In natural environments bacterial communities consist of several distinct species increasing the complexity of the underlying interactions. Furthermore, these interactions can result in emergent properties like increased degradation, optimized productivity and growth. I am especially interested in characterizing bacterial evolution in multi-species communities so we can understand the driving mechanisms behind the ability to form complex communities, particular in biofilms, and how this affects the interactions and fitness.

Living materials are bio-hybrid structures that are composed of biological living cells (either non-engineered or genetically engineered) housed within a non-living synthetic matrix. 3D printing has been shown to be an effective technology for the fabrication of living materials with controlled shapes and sizes. Customized living materials from nano- to macroscales can be 3D printed with high resolution into spatially defined patterns. The living cells in these materials endow them with novel functionalities such as sense-and-respond, energy production, production of high-value compounds, detoxification of harmful compounds, or self-healing capacities, among others.

Biological systems rely on the DNA – RNA – protein information transfer paradigm that determines the phenotype of an organism. Biologists have analyzed these “omes” for years in the form of genomics, transcriptomics and proteomics. In addition to these, epigenomics and metabolomics have recently been used to answer specific questions relating to the many functions of an organism. Given the year on year advances in “omics” technologies, the volume of information that can be gathered in individual studies is expanding rapidly. Furthermore, the current high throughput nature of these techniques has increased accessibility to this information in terms of time and cost. This has placed many researchers in a situation where they can collect several omics data sets on the same experimental samples. In order to draw more comprehensive conclusions on biological processes these data sets must be integrated and analyzed as a holistic system.

Bacterial evolution of antibiotic resistance presents a formidable challenge for public health. As discovery of new antibiotic classes has slowed down, an important question is how best to use existing antibiotics. Can we dose these drugs in a way that is clinically effective, but avoids evolution of resistance?