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Biology subjects

Bhowmick, A. R.

Publications and source records attributed to Bhowmick, A. R..

3 recordsLinked to original sources

Multiscale patterning of a model apical extracellular matrix revealed by systematic endogenous protein tagging

Barrier epithelia are shielded from the external environment by their apical extracellular matrices (aECMs). The molecular complexity of aECMs has challenged understanding of their organization in vivo. To define the molecular architecture of a model aECM we generated a toolkit of 102 fluorescently tagged aECM components using gene editing in C. elegans, focusing on proteins secreted by the epidermis to form the collagen-rich cuticle. We developed efficient pipelines for modular protein tagging and rapid fluorophore swapping. Most tagged collagens were functional and exhibited exquisitely specific patterning across stages, cell types, and matrix substructures. We define multiple reference markers for key substructures including the little-understood cortical layer, as well as the helical crossed fiber arrays that function as a hydrostatic skeleton to maintain organismal shape. We further tagged >30 members of key aECM protein classes including proteases, protease inhibitors, and lipid transporters. Our standardized markers will allow dissection of the mechanistic basis of aECM spatiotemporal patterning in vivo. HighlightsO_LIFirst large-scale protein tagging resource for the apical extracellular matrix C_LIO_LIOptimization of CRISPR methods for protein tagging including color swaps C_LIO_LITagged proteins are functional and exhibit a high degree of stage-, cell- and compartment specificity C_LIO_LIReference localization patterns for multiple aECM compartments and markers for newly defined compartments C_LI

developmental biology↗

Deciphering Memory Patterns in Eco-Epidemiological systems through the lens of BaFOMS: A Bayesian Fractional Order Model Selection Method

The evolution of eco-epidemiological systems is significantly influenced by the memory or previous history of the system. These non-Markovian dynamics are effectively modelled using fractional derivatives (FDs), incorporating memory kernels that reflect long-term or short-term memory characteristics in corresponding nonlinear fractional differential evolution equations. We introduce BaFOMS, a framework for identifying and selecting the optimal FD model for eco-epidemiological processes based on historical data. Specifically, we evaluate a class of fractional logistic growth models defined by their time correlation functions and determine the optimal model through Bayesian inference, selecting the one with the highest posterior probability. We also demonstrated BaFOMS efficiency in parameter estimation and forecasting, producing reliable results with quantified uncertainties. The method is shown to be robust across a range of eco-epidemiological datasets, offering computational efficiency and reliable inference about the evolution dynamics.

ecology↗

ILORA: A database of alien vascular flora of India

1) Biological invasions pose an unprecedented threat to biodiversity and ecosystems at different spatial scales, especially for a biodiversity-rich developing nation like India. While country-level checklists of alien taxa are important, databases having their biological and ecological attributes are of paramount importance for facilitating research activities and developing policy interventions. Such a comprehensive database for alien flora is lacking in India. 2) We have curated data for 14 variables related to ecology, biogeography, introduction pathway, socio-economy and distribution of 1747 alien vascular plant species from 22 national and global sources to produce the Indian Alien Flora Information (ILORA) version 1.0 database. This paper describes the detailed methodology of curating these data along with the rationale behind selecting these variables. 3) The database, the first of its kind for the Indian alien flora, will provide easy access to high quality data and offer a ready reference to comprehend the existing scenario of alien plant species in the country. The database is dynamic and will be updated regularly. It has a provision to incorporate user submitted data, which will allow increasing the resolution of the database as well as the expansion of its capacity. 4) The database is envisaged to become a nationwide collaborative platform for a wide spectrum of stakeholders. It is freely accessible via an online data repository as well as through a dedicated website (https://ilora2020.wixsite.com/ilora2020).

ecology↗