Biology subjects

Kula-Pacurar, A.

Publications and source records attributed to Kula-Pacurar, A..

3 recordsLinked to original sources

bioRxiv2026

Identification of different sequence properties between HIV-1 DNA and RNA across subtypes using the k-mer-based approach

Advanced analytical tools that enable mining of the masked features hidden in intricate datasets and strengthening the biological interpretation of multigenomic outputs hold paramount importance. At present, HIV-1 subtyping remains a challenging task in a great part due to analytical tool discordance. To tackle this issue, in this study, we present an updated version of a k-mer-based approach, PORT-EK-v2, a streamlined bioinformatic pipeline, allowing for a comparison of multiple genomic datasets and identification of over-represented genomic regions, k-mers, related to specific origins of datasets. Using PORT-EK-v2, we exemplified that intrinsic sequence patterns between HIV-1 DNA and RNA are distinct across group M HIV-1 subtypes. Furthermore, we showcased that "isolate k-mer count", a predictive variable computed in this work, could serve as a default choice in classifying the HIV-1 DNA versus RNA sequences across subtypes. Lastly, results based on network-based analyses and Markov chain Monte Carlo modeling unveiled a clear discontinuation of a random walk throughout the network properties corresponding to each tested group of HIV-1 subtypes, confirming the specificity of enriched k-mer retrieved by PORT-EK-v2 and the genomic diversity across group M HIV-1 subtypes. Source code for PORT-EK-v2 is at https://github.com/Quantitative-Virology-Research-Group/PORT-EK-version-2 and is freely available.

bioinformatics↗

bioRxiv2024

Distinguishable topological properties of functional genome networks in HIV-1 reservoirs

HIV-1 reservoirs display heterogeneous nature, lodging both intact and defective proviruses. Recent evidence has shed light on their difference, particularly in the context of immune-mediated selection. To deepen our understanding of such heterogeneous HIV-1 reservoirs and their functional implications, we pioneered the integration of basic concepts of graph theory to characterize the composition of HIV-1 reservoirs. Our analysis revealed noticeable topological properties in networks, featuring immunologic signatures enriched by genes harboring intact and defective proviruses, when comparing antiretroviral therapy (ART)-treated HIV-1-infected individuals and elite controllers. The key variable, the rich factor, played a pivotal role in classifying distinct topological properties in networks. The host gene expression strengthened the accuracy of classification between elite controllers and ART-treated patients. Overall, our work provides a prime example of leveraging genomic approaches alongside mathematical tools to unravel the complexities of HIV-1 reservoirs.

genomics↗

bioRxiv2020

Replication of SARS-CoV-2 in human respiratory epithelium

SARS-CoV-2 emerged by the end of 2019 to rapidly spread in 2020. At present, it is of utmost importance to understand the virus biology and to rapidly assess the potential of existing drugs and develop new active compounds. While some animal models for such studies are under development, most of the research is carried out in the Vero E6 cells. Here, we propose fully differentiated human airway epithelium cultures as a model for studies on the SARS-CoV-2. Further, we also provide basic characteristics of the system.

microbiology↗