Environment-Organism Feedbacks Drive Changes in Ecological Interactions.

Ecological interactions are foundational to our understanding of community composition and function. While interactions are known to change depending on the environmental context, it has generally been assumed that external environmental factors are responsible for driving these dependencies. Here, we derive a theoretical framework which instead focuses on how intrinsic environmental changes caused by the organisms themselves alter interaction values.

Two codependent routes lead to high-level MRSA.

Methicillin-resistant (MRSA), in which acquisition of [which encodes the cell wall peptidoglycan biosynthesis component penicillin-binding protein 2a (PBP2a)] confers resistance to β-lactam antibiotics, is of major clinical concern. We show that, in the presence of antibiotics, MRSA adopts an alternative mode of cell division and shows an altered peptidoglycan architecture at the division septum. PBP2a can replace the transpeptidase activity of the endogenous and essential PBP2 but not that of PBP1, which is responsible for the distinctive native septal peptidoglycan architecture.

Cell motility empowers bacterial contact weapons.

Many bacteria kill competitors using short-range weapons, such as the Type VI secretion system and contact dependent inhibition (CDI). Although these weapons can deliver powerful toxins, they rely on direct contact between attacker and target cells. We hypothesized that movement enables attackers to contact more targets and thus greatly empower their weapons.

Tracking bacteria at high density with FAST, the Feature-Assisted Segmenter/Tracker.

Most bacteria live attached to surfaces in densely-packed communities. While new experimental and imaging techniques are beginning to provide a window on the complex processes that play out in these communities, resolving the behaviour of individual cells through time and space remains a major challenge. Although a number of different software solutions have been developed to track microorganisms, these typically require users either to tune a large number of parameters or to groundtruth a large volume of imaging data to train a deep learning model-both manual processes which can be very time consuming for novel experiments.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes.

Droplet printing reveals the importance of micron-scale structure for bacterial ecology.

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array.

Controlled packing and single-droplet resolution of 3D-printed functional synthetic tissues.

3D-printing networks of droplets connected by interface bilayers are a powerful platform to build synthetic tissues in which functionality relies on precisely ordered structures. However, the structural precision and consistency in assembling these structures is currently limited, which restricts intricate designs and the complexity of functions performed by synthetic tissues. Here, we report that the equilibrium contact angle (θ) between a pair of droplets is a key parameter that dictates the tessellation and precise positioning of hundreds of picolitre-sized droplets within 3D-printed, multi-layer networks.