shape of the 5′ untranslated region (UTR) primer binding site (PBS) segment. Down-regulation of RHA or the anomalous shape of the PBS segment abrogated hypermethylated caps and derepressed eIF4E binding for virion protein translation during global down-regulation of host translation. mTOR inhibition was detrimental to HIV-1 proliferation and attenuated Tat, Rev, and Nef synthesis. This study identified mutually exclusive translation pathways and the calibration of virion structural/accessory protein synthesis with de novo synthesis of the viral regulatory proteins. The hypermethylation of select, viral mRNA resulted in CBC exchange to heterodimeric CBP80/NCBP3 that expanded the functional capacity of HIV-1 in immune cells.

DeePVP: Identification and classification of phage virion protein using deep learning

The poor annotation of phage virion protein (PVP) is the bottleneck of many areas of viral research, such as viral phylogenetic analysis, viral host identification and antibacterial drug design. Because of the high diversity of the PVP sequences, the PVP annotation remains a great challenging bioinformatic task. Based on deep learning, we present DeePVP that contains a main module and an extended module. The main module aims to identify the PVPs from non-PVP over a phage genome, while the extended module can further classify the predicted PVP into one of the ten major classes of PVP. Compared with the state-of-the-art tools that can distinguish PVP from non-PVP, DeePVP's main module performs much better, with an F1-score 9.05% higher in the PVP identification task. Compared with PhANNs, a tool that can further classify the predicted PVP into a specific class, the overall accuracy of DeePVP's extended module is approximately 3.72% higher in the PVP classification task. Two application cases on the genome of mycobacteriophage PDRPxv and Escherichia phage HP3 show that the predictions of DeePVP are much more reliable and can better reveal the compact PVP-enriched region, which may be conserved during the viral evolution process, over the phage genome.

iPVP-MCV: A Multi-Classifier Voting Model for the Accurate Identification of Phage Virion Proteins

The classic structure of a bacteriophage is commonly characterized by complex symmetry. The head of the structure features icosahedral symmetry, whereas the tail features helical symmetry. The phage virion protein (PVP), a type of bacteriophage structural protein, is an essential material of the infectious viral particles and is responsible for multiple biological functions. Accurate identification of PVPs is of great significance for comprehending the interaction between phages and host bacteria and developing new antimicrobial drugs or antibiotics. However, traditional experimental approaches for identifying PVPs are often time-consuming and laborious. Therefore, the development of computational methods that can efficiently and accurately identify PVPs is desired. In this study, we proposed a multi-classifier voting model called iPVP-MCV to enhance the predictive performance of PVPs based on their amino acid sequences. First, three types of evolutionary features were extracted from the position-specific scoring matrix (PSSM) profiles to represent PVPs and non-PVPs. Then, a set of baseline models were trained based on the support vector machine (SVM) algorithm combined with each type of feature descriptors. Finally, the outputs of these baseline models were integrated to construct the proposed method iPVP-MCV by using the majority voting strategy. Our results demonstrated that the proposed iPVP-MCV model was superior to existing methods when performing the rigorous independent dataset test.

Application of machine learning in bacteriophage research

Phages are one of the key components in the structure, dynamics, and interactions of microbial communities in different bins. It has a clear impact on human health and the food industry. Bacteriophage characterization using in vitro approaches are time/cost consuming and laborious tasks. On the other hand, with the advent of new high-throughput sequencing technology, the development of a powerful computational framework to characterize the newly identified bacteriophages is inevitable for future research. Machine learning includes powerful techniques that enable the analysis of complex datasets for knowledge discovery and pattern recognition. In this study, we have conducted a comprehensive review of machine learning methods application using different types of features were applied in various aspects of bacteriophage research including, automated curation, identification, classification, host species recognition, virion protein identification, and life cycle prediction. Moreover, potential limitations and advantages of the developed frameworks were discussed.

Effect of Inactivation Methods on SARS-CoV-2 Virion Protein and Structure

The risk posed by Severe Acute Respiratory Syndrome Coronavirus -2 (SARS-CoV-2) dictates that live-virus research is conducted in a biosafety level 3 (BSL3) facility. Working with SARS-CoV-2 at lower biosafety levels can expedite research yet requires the virus to be fully inactivated. In this study, we validated and compared two protocols for inactivating SARS-CoV-2: heat treatment and ultraviolet irradiation. The two methods were optimized to render the virus completely incapable of infection while limiting the destructive effects of inactivation. We observed that 15 min of incubation at 65 °C completely inactivates high titer viral stocks. Complete inactivation was also achieved with minimal amounts of UV power (70,000 µJ/cm2), which is 100-fold less power than comparable studies. Once validated, the two methods were then compared for viral RNA quantification, virion purification, and antibody detection assays. We observed that UV irradiation resulted in a 2-log reduction of detectable genomes compared to heat inactivation. Protein yield following virion enrichment was equivalent for all inactivation conditions, but the quality of resulting viral proteins and virions were differentially impacted depending on inactivation method and time. Here, we outline the strengths and weaknesses of each method so that investigators might choose the one which best meets their research goals.

VirionFinder: Identification of Complete and Partial Prokaryote Virus Virion Protein From Virome Data Using the Sequence and Biochemical Properties of Amino Acids

Viruses are some of the most abundant biological entities on Earth, and prokaryote virus are the dominant members of the viral community. Because of the diversity of prokaryote virus, functional annotation cannot be performed on a large number of genes from newly discovered prokaryote virus by searching the current database; therefore, the development of an alignment-free algorithm for functional annotation of prokaryote virus proteins is important to understand the viral community. The identification of prokaryote virus proteins (PVVPs) is a critical step for many viral analyses, such as species classification, phylogenetic analysis and the exploration of how prokaryote virus interact with their hosts. Although a series of PVVP prediction tools have been developed, the performance of these tools is still not satisfactory. Moreover, viral metagenomic data contains fragmented sequences, leading to the existence of some incomplete genes. Therefore, a tool that can identify partial prokaryote virus proteins is also needed. In this work, we present a novel algorithm, called VirionFinder, to identify the complete and partial PVVPs from non-prokaryote virus virion proteins (non-PVVPs). VirionFinder uses the sequence and biochemical properties of 20 amino acids as the mathematical model to encode the protein sequences and uses a deep learning technique to identify whether a given protein is a PVVP. Compared with the state-of-the-art tools using artificial benchmark datasets, the results show that under the same specificity (Sp), the sensitivity (Sn) of VirionFinder is approximately 10–34% much higher than the Sn of these tools on both complete and partial proteins. When evaluating related tools using real virome data, the recognition rate of PVVP-like sequences of VirionFinder is also much higher than that of the other tools. We expect that VirionFinder will be a powerful tool for identifying novel virion proteins from both complete prokaryote virus genomes and viral metagenomic data. VirionFinder is freely available at https://github.com/zhenchengfang/VirionFinder.

Effects of inactivation method on SARS-CoV-2 virion protein and structure

The risk posed by Severe Acute Respiratory Syndrome Coronavirus −2 (SARS-CoV-2) dictates that live-virus research is conducted in a biosafety level 3 (BSL3) facility. Working with SARS-CoV-2 at lower biosafety levels can expedite research yet requires the virus to be fully inactivated. In this study, we validated and compared two protocols for inactivating SARS-CoV-2: heat treatment and ultraviolet irradiation. The two methods were optimized to render the virus completely incapable of infection while limiting destructive effects of inactivation. We observed that 15 minutes of incubation at 65°C completely inactivates high titer viral stocks. Complete inactivation was also achieved with minimal amounts of UV power (70,000 μJ/cm2), which is 100-fold less power than comparable studies. Once validated, the two methods were then compared for viral RNA quantification, virion purification, and antibody recognition. We observed that UV irradiation resulted in a 2-log reduction of detectable genomes compared to heat inactivation. Protein yield following virion enrichment was equivalent for all inactivation conditions, but the resulting viral proteins and virions were negatively impacted by inactivation method and time. We outline the strengths and weaknesses of each method so that investigators might choose the one which best meets their research goals.

The Molluscum Contagiosum Gene MC021L Partially Compensates for the Loss of Its Vaccinia Virus Homolog, F13L

ABSTRACT Orthopoxviruses produce two antigenically distinct infectious enveloped virions termed intracellular mature virions and extracellular virions (EV). EV have an additional membrane compared to intracellular mature virions due to a wrapping process at the trans-Golgi network and are required for cell-to-cell spread and pathogenesis. Specific to the EV membrane are a number of proteins highly conserved among orthopoxviruses, including F13, which is required for the efficient wrapping of intracellular mature virions to produce EV and which plays a role in EV entry. The distantly related molluscipoxvirus, molluscum contagiosum virus, is predicted to encode several vaccinia virus homologs of EV-specific proteins, including the homolog of F13L, MC021L. To study the function of MC021, we replaced the F13L open reading frame in vaccinia virus with an epitope-tagged version of MC021L. The resulting virus (vMC021L-HA) had a small-plaque phenotype compared to vF13L-HA but larger than vΔF13L. The localization of MC021-HA was markedly different from that of F13-HA in infected cells, but MC021-HA was still incorporated in the EV membrane. Similar to F13-HA, MC021-HA was capable of interacting with both A33 and B5. Although MC021-HA expression did not fully restore plaque size, vMC021L-HA produced amounts of EV similar to those produced by vF13L-HA, suggesting that MC021 retained some of the functionality of F13. Further analysis revealed that EV produced from vMC021L-HA exhibit a marked reduction in target cell binding and an increase in dissolution, both of which correlated with a small-plaque phenotype. IMPORTANCE The vaccinia virus extracellular virion protein F13 is required for the production and release of infectious extracellular virus, which in turn is essential for the subsequent spread and pathogenesis of orthopoxviruses. Molluscum contagiosum virus infects millions of people worldwide each year, but it is unknown whether EV are produced during infection for spread. Molluscum contagiosum virus contains a homolog of F13L termed MC021L. To study the potential function of this homolog during infection, we utilized vaccinia virus as a surrogate and showed that a vaccinia virus expressing MC021L-HA in place of F13L-HA exhibits a small-plaque phenotype but produces similar levels of EV. These results suggest that MC021-HA can compensate for the loss of F13-HA by facilitating wrapping to produce EV and further delineates the dual role of F13 during infection.