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Biology subjects

Pai, S. S.

Publications and source records attributed to Pai, S. S..

2 recordsLinked to original sources

RelCoVax(R), a two antigen subunit protein vaccine candidate against SARS-CoV-2 induces strong immune responses in mice

The COVID-19 pandemic has spurred an unprecedented movement to develop safe and effective vaccines against the SARS-CoV-2 virus to immunize the global population. The first set of vaccine candidates that received emergency use authorization targeted the spike (S) glycoprotein of the SARS-CoV-2 virus that enables virus entry into cells via the receptor binding domain (RBD). Recently, multiple variants of SARS-CoV-2 have emerged with mutations in S protein and the ability to evade neutralizing antibodies in vaccinated individuals. We have developed a dual RBD and nucleocapsid (N) subunit protein vaccine candidate named RelCoVax(R) through heterologous expression in mammalian cells (RBD) and E. coli (N). The RelCoVax(R) formulation containing a combination of aluminum hydroxide (alum) and a synthetic CpG oligonucleotide as adjuvants elicited high antibody titers against RBD and N proteins in mice after a prime and boost dose regimen administered 2 weeks apart. The vaccine also stimulated cellular immune responses with a potential Th1 bias as evidenced by increased IFN-{gamma} release by splenocytes from immunized mice upon antigen exposure particularly N protein. Finally, the serum of mice immunized with RelCoVax(R) demonstrated the ability to neutralize two different SARS-CoV-2 viral strains in vitro including the Delta strain that has become dominant in many regions of the world and can evade vaccine induced neutralizing antibodies. These results warrant further evaluation of RelCoVax(R) through advanced studies and contribute towards enhancing our understanding of multicomponent subunit vaccine candidates against SARS-CoV-2.

immunology↗

A comparative analysis of computational tools for the prediction of epigenetic DNA methylation from long-read sequencing data

Recent development of Oxford Nanopore long-read sequencing has opened new avenues of identifying epigenetic DNA methylation. Among the different epigenetic DNA methylations, N6-methyladenosine is the most prevalent DNA modification in prokaryotes and 5-methylcytosine is common in higher eukaryotes. Here we investigated if N6-methyladenosine and 5-methylcytosine modifications could be predicted from the nanopore sequencing data. Using publicly available genome sequencing data of Saccharomyces cerevisiae, we compared the open-access computational tools, including Tombo, mCaller, Nanopolish and DeepSignal for predicting 6mA and 5mC. Our results suggest that Tombo and mCaller can predict DNA N6-methyladenosine modifications at a specific location, whereas, Tombo dampened fraction, Nanopolish methylation likelihood and DeepSignal methylation probability have comparable efficiency for 5-methylcytosine prediction from Oxford Nanopore sequencing data.

bioinformatics↗