Biology subjects

Janini, L. M. R.

Publications and source records attributed to Janini, L. M. R..

3 recordsLinked to original sources

bioRxiv2023

Development and characterization of a multimeric recombinant protein based on the spike protein receptor binding domain of SARS-CoV-2 that can neutralize virus infection

BackgroundThe SARS-CoV-2 virus, responsible for the COVID-19 pandemic, has four structural proteins and sixteen non-structural proteins. The S-protein is one of the structural proteins exposed on the surface of the virus and is the main target for producing neutralizing antibodies and vaccines. The S-protein forms a trimer that can bind the angiotensin-converting enzyme 2 (ACE2) through its receptor binding domain (RBD) for cell entry. MethodsWe stably expressed in a constitutive manner in HEK293 cells a new recombinant protein containing a signal sequence of immunoglobulin to produce an extended C-terminal portion of the RBD followed by a region responsible for the trimerization inducer of the bacteriophage T4, and a sequence of 6 histidines. The protein was produced and released in the culture supernatant of cells and was purified by Ni-agarose column and exclusion chromatography. It was then characterized by SDS-polyacrylamide gel and used as antigen to generate protective antibodies to inhibit ACE2 receptor interaction and virus entry into Vero cells. ResultsThe purified protein displayed a molecular mass of 135 kDa and with a secondary structure like the monomeric RBD. Electrophoresis analysis in SDS-polyacrylamide gel with and without reducing agents, and in the presence of crosslinkers indicated that it forms a multimeric structure composed of trimers and hexamers. The purified protein was able to bind the ACE2 receptor and generated high antibody titers in mice (1:10000), capable of inhibiting the binding of biotin labeled ACE2 to the virus S1 subunit, and to neutralize the entry of the SARS-CoV-2 Wuhan strain into cells. ConclusionOur results characterize a new multimeric protein based on S1 subunit to combat COVID-19, as a possible immunogen or antigen for diagnosis.

microbiology↗

bioRxiv2022

Mathematical Modeling of Bottleneck Transmissions of RNA Virus Infecting a Homogeneous Host Population

There is no consensus about when a potential viral infection event presents greater risk of a successful transmission. Some authors suggest that late infection stages present higher risk of transmission. Others suggest that the early infection stages play a most relevant role in transmission events. However, studies considering the fitness or mutational effects on the viral particles over transmission events are lacking. We propose to approach this question through a two-level mathematical model based on RNA viral population dynamics. The first level of the model represents the intra-host viral population dynamics and the second level of the model represents the host-to-host dynamics of transmission events. The intra-host dynamics model uses the fitness of viral particles as means to track the presence of highly infective particles during transmission bottlenecks. More specifically, the intra-host dynamics is described by a stochastic quasispecies, based on a multivariate branching process. The host-to-host dynamics of transmission events is emulated by a putative transmission tree with host zero at the root and a fixed number of branches emanating from each internal node. A Monte Carlo strategy was adopted to explore the tree by sampling random walks along transmission chains along the tree. Viral infections of a single host and several transmission events among hosts were simulated in early and late infection stages scenarios. The results show that the early infection stages may represent a key factor in the viral pandemic. Over the evolution of the viral population within each host the mean fitness decreases due to occurrence of mutations (most of them causing deleterious effects). Despite the small opportunity interval, transmissions that occur in early stages could probably infect new hosts at a higher rate than in late stages. It was observed that a very early transmission scenario could reach a transmission chain 20 times longer than a very late transmission scenario. This indicates that the quality of the viral particles is a relevant factor for transmission events.

evolutionary biology↗

bioRxiv2021

Direct RNA sequencing reveals SARS-CoV-2 m6A sites and possible differential DRACH motif methylation among variants

The causative agent of COVID-19 pandemic, the SARS-CoV-2 coronavirus, has a 29,903 bases positive-sense single-stranded RNA genome. RNAs exhibit about 100 modified bases that are essential for proper function. Among internal modified bases, the N6-methyladenosine, or m6A, is the most frequent, and is implicated in SARS-CoV-2 immune response evasion. Although the SARS-CoV-2 genome is RNA, almost all genomes sequenced so far are in fact, reverse transcribed complementary DNAs. This process reduces the true complexity of these viral genomes because incorporation of dNTPs hides RNA base modifications. Here, in this perspective paper, we present an initial exploration of the Nanopore direct RNA sequencing to assess the m6A residues in the SARS-CoV-2 sequences of ORF3a, E, M, ORF6, ORF7a, ORF7b, ORF8, N, ORF10 and the 3-untranslated region. We identified 15 m6A methylated positions, of which, 6 are in ORF N. Also, because m6A is associated with the DRACH motif, we compared its distribution in major SARS-CoV-2 variants. Although DRACH is highly conserved among variants we show that variants Beta and Eta have a fourth position C>U change in DRACH at 28,884b that could affect methylation. The Nanopore technology offers a unique opportunity for the study of viral epitranscriptomics. This technique is PCR-free and is not sequencing-by-synthesis, therefore, no PCR bias and synthesis errors are introduced. The modified bases are preserved and assessed directly with no need for chemical treatments or antibodies. This is the first report of direct RNA sequencing of a Brazilian SARS-CoV-2 sample coupled with the identification of modified bases.

genomics↗