bioRxiv Science⌕ Search

Biology subjects

Camadro, J.-M.

Publications and source records attributed to Camadro, J.-M..

2 recordsLinked to original sources
bioRxiv2021

Insight in the quorum sensing-driven lifestyle of the non-pathogenic Agrobacterium tumefaciens 6N2 and the interactions with the yeast Meyerozyma guilliermondii

Agrobacterium tumefaciens is considered a prominent phytopathogen, though most isolates are nonpathogenic. Agrobacteria can inhabit plant tissues interacting with other microorganisms. Yeasts are likewise part of these communities. We analyzed the quorum sensing (QS) systems of A. tumefaciens strain 6N2, and its relevance for the interaction with the yeast Meyerozyma guilliermondii, both sugarcane endophytes. We show that strain 6N2 is nonpathogenic, produces OHC8-HSL, OHC10-HSL, OC12-HSL and OHC12-HSL as QS signals, and possesses a complex QS architecture, with one truncated, two complete systems, and three additional QS-signal receptors. A proteomic approach showed differences in QS-regulated proteins between pure (64 proteins) and dual (33 proteins) cultures. Seven proteins were consistently regulated by quorum sensing in pure and dual cultures. M. guilliermondii proteins influenced by QS activity were also evaluated. Several up- and down- regulated proteins differed depending on the bacterial QS. These results show the importance of the QS regulation in the bacteria-yeast interactions. HighlightsThe avirulent A. tumefaciens 6N2 has two replicons and a complex QS architecture The profile of QS-regulated proteins is modified in dual cultures with Pa. laurentii The bacterial QS activity alters the proteome of the yeast Pa. laurentii

microbiology↗
bioRxiv2018

Pixel: a digital lab assistant to integrate biological data in multi-omics projects

BackgroundIn biology, high-throughput experimental technologies, also referred as "omics" technologies, are increasingly used in research laboratories. Several thousands of gene expression measurements can be obtained in a single experiment. Researchers are routinely facing the challenge to annotate, store, explore and mine all the biological information they have at their disposal. We present here the Pixel web application (Pixel Web App), an original content management platform to help people involved in a multi-omics biological project. MethodsThe Pixel Web App is built with open source technologies and hosted on the collaborative development platform GitHub (https://github.com/Candihub/pixel). It is written in Python using the Django framework and stores all the data in a PostgreSQL database. It is developed in the open and licensed under the BSD 3-clause license. The Pixel Web App is also heavily tested with both unit and functional tests, a strong code coverage and continuous integration provided by CircleCI. To ease the development and the deployment of the Pixel Web App, Docker and Docker Compose are used to bundle the application as well as its dependencies. ResultsThe Pixel Web App offers researchers an intuitive way to annotate, store, explore and mine their multi-omics results. It can be installed on a personal computer or on a server to fit the needs of many users. In addition, anyone can enhance the application to better suit their needs, either by contributing directly on GitHub (encouraged) or by extending Pixel on their own. The Pixel Web App does not provide any computational programs to analyze the data. Still, it helps to rapidly explore and mine existing results and holds a strategic position in the management of research data.

bioinformatics↗