Proposed approach (experimental / theoretical / computational)

In recent years, several methods emerged to analyze the organization of dense bacterial communities over flat, 2D substrates [Ref. 5]. However, these solutions are inefficient for studying most bacterial communities which organize in 3D. To address this problem, we propose to use Myxococcus fruiting bodies as a model system, which have the advantage of being well organized assemblies. We will image these structures by confocal microscopy. To reconstruct the bacteria order field, we will expand the capabilities of our in-house, supervised-deep-learning-based method [Refs 5,9]. To enhance the size of our training dataset, we propose to use simulations, following an established approach in the field. Following two recent works [Refs. 1,2], we propose to use CycleGAN (Generative Adversarial Networks) to generate realistic bacterial datasets (with spatial and temporal continuity) directly from simulations of ellipses interacting through Lennard-Jones potential, using the popular ya||a code [Ref. 4]. These simulations will also be helpful to test continuum active nematics models [Ref. 8,10]. Once our approach proves effective on the Myxococcus system, we will expand it to other ecologically-relevant bacterial communities, e.g. alcanivorax borkumensis [Ref. 8].