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Microscopic organisms known as bacteria are found in virtually every environment on the planet. One reason bacteria are so successful is that they are able to form communities known as biofilms on surfaces in animals and other living things, as well as on rocks and other features in the environment. These biofilms protect the bacteria from fluctuations in the environment and toxins. For over 30 years, a class of enzymes called the GGDEF enzymes were thought to make a single signal known as cyclic di-GMP that regulates the formation of biofilms. However, in 2016, a team of researchers reported that some GGDEF enzymes, including one from a bacterium called Geobacter sulfurreducens, were also able to produce two other signals known as cGAMP and cyclic di-AMP. The experiments involved making the enzymes and testing their activity outside the cell. Therefore, it remained unclear whether these enzymes (dubbed ‘Hypr’ GGDEF enzymes) actually produce all three signals inside cells and play a role in forming bacterial biofilms. G. sulfurreducens is unusual because it is able to grow on metallic minerals or electrodes to generate electrical energy. As part of a community of microorganisms, they help break down pollutants in contaminated areas and can generate electricity from wastewater. Now, Hallberg, Chan et al. – including many of the researchers involved in the 2016 work – combined several experimental and mathematical approaches to study the Hypr GGDEF enzymes in G. sulfurreducens. The experiments show that the Hypr GGDEF enzymes produced cGAMP, but not the other two signals, inside the cells. This cGAMP regulated the ability of G. sulfurreducens to grow by extracting electrical energy from the metallic minerals, which appears to be a new, biofilm-less lifestyle. Further experiments revealed how Hypr GGDEF enzymes have evolved to preferentially make cGAMP over the other two signals. Together, these findings demonstrate that enzymes with the ability to make several different signals, are capable of generating specific responses in bacterial cells. By understanding how bacteria make decisions, it may be possible to change their behaviors. The findings of Hallberg, Chan et al. help to identify the signaling pathways involved in this decision-making and provide new tools to study them in the future.
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Current and Emerging Tools of Computational Biology To Improve the Detoxification of Mycotoxins
ABSTRACT Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we focus on mycotoxins—fungus-produced toxins that contaminate food and feed—and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.
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- Award ID(s):
- 2103545
- PAR ID:
- 10340888
- Editor(s):
- Zhou, Ning-Yi
- Date Published:
- Journal Name:
- Applied and Environmental Microbiology
- Volume:
- 88
- Issue:
- 3
- ISSN:
- 0099-2240
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1128/aem.02102-21
