No abstract

The capacity for five Brettanomyces bruxellensis strains to form biofilm on stainless steel was confirmed, and the sanitation of these biofilms was tested using a solution of lactic acid and a reference method (a solution of foaming caustic soda and peroxide at 5 %). Different responses were observed depending on the strain: lactic acid solution induced a slight reduction in cell population, while the reference method resulted in the elimination of the adhered cells for three strains, but generated VBNC states for two others. The effects of sanitation on the biofilm formed is strain-dependent.

It is essential to discriminate between B. bruxellensis isolates at the strain level, because stress resistance capacities are strain dependent and also related to the genetic groups (GG). In this work, we investigated further the correlation between genetic groups and cell polymorphism by analysing optical microscopy images via deep learning. A Convolutional Neural Network (CNN) was trained to discriminate between 74 different B. bruxellensis isolates belonging to 4 of the 6 genetic groups described. Compared to the microsatellite analysis, the CNN enabled the prediction of the genetic groups of B. bruxellensis isolates with 96.6 % accuracy in a faster and cheaper way and with the same genetic group affiliations. Based on these very promising results, further research is needed to validate this technique for all genetic groups.

Ability to form biofilms is a potential resistance strategy, although it has not been much explored so far for the spoilage yeast Brettanomyces bruxellensis. The capacity of two strains to adhere and form biofilms on stainless steel chips in wine was studied. Using electronic microscopy, some particular structures, such as filamentous cells or chlamydospore-like structure, potentially involved in B. bruxellensis resistance were revealed. Some detachment phenomenon was identified and may be at the origin of the wine recurrent contamination.