Mookherjee, A. | bioRxiv Science

bioRxiv2026

AutoWrinkleID: a machine learning pipeline for biofilm wrinkle identification and quantitative analysis

Biofilms are widely distributed in both natural and engineered systems and play a fundamental role in microbial ecology and biotechnological applications. When grown on agar substrates, biofilms often exhibit macroscopic structural features due to mechanical instabilities driven by matrix production. These wrinkles encode relevant information about biofilm growth and structural development and have even been shown to possess some functional roles. Despite their relevance, currently available approaches for wrinkle detection from images rely on manual annotation, which is time-consuming, not scalable, and strongly dependent on the annotator. In the present study, we developed an end-to-end machine learning pipeline, named AutoWrinkleID, that starts from bright field images of biofilms and performs wrinkle identification, characterisation, and quantification across multiple bacterial species and strains. The name reflects the automated identification and subsequent characterisation and quantification of biofilm wrinkles. The annotations used to generate the masks, namely images containing only the wrinkle structures, were obtained both through manual labelling and using constitutive fluorescence and motility fluorescence. Interestingly, we found that models trained using only manual annotations perform worse than those trained using motility fluorescence markers. A comparison between motility and constitutive fluorescence masks further indicates that motility based annotations consistently outperform constitutive fluorescence across all strains, strongly suggesting that motile phenotypes are tightly associated with wrinkle structures. Additional computational analysis is conducted on the same dataset to assess the robustness and limitations of the results as a function of training dataset. We also observed that Sholl analysis, originally developed for the study of neuronal dendrites and later applied to wrinkle analysis, can effectively characterize wrinkle patterns, although its applicability is strongly limited by wrinkle shape and by the quality of the masks.

biophysics↗

bioRxiv2024

Electrogenic Dynamics of Biofilm Formation: Correlation Between Genetic Expression and Electrochemical Activity in Bacillus subtilis

Bacterial biofilms are structured microbial communities that play a big role in diverse processes such as nutrient cycling and bacterial pathogenesis. Biofilms are known for their electron transfer properties which are essential for metabolic processes, microbial survival, and maintaining redox balance. In this study, we investigated the electrogenic properties of Bacillus subtilis, a bacterial producer of electron-donating biofilms. Interdigitated gold electrodes were utilized to continuously measure the electrochemical activity of biofilm-forming B. subtilis cells as well as genetic mutants unable to create them (biofilm-deficient), over three days of growth. The formation of extracellular polymeric substances (EPS) and filamentous appendages was monitored via scanning electron microscopy (SEM). Chronoamperometry was used to assess electrochemical activity, which showed fluctuations in electrical current at specific time points in biofilm-forming cells. In contrast, biofilm-deficient cells showed no corresponding changes in current. Cyclic voltammetry (CV) revealed significant differences between the voltammograms of biofilm-forming and biofilm-deficient cells that were hypothesized to be a result of the reduction of secreted flavodoxin only in biofilm-forming cells. Electrochemical impedance spectroscopy (EIS) was also performed at various intervals and analyzed using an equivalent circuit model. We identified the presence of a charge transfer resistance (Rct) exclusively in biofilm-forming cells which correlated to the time of increased electrochemical activity measured using choronoamperometry. Finally, through confocal microscopy, we found that the expression of a gene involved in biofilm matrix formation, tasA, was correlated with the time where electrochemical charge transfer was measured. Altogether, these results indicate that electrochemical activity is primarily present in biofilm-forming cells rather than in biofilm-deficient mutants. By combining electrochemical and microscopic methods, a methodology was developed to continuously monitor the stages of biofilm formation through measurement of electrochemical activity, substantiating a correlation between the expression of biofilm genes and their electrochemical or redox activities. These data show that electrochemical activities within biofilms vary over time and there is a temporal relationship between these processes and the expression of genes responsible for biofilm development.

bioengineering↗