Biology subjects

Bhakta, M.

Publications and source records attributed to Bhakta, M..

4 recordsLinked to original sources

bioRxiv2022

Honokiol and alfa-Mangostin inhibit Mayaro virus replication by stimulating the type I interferon pathway

Mayaro virus (MAYV) is an emerging arbovirus with increasing circulation across the Americas. In the present study, we evaluated the potential antiviral activity of the following natural compounds against MAYV and other arboviruses: Sanguinarine, (R)-Shikonin, Fisetin, Honokiol, Tanshinone IIA and -Mangostin. Sanguinarine and Shikonin showed significant cytotoxicity, whereas Fisetin, Honokiol, Tanshinone IIA and -Mangostin were well-tolerated in all the cell lines tested. Honokiol and -Mangostin treatment protected Vero-E6 cells against MAYV-induced damage and resulted in a dose-dependent reduction in viral progeny yields for each of the MAYV strains and human cell lines assessed. Also, Honokiol and -Mangostin disrupted MAYV infection at different stages of the virus life cycle. Moreover, these compounds decreased Una, Chikungunya and Zika viral titers and downmodulated the expression of E1 and nsP1 viral proteins from MAYV, Una and Chikungunya. Finally, in Honokiol- and -Mangostin-treated cells, we observed an upregulation in the expression of type I interferon and specific interferon-stimulated genes, including IFN, IFN{beta}, MxA, ISG15, OAS2, MDA-5, TNF and IL-1{beta}, which may promote an antiviral cellular state. Our results indicate that Honokiol and -Mangostin present potential broad-spectrum activity against different arboviruses through a possible modulation of the interferon pathway.

microbiology↗

bioRxiv2021

INCORPORATING A DYNAMIC GENE-BASED PROCESS MODULE INTO A CROP SIMULATION MODEL

Dynamic crop simulation models are tools that predict plant phenotype grown in specific environments for genotypes using genotype-specific parameters (GSPs), often referred to as "genetic coefficients." These GSPs are estimated using phenotypic observations and may not represent "true" genetic information. Instead, estimating GSPs requires experiments to measure phenotypic responses when new cultivars are released. The goal of this study was to evaluate a new approach that incorporates a dynamic gene-based module for simulating time-to-flowering for common bean (Phaseolus vulgaris L.) into an existing dynamic crop model. A multi-environment study conducted in 2011 and 2012 included 187 recombinant inbred lines (RILs) from a bi-parental bean family to measure the effects of quantitative trait loci (QTL), environment (E), and QTLxE interactions across five sites. The dynamic mixed linear model from Vallejos et al. (2020) was modified in this study to create a dynamic module that was then integrated into the CSM-CROPGRO-Drybean model. This new hybrid crop model, with the gene-based flowering module replacing the original flowering component, requires allelic makeup of each genotype being simulated and daily E data. The hybrid model was compared to the original CSM model using the same E data and previously estimated GSPs to simulate time-to-flower. The integrated gene-based module simulated days of first flower agreed closely with observed values (root mean square error of 2.73 days and model efficiency of 0.90) across the five locations and 187 genotypes. The hybrid model with its gene-based module also described most of the G, E and GxE effects on time-to-flower and was able to predict final yield and other outputs simulated by the original CSM. These results provide the first evidence that dynamic crop simulation models can be transformed into gene-based models by replacing an existing process module with a gene-based module for simulating the same process.

genomics↗

bioRxiv2019

Erosion of the Epigenetic Landscape and Loss of Cellular Identity as a Cause of Aging in Mammals

All living things experience entropy, manifested as a loss of inherited genetic and epigenetic information over time. As budding yeast cells age, epigenetic changes result in a loss of cell identity and sterility, both hallmarks of yeast aging. In mammals, epigenetic information is also lost over time, but what causes it to be lost and whether it is a cause or a consequence of aging is not known. Here we show that the transient induction of genomic instability, in the form of a low number of non-mutagenic DNA breaks, accelerates many of the chromatin and tissue changes seen during aging, including the erosion of the epigenetic landscape, a loss of cellular identity, advancement of the DNA methylation clock and cellular senescence. These data support a model in which a loss of epigenetic information is a cause of aging in mammals.\n\nOne Sentence SummaryThe act of repairing DNA breaks induces chromatin reorganization and a loss of cell identity that may contribute to mammalian aging

molecular biology↗

bioRxiv2018

Rational reprogramming of cellular states by combinatorial perturbation

Ectopic expression of transcription factors (TFs) can reprogram cell state. However, due to the large combinatorial space of possible TF cocktails, it remains difficult to identify TFs that reprogram specific cell types. Here, we develop Reprogram-Seq to experimentally screen thousands of TF cocktails for reprogramming performance. Reprogram-Seq leverages organ-specific cell atlas data with single-cell perturbation and computational analysis to predict, evaluate, and optimize TF combinations that reprogram a cell type of interest. Focusing on the cardiac system, we perform Reprogram-Seq on MEFs using an undirected library of 48 cardiac factors and separately on a directed library of 10 epicardial-related TFs. We identify a novel combination of 3 TFs which efficiently reprogram MEFs to epicardial-like cells that are transcriptionally, molecularly, morphologically, and functionally similar to primary epicardial cells. Reprogram-Seq holds promise to accelerate the generation of specific cell types for regenerative medicine.

genomics↗