Biology subjects

Mukherjee, J.

Publications and source records attributed to Mukherjee, J..

4 recordsLinked to original sources

bioRxiv2018

β-actin mRNA interactome mapping by proximity biotinylation

The molecular function and fate of mRNAs are controlled by RNA binding proteins (RBPs). However, identification of the interacting proteome of a specific mRNA in vivo is still very challenging. Based on the widely-used RNA tagging with MS2 aptamers for RNA visualization, we developed a novel RNA proximity biotinylation (RNA-BioID) method by tethering biotin ligase (BirA*) via MS2 coat protein (MCP) at the 3UTR of endogenously MS2 tagged {beta}-actin mRNA in mouse embryonic fibroblasts (MEFs). We demonstrate the dynamics of the {beta}-actin mRNA interactome by characterizing its changes upon serum-induced localization of the mRNA. Apart from the previously known interactors, we identified over 60 additional {beta}-actin associated RBPs by RNA-BioID, among them the KH-domain containing protein FUBP3/MARTA2 has shown to be required for {beta}-actin mRNA localization. This protein binds to the 3-untranslated region of {beta}-actin mRNA, is essential for {beta}-actin mRNA localization but does not interact with the characterized {beta}-actin zipcode element. RNA-BioID provides a tool to identify new mRNA interactors and to study the dynamic view of the interacting proteome of endogenous mRNAs in space and time.

cell biology↗

bioRxiv2018

GRaphical footprint based Alignment-Free method (GRAFree) for reconstructing evolutionary Traits in Large-Scale Genomic Features

In our study, we attempt to extract novel features from mitochondrial genomic sequences reflecting their evolutionary traits by our proposed method GRAFree (GRaphical footprint based Alignment-Free method). These features are used to build a phylogenetic tree given a set of species from insect, fish, bird, and mammal. A novel distance measure in the feature space is proposed for the purpose of reflecting the proximity of these species in the evolutionary processes. The distance function is found to be a metric. We have proposed a three step technique to select a feature vector from the feature space. We have carried out variations of these selected feature vectors for generating multiple hypothesis of these trees and finally we used a consensus based tree merging algorithm to obtain the phylogeny. Experimentations were carried out with 157 species covering four different classes such as, Insecta, Actinopterygii, Aves, and Mammalia. We also introduce a measure of quality of the inferred tree especially when the reference tree is not present. The performance of the output tree can be measured at each clade by considering the presence of each species at the corresponding clade. GRAFree can be applied on any graphical representation of genome to reconstruct the phylogenetic tree. We apply our proposed distance function on the selected feature vectors for three naive methods of graphical representation of genome. The inferred tree reflects some accepted evolutionary traits with a high bootstrap support. This concludes that our proposed distance function can be applied to capture the evolutionary relationships of a large number of both close and distance species using graphical methods.

evolutionary biology↗

bioRxiv2018

Data-driven analysis of biomedical literature suggests broad-spectrum benevolence of culinary herbs and spices

Spices and herbs are key dietary ingredients used across cultures worldwide. Beyond their use as flavoring and coloring agents, the popularity of these aromatic plant products in culinary preparations has been attributed to their antimicrobial properties. Last few decades have witnessed an exponential growth of biomedical literature investigating the impact of spices and herbs on health, presenting an opportunity to mine for patterns from empirical evidence. Systematic investigation of empirical evidence to enumerate the health consequences of culinary herbs and spices can provide valuable insights into their therapeutic utility. We implemented a text mining protocol to assess the health impact of spices by assimilating, both, their positive and negative effects. We conclude that spices show broad-spectrum benevolence across a range of disease categories in contrast to negative effects that are comparatively narrow-spectrum. We also implement a strategy for disease-specific culinary recommendations of spices based on their therapeutic tradeoff against adverse effects. Further by integrating spice-phytochemical-disease associations, we identify bioactive spice phytochemicals potentially involved in their therapeutic effects. Our study provides a systems perspective on health effects of culinary spices and herbs with applications for dietary recommendations as well as identification of phytochemicals potentially involved in underlying molecular mechanisms.

bioinformatics↗

bioRxiv2018

SpiceRx: an integrated resource for the health impacts of culinary spices and herbs

Spices and herbs are key dietary ingredients used in cuisines across the world. They have been reported to be of medicinal value for a wide variety of diseases through a large body of biomedical investigations. Bioactive phytochemicals in these plant products form the basis of their therapeutic potential as well as adverse effects. A systematic compilation of empirical data involving these aspects of culinary spices and herbs could help unravel molecular mechanisms underlying their effects on health.\n\nSpiceRx provides a platform for exploring the health impact of spices and herbs used in food preparations through a structured database of tripartite relationships with their phytochemicals and disease associations. Starting with an extensive dictionary of culinary spices and herbs, their disease associations were text mined from MEDLINE, the largest database of biomedical abstracts, assisted with manual curation. This information was further combined with spice-phytochemical and phytochemical-disease associations. SpiceRx is an integrated repertoire of evidence-based knowledge pertaining to the health impacts of culinary spices and herbs, and facilitates their disease-specific culinary recommendations as well as exploration of molecular mechanisms underlying their health effects.\n\nAvailability and ImplementationSpiceRx is available at http://cosylab.iiitd.edu.in/spicerx and supports all modern browsers. SpiceRx is implemented with Python web development framework Django and relational database PostgreSQL; the front-end was built using HTML, CSS, JavaScript, AJAX, jQuery, JSME Molecular Editor, Bootstrap, Jmol, DataTables and Google Charts.\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗