Quantifying biofilm propagation on chemically modified surfaces.

Conditions affecting biofilm formation differ among bacterial species and this presents a challenge to studying biofilms in the lab. This work leverages functionalized silanes to control surface chemistry in the study of early biofilm propagation, quantified with a semi-automated image processing algorithm. These methods support the study of sp.

Application of electrochemical surface plasmon resonance (ESPR) to the study of electroactive microbial biofilms.

Electrochemical surface plasmon resonance (ESPR) monitors faradaic processes optically by the change in refractive index that occurs with a change in redox state at the electrode surface. Here we apply ESPR to investigate the anode-grown Geobacter sulfurreducens biofilm (GSB), a model system used to study electroactive microbial biofilms (EABFs) which perform electrochemical reactions using electrodes as metabolic electron acceptors or donors. A substantial body of evidence indicates that electron transfer reactions among hemes of c-type cytochromes (c-Cyt) play major roles in the extracellular electron transfer (EET) pathways that connect intracellular metabolic processes of cells in an EABF to the electrode surface.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of and H1-Type VI Secretion Interactions.

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of .

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform.

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial distribution and activities of community members. We have developed a microwell array platform that can be used to rapidly assemble and track thousands of bacterial communities in parallel. This protocol highlights the utility of the platform and describes its use for optically monitoring the development of simple, two-member communities within an ensemble of arrays within the platform.