posted on 2021-06-16, 17:38authored byTianyang Deng, Damon DePaoli, Ludovick Bégin, Nan Jia, Leon Torres de Oliveira, Daniel C. Côté, Warwick F. Vincent, Jesse Greener
Microfluidic bioanalytical platforms
are driving discoveries from
synthetic biology to the health sciences. In this work, we present
a platform for <i>in vivo</i> live-cell imaging and automated
species detection in mixed cyanobacterial biofilms from cold climate
environments. Using a multimodal microscope with custom optics applied
to a chip with six parallel growth channels, we monitored biofilm
dynamics via continuous imaging at natural irradiance levels. Machine
learning algorithms were applied to the collected hyperspectral images
for automatic segmentation of mixed-species biofilms into individual
species of cyanobacteria with similar filamentous morphology. The
coupling of microfluidic technology with modern multimodal imaging
and computer vision systems provides a versatile platform for the
study of cause-and-effect scenarios of cyanobacterial biofilms, which
are important elements of many ecosystems, including lakes and rivers
of the polar regions.