Abstract
Electrode-associated microbial biofilms are essential to the function of bioelectrochemical systems (BESs). These systems exist in a number of different configurations but all rely on electroactive microorganisms utilizing an electrode as either an electron acceptor or an electron donor to catalyze biological processes. Investigations of the structure and function of electrode associated biofilms are critical to further the understanding of how microbial communities are able to reduce and oxidize electrodes. The community structure of electrode-reducing biofilms is diverse and often dominated by Geobacter spp. whereas electrode-oxidizing biofilms are often dominated by other microorganisms. The application of a wide range of tools, such as high-throughput sequencing and metagenomic data analyses, provide insight into the structure and possible function of microbial communities on electrode surfaces. However, the development and application of techniques that monitor gene expression profiles in real-time are required for a more definite spatial and temporal understanding of the diversity and biological activities of these dynamic communities. This mini review summarizes the key gene expression techniques used in BESs research, which have led to a better understanding of population dynamics, cell cell communication and molecule-surface interactions in mixed and pure BES communities.
Original language | English |
---|---|
Article number | 663 |
Number of pages | 7 |
Journal | Frontiers in Microbiology |
Volume | 5 |
DOIs | |
Publication status | Published - Nov 2014 |
Externally published | Yes |
Bibliographical note
Copyright the Author(s) 2014. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- bioelectrochemical systems
- electricigens
- real-time gene expression
- biofilms
- Geobacter
- electrodes
- Electrodes
- Biofilms
- Bioelectrochemical systems
- Electricigens
- Real-time gene expression