Identification of Novel Therapeutic Candidates Against SARS-CoV-2 Infections: An Application of RNA Sequencing Toward mRNA Based Nanotherapeutics

Abstract

Due to fast transmission and various circulating SARS-CoV-2 variants, a significant increase of coronavirus 2019 infection cases with acute respiratory symptoms has prompted worries about the efficiency of current vaccines. The possible evasion from vaccine immunity urged scientists to identify novel therapeutic targets for developing improved vaccines to manage worldwide COVID-19 infections. Our study sequenced pooled peripheral blood mononuclear cells transcriptomes of SARS-CoV-2 patients with moderate and critical clinical outcomes to identify novel potential host receptors and biomarkers that can assist in developing new translational nanomedicines and vaccine therapies. The dysregulated signatures were associated with humoral immune responses in moderate and critical patients, including B-cell activation, cell cycle perturbations, plasmablast antibody processing, adaptive immune responses, cytokinesis, and interleukin signaling pathway. The comparative and longitudinal analysis of moderate and critically infected groups elucidated diversity in regulatory pathways and biological processes. Several immunoglobin genes (IGLV9-49, IGHV7-4, IGHV3-64, IGHV1-24, IGKV1D-12, and IGKV2-29), ribosomal proteins (RPL29, RPL4P2, RPL5, and RPL14), inflammatory response related cytokines including Tumor Necrosis Factor (TNF, TNFRSF17, and TNFRSF13B), C-C motif chemokine ligands (CCL3, CCL25, CCL4L2, CCL22, and CCL4), C-X-C motif chemokine ligands (CXCL2, CXCL10, and CXCL11) and genes related to cell cycle process and DNA proliferation (MYBL2, CDC20, KIFC1, and UHCL1) were significantly upregulated among SARS-CoV-2 infected patients. 60S Ribosomal protein L29 (RPL29) was a highly expressed gene among all COVID-19 infected groups. Our study suggested that identifying differentially expressed genes (DEGs) based on disease severity and onset can be a powerful approach for identifying potential therapeutic targets to develop effective drug delivery systems against SARS-CoV-2 infections. As a result, potential therapeutic targets, such as the RPL29 protein, can be tested in vivo and in vitro to develop future mRNA-based translational nanomedicines and therapies to combat SARS-CoV-2 infections.

Deep proteome analysis of time-series human plasma samples applied to Covid-19 antibody test

“…The identification of this RL11_human in this analysis, along with its alignment with the variation profile of the antigen antibody group from the antibody testing, suggests relevance to previous reports [18][19][20]. According to the report by Q. Zhu et al [19], they propose the potential to create a conducive cellular environment that significantly facilitates cell replication and promotes a favorable context for virus replication.…”

“…Investigation into this phenomenon revealed previous reports of a similar significant increase in the expression of this 60S Ribosomal protein after Covid-19 infection. Z. Khalid et al have previously reported that 60S Ribosomal protein L29 (RPL29) was highly expressed across all COVID-19 infection groups [18][19][20]. The screened 60S ribosomal protein L11 (RL11_human) in this analysis is a component of the 60S ribosomal subunit, a central part of the ribosome, with several important functions: Ribosome conformation: RL11_human plays a crucial role in the conformation and maturation of ribosomes.…”

Portraying the dark side of endogenous IFN-λ for promoting cancer progression and immunoevasion in pan-cancer

“…4 I), indicating that they have a positive role in the enhancement of tumor-associated immunity. Some of the upregulated genes such as CXCL13 [ 21 ] and CXCL11 [ 22 ] and KLK5 [ 23 ] have been experimentally verified in prior studies to regulate humoral immune response and support tumor infiltration. Furthermore, KEGG pathway enrichment analysis showed that these DEGs were mainly enriched in cytokine-cytokine receptor interactions and JAK-STAT signaling pathway pathways (Fig.…”

Adaptive best subset selection algorithm and genetic algorithm aided ensemble learning method identified a robust severity score of COVID‐19 patients

“…Among these 14 genes (Table S2), some of them are reported to be closely related to COVID-19. RNF187 has been shown to be a biomarker in children with COVID-19 [22]; NCR3 is significantly associated with the decreased proportion of CD8+ T and T helper 2 cells in the peripheral circulation in COVID-19 patients [23]; TEX2 can predict the ventilator-free days of patients with COVID-19 [24]; ITPKB is a hub gene shared by Alzheimer's disease and COVID-19 [25]; TUBG1 is involved in the immune interaction of COVID-19 and lymphoma [26]; RPL14 is a significantly upregulated gene in COVID-19 patients [27]. Besides the above genes, other unreported genes in the AGAE score may also have research significance.…”