Search bioRxiv⌕ Search

Biology subjects

Krishnamurthy, A.

Publications and source records attributed to Krishnamurthy, A..

3 recordsLinked to original sources

Distinct contact guidance mechanisms in single endothelial cells and in monolayers

In many tissues, cell shape and orientation are controlled by a combination of internal and external biophysical cues. Anisotropic substrate topography is a ubiquitous cue that leads to cellular elongation and alignment, a process termed contact guidance, whose underlying mechanisms remain incompletely understood. Additionally, whether contact guidance responses are similar in single cells and in cellular monolayers is unknown. Here, we address these questions in vascular endothelial cells (ECs) that in vivo form a monolayer that lines blood vessels. Culturing single ECs on microgrooved substrates that constitute an idealized mimic of anisotropic basement membrane topography elicits a strong, groove depth-dependent contact guidance response. Interestingly, this response is greatly attenuated in confluent monolayers. While contact guidance in single cells is principally driven by persistence bias of cell protrusions in the direction of the grooves and is surprisingly insensitive to actin stress fiber disruption, cell shape and alignment in dense EC monolayers are driven by the organization of the basement membrane secreted by the cells, which leads to a loss of interaction with the microgrooves. The findings of distinct contact guidance mechanisms in single ECs and in EC monolayers promise to inform strategies aimed at designing topographically patterned endovascular devices.

cell biology↗

Dug: A Semantic Search Engine Leveraging Peer-Reviewed Literature to Span Biomedical Data Repositories

MotivationAs the number of public data resources continues to proliferate, identifying relevant datasets across heterogenous repositories is becoming critical to answering scientific questions. To help researchers navigate this data landscape, we developed Dug: a semantic search tool for biomedical datasets utilizing evidence-based relationships from curated knowledge graphs to find relevant datasets and explain why those results are returned. ResultsDeveloped through the National Heart, Lung, and Blood Institutes (NHLBI) BioData Catalyst ecosystem, Dug has indexed more than 15,911 study variables from public datasets. On a manually curated search dataset, Dugs total recall (total relevant results/total results) of 0.79 outperformed default Elasticsearchs total recall of 0.76. When using synonyms or related concepts as search queries, Dug (0.36) far outperformed Elasticsearch (0.14) in terms of total recall with no significant loss in the precision of its top results. Availability and ImplementationDug is freely available at https://github.com/helxplatform/dug. An example Dug deployment is also available for use at https://search.biodatacatalyst.renci.org/. Contactawaldrop@rti.org or scox@renci.org

bioinformatics↗

NuMorph: tools for cellular phenotyping in tissue cleared whole brain images

Tissue clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here we introduce NuMorph, a group of image analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after tissue clearing and imaging by a conventional light-sheet microscope. We applied NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) conditional knockout model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) conditional knockout model with a more subtle brain overgrowth phenotype. In each case, we identified differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of 3D whole brain imaging approaches and the tools are widely applicable for studying 3D structural deficits of the brain at cellular resolution in animal models of neuropsychiatric disorders.

neuroscience↗