Confounding factors in profiling of locus-specific human endogenous retrovirus (HERV) transcript signatures in primary T cells using multi-study-derived datasets.

BACKGROUND: Human endogenous retroviruses (HERV) are repetitive sequence elements and a substantial part of the human genome. Their role in development has been well documented and there is now mounting evidence that dysregulated HERV expression also contributes to various human diseases. While research on HERV elements has in the past been hampered by their high sequence similarity, advanced sequencing technology and analytical tools have empowered the field. For the first time, we are now able to undertake locus-specific HERV analysis, deciphering expression patterns, regulatory networks and biological functions of these elements. To do so, we inevitable rely on omics datasets available through the public domain. However, technical parameters inevitably differ, making inter-study analysis challenging. We here address the issue of confounding factors for profiling locus-specific HERV transcriptomes using datasets from multiple sources. METHODS: We collected RNAseq datasets of CD4 and CD8 primary T cells and extracted HERV expression profiles for 3220 elements, resembling most intact, near full-length proviruses. Looking at sequencing parameters and batch effects, we compared HERV signatures across datasets and determined permissive features for HERV expression analysis from multiple-source data. RESULTS: We could demonstrate that considering sequencing parameters, sequencing-depth is most influential on HERV signature outcome. Sequencing samples deeper broadens the spectrum of expressed HERV elements. Sequencing mode and read length are secondary parameters. Nevertheless, we find that HERV signatures from smaller RNAseq datasets do reliably reveal most abundantly expressed HERV elements. Overall, HERV signatures between samples and studies overlap substantially, indicating a robust HERV transcript signature in CD4 and CD8 T cells. Moreover, we find that measures of batch effect reduction are critical to uncover genic and HERV expression differences between cell types. After doing so, differences in the HERV transcriptome between ontologically closely related CD4 and CD8 T cells became apparent. CONCLUSION: In our systematic approach to determine sequencing and analysis parameters for detection of locus-specific HERV expression, we provide evidence that analysis of RNAseq datasets from multiple studies can aid confidence of biological findings. When generating de novo HERV expression datasets we recommend increased sequence depth ( > = 100 mio reads) compared to standard genic transcriptome pipelines. Finally, batch effect reduction measures need to be implemented to allow for differential expression analysis.

In Silico Design of siRNAs for Silencing CLEC5A Receptor as a Potential Therapeutic Approach Against Dengue and Japanese Encephalitis Virus Infection in Human.

Dengue and Japanese encephalitis virus (JEV) are mosquito-borne RNA viruses that can cause severe illness leading to death in the tropics and subtropics. Both of these viruses interact directly with the C-type lectin domain family 5, member A receptor (CLEC5A) on human macrophages which stimulates the release of proinflammatory cytokines. Since blockade of this interaction has been shown to suppress the secretion of cytokines, CLEC5A is considered a potential target for the development of new treatments to reduce virus-induced brain damage. Developing a vaccine against dengue is challenging because this virus can cause disease through 4 different serotypes. Therefore, the vaccine must immunize against all 4 serotypes to be effective, while unvaccinated people still contract JEV and suffer from its complications. Small interfering RNAs (siRNAs) play an important role in regulating gene expression by causing the degradation of target mRNAs. In this study, we attempted to rationally design potential siRNA molecules using various software, targeting the CLEC5A gene. In total, 3 siRNAs were found to be potential candidates for CLEC5A silencing. They showed good target accessibility, optimum guanine-cytosine (GC) content, the least chance of off-target effects, positive energy of folding, and strong interaction with Argonaute2 protein as denoted by a negative docking energy score. In addition, molecular dynamics simulation of the siRNA-Ago2-docked complexes showed the stability of the complexes over 1.5 nanoseconds. These predicted siRNAs might effectively downregulate the expression of the CLEC5A receptor and thus prove vital in the treatment of dengue and JEV infections.

Most frequently harboured missense variants of hACE2 across different populations exhibit varying patterns of binding interaction with spike glycoproteins of emerging SARS-CoV-2 of different lineages.

Since the emergence of SARS-CoV-2 at Wuhan in the Hubei province of China in 2019, the virus has accumulated various mutations, giving rise to many variants. According to the combinations of mutations acquired, these variants are classified into lineages and greatly differ in infectivity and transmissibility. In 2021 alone, a variant of interest (VoI) Mu (B.1.621), as well as, variants of concern (VoC) Delta (B.1.617.2) and Omicron (BA.1, BA.2) and later in 2022, BA.4, BA.5, and BA.2.12.1 have emerged. Since then, the world has seen prominent surges in the rate of infection during short periods of time. However, not all populations have suffered equally, which suggests a possible role of host genetic factors. Here, we investigated the strength of binding of the spike glycoprotein receptor-binding domain (RBD) of the SARS-CoV-2 variants: Mu, Delta, Delta Plus (AY.1), Omicron sub-variants BA.1, BA.2, BA.4, BA.5, and BA.2.12.1 with the human angiotensin-converting enzyme 2 (hACE2) missense variants prevalent in major populations. In this purpose, molecular docking analysis, as well as, molecular dynamics simulation was performed of the above-mentioned SARS-CoV-2 RBD variants with the hACE2 containing the single amino acid substitutions prevalent in African (E37K), Latin American (F40L), non-Finnish European (D355 N), and South Asian (P84T) populations, in order to predict the effects of the lineage-defining mutations of the viral variants on receptor binding. The effects of these mutations on protein stability were also explored. The protein-protein docking and molecular dynamics simulation analyses have revealed variable strength of attachment and exhibited altered interactions in the case of different hACE2-RBD complexes. In vitro studies are warranted to confirm these findings which may enable early prediction regarding the risk of transmissibility of newly emerging variants across different populations in the future.

Prediction of putative potential siRNAs for inhibiting SARS-CoV-2 strains, including variants of concern and interest.

Aim: To predict siRNAs as a therapeutic intervention for highly infectious new variants of SARS-CoV-2. Methods: Conserved coding sequence regions of 11 SARS-CoV-2 proteins were used to construct siRNAs through sampling of metadata comprising 214,256 sequences. Results: Predicted siRNAs S1: 5'-UCAUUGAGAAAUGUUUACGCA-3' and S2: 5'-AAAGACAUCAGCAUACUCCUG-3' against RdRp of SARS-CoV-2 satisfied all the stringent filtering processes and showed good binding characteristics. The designed siRNAs are expected to inhibit viral replication and transcription of various coronavirus strains encompassing variants of concern and interest. Conclusion: The predicted siRNAs are expected to be potent against SARS-CoV-2, and following in vitro and in vivo validations may be considered as potential therapeutic measures.

An in-depth in silico and immunoinformatics approach for designing a potential multi-epitope construct for the effective development of vaccine to combat against SARS-CoV-2 encompassing variants of concern and interest.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest of the several viral pathogens that have acted as a threat to human health around the world. Thus, to prevent COVID-19 and control the outbreak, the development of vaccines against SARS-CoV-2 is one of the most important strategies at present. The study aimed to design a multi-epitope vaccine (MEV) against SARS-CoV-2. For the development of a more effective vaccine, 1549 nucleotide sequences were taken into consideration, including the variants of concern (B.1.1.7, B.1.351, P.1 and, B.1.617.2) and variants of interest (B.1.427, B.1.429, B.1.526, B.1.617.1 and P.2). A total of 11 SARS-CoV-2 proteins (S, N, E, M, ORF1ab polyprotein, ORF3a, ORF6, ORF7a, ORF7b, ORF8, ORF10) were targeted for T-cell epitope prediction and S protein was targeted for B-cell epitope prediction. MEV was constructed using linkers and adjuvant beta-defensin. The vaccine construct was verified, based on its antigenicity, physicochemical properties, and its binding potential, with toll-like receptors (TLR2, TLR4), ACE2 receptor and B cell receptor. The selected vaccine construct showed considerable binding with all the receptors and a significant immune response, including elevated antibody titer and B cell population along with augmented activity of TH cells, Tc cells and NK cells. Thus, immunoinformatics and in silico-based approaches were used for constructing MEV which is capable of eliciting both innate and adaptive immunity. In conclusion, the vaccine construct developed in this study has all the potential for the development of a next-generation vaccine which may in turn effectively combat the new variants of SARS-CoV-2 identified so far. However, in vitro and animal studies are warranted to justify our findings for its utility as probable preventive measure.