Biology subjects

Dasgupta, S.

Publications and source records attributed to Dasgupta, S..

3 recordsLinked to original sources

bioRxiv2018

Physics of lumen growth

We model the dynamics of formation of intercellular secretory lumens. Using conservation laws, we quantitatively study the balance between paracellular leaks and the build-up of osmotic pressure in the lumen. Our model predicts a critical pumping threshold to expand stable lumens. Consistently with experimental observations in bile canaliculi, the model also describes a transition between a monotonous and oscillatory regime during luminogenesis as a function of ion and water transport parameters. We finally discuss the possible importance of regulation of paracellular leaks in intercellular tubulogenesis.

biophysics↗

bioRxiv2018

Extensive genomic diversity among Mycobacterium marinum strains revealed by whole genome sequencing

Mycobacterium marinum is the causative agent for the tuberculosis-like disease mycobacteriosis in fish and skin lesions in humans. Ubiquitous in its geographical distribution, M. marinum is known to occupy diverse fish as hosts. However, information about its genomic diversity is limited. Here, we provide the genome sequences for 15 M. marinum strains isolated from infected humans and fish. Comparative genomic analysis of these and four available genomes of the M. marinum strains M, E11, MB2 and Europe reveal high genomic diversity among the strains, leading to the conclusion that M. marinum should be divided into two different clusters, the \"M\"- and the \"Aronson\"-type. We suggest that these two clusters should be considered, if not two separate species, at least two M. marinum subspecies. Our data also show that the M. marinum pan-genome for both groups is open and expanding and we provide data showing high number of mutational hotspots in M. marinum relative to other mycobacteria such as Mycobacterium tuberculosis. This high genomic diversity might be related to that M. marinum occupy different ecological niches.

genomics↗

bioRxiv2017

A neural algorithm for a fundamental computing problem

Similarity search, such as identifying similar images in a database or similar documents on the Web, is a fundamental computing problem faced by many large-scale information retrieval systems. We discovered that the flys olfac-tory circuit solves this problem using a novel variant of a traditional computer science algorithm (called locality-sensitive hashing). The flys circuit assigns similar neural activity patterns to similar input stimuli (odors), so that behav-iors learned from one odor can be applied when a similar odor is experienced. The flys algorithm, however, uses three new computational ingredients that depart from traditional approaches. We show that these ingredients can be translated to improve the performance of similarity search compared to tra-ditional algorithms when evaluated on several benchmark datasets. Overall, this perspective helps illuminate the logic supporting an important sensory function (olfaction), and it provides a conceptually new algorithm for solving a fundamental computational problem.

neuroscience↗