Tâm Mignot has given an interview for the CNRS Journal about MiSiC, the first tool capable of automatically analyzing images of bacterial biofilms found in our mouths, in hospitals or in the soil.
A team from Marseille has just developed MiSiC, the first tool capable of automatically analyzing images of bacterial biofilms found in our mouths, in hospitals or in the soil. Explanations with one of its promoters, biologist Tâm Mignot.
Can you remind us what a bacterial biofilm is?
Tâm Mignot. It is an assembly of several hundreds to several millions of bacteria, belonging to one or several species, which adhere to a surface and to each other via the secretion of natural polymers called “exopolysaccharides”. This type of structure exists everywhere: in nature (in soils, oceans, on plants, on animals…), in industry (for example on oil refinery filters or ship hulls) or in hospitals (on injection equipment such as catheters, or on prostheses or wounds). Plaque is a bacterial biofilm that forms on the surface of teeth and is responsible for periodontal disease (x2000 magnification with a scanning electron microscope).
What are the benefits of studying them?
T. M. Knowing more about bacterial biofilms is crucial not only for basic research, but also for applied research, including medical, agronomic and environmental research. With regard to the former, one of its objectives is to refine our knowledge of the cellular and molecular processes through which biofilms form and dissolve. Until a few decades ago, the focus was on the study of individual bacteria in culture. However, the examination of biofilms in nature has revealed that up to 80% of the micro-organisms on our planet live in this form and not in isolation…
What about the importance of studying them in applied research?
T. M. At the medical level, the analysis of molecules involved in the dissolution of bacterial biofilms could lead to new and more effective antimicrobial treatments against pathogens developing in hospitals. On the environmental side, research on these structures could help promote the formation of biofilms that are beneficial to nature, some of which are capable of fixing or degrading certain pollutants (heavy metals, hydrocarbons, etc.) or carbon dioxide from the air. Finally, in the agronomic field, a detailed understanding of the processes of formation of biofilms could make it possible to stimulate their development at the level of the roots of the plants: indeed, some of them can optimize the growth of the plants by supporting the fixation of the nitrogen of the ground in their roots.
What exactly is MiSiC?
T. M. It is a microscopic image analysis software that allows the study of the structure of a dense microbial community, in other words a bacterial biofilm; MiSiC is the abbreviation of “Microbial Segmentation in dense Colonies”. More precisely, our system can distinguish the different species of a bacterial biofilm and count the number of bacteria of each of these species. It is freely downloadable and installable under the Napari image analysis interface, and is intended for all researchers who study bacteria in colonies or biofilms – provided that the latter are in two dimensions, i.e. flat; not in 3D, with stacked cells.
What does this tool add to those already available?
T. M. As we have shown in work published in September 20212, MiSiC is compatible with not just one but all types of microscopic images: in “phase contrast” – where cells appear in black on a light background -, in “fluorescence” – where cells fluoresce on a black background -, and in “bright field” mode – where cells shine on a black background. Secondly, it is applicable to a large number of bacterial species; and in case of biofilms made of several species, it allows to distinguish them via different colors. But above all, MiSiC makes it possible to reliably count millions of bacteria in a community, whereas it was difficult to count even a thousand under these conditions. This will accelerate research on bacterial biofilms.
How does it work?
T. M. By searching the microscopic image analyzed for all objects with a rounded rod shape at the ends. Indeed, during the development of this system, Swapnesh Panigrahi, an expert in artificial intelligence in our team, and Leon Espinosa, a specialist in analysis for microbiology, had the stroke of genius to understand that.