Probing phenotypic growth in expanding Bacillus subtilis biofilms View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-05

AUTHORS

Xiaoling Wang, Stephan A. Koehler, James N. Wilking, Naveen N. Sinha, Matthew T. Cabeen, Siddarth Srinivasan, Agnese Seminara, Shmuel Rubinstein, Qingping Sun, Michael P. Brenner, David A. Weitz

ABSTRACT

We develop an optical imaging technique for spatially and temporally tracking biofilm growth and the distribution of the main phenotypes of a Bacillus subtilis strain with a triple-fluorescent reporter for motility, matrix production, and sporulation. We develop a calibration procedure for determining the biofilm thickness from the transmission images, which is based on Beer-Lambert's law and involves cross-sectioning of biofilms. To obtain the phenotype distribution, we assume a linear relationship between the number of cells and their fluorescence and determine the best combination of calibration coefficients that matches the total number of cells for all three phenotypes and with the total number of cells from the transmission images. Based on this analysis, we resolve the composition of the biofilm in terms of motile, matrix-producing, sporulating cells and low-fluorescent materials which includes matrix and cells that are dead or have low fluorescent gene expression. We take advantage of the circular growth to make kymograph plots of all three phenotypes and the dominant phenotype in terms of radial distance and time. To visualize the nonlocal character of biofilm growth, we also make kymographs using the local colonization time. Our technique is suitable for real-time, noninvasive, quantitative studies of the growth and phenotype distribution of biofilms which are either exposed to different conditions such as biocides, nutrient depletion, dehydration, or waste accumulation. More... »

PAGES

4607-4615

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00253-016-7461-4

DOI

http://dx.doi.org/10.1007/s00253-016-7461-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029397609

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27003268


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00253-016-7461-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00253-016-7461-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00253-016-7461-4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00253-016-7461-4'


 

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299 School of Mechanical Engineering, University of Science and Technology Beijing, 100083, Beijing, China
300 rdf:type schema:Organization
301 https://www.grid.ac/institutes/grid.41891.35 schema:alternateName Montana State University
302 schema:name Department of Chemical and Biological Engineering, Montana State University, 59717-3920, Bozeman, MT, USA
303 School of Engineering and Applied Sciences, Harvard University, 02138, Cambridge, MA, USA
304 rdf:type schema:Organization
 




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