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Extracytoplasmic Function (ECF) Sigma Factors: From Regulatory Specificity to Synthetic Switches

Final Report Summary - SYNTHETIC ECFDEVICES (Extracytoplasmic Function (ECF) Sigma Factors: From Regulatory Specificity to Synthetic Switches)

For many years, we have been exploiting bacteria for the production of compounds that have industrial, economical, or medical relevance; that is the case of vitamins, fine chemicals and enzymes. Traditionally, optimization of the production capacity of bacteria, in regard to the compound of interest, relies mostly on the optimization of growth conditions and only afterwards on the introduction of small modifications on the DNA level; these could, for example, increase the expression of the enzyme of interest. With the fast and broad development of systems and synthetic biology over the last few decades, we are now (theoretically) able to do extensive genetic alterations in bacteria in order to tightly control their behaviour. Systems biology greatly expanded our knowledge on global cellular processes and allowed us to computationally model and test our hypotheses as well as guide our experimental approaches to achieve a given goal. At the same time, synthetic biology actively contributes to the expansion of the available tools to genetically alter the organisms and provide us with comprehensive knowledge on the laws governing basic biological processes, i.e. what is biologically possible and what is not. While the potential is there, the truth is that there is still much to do. Of particular interest to us is that most of the efforts on the development of well evaluated genetic tools is currently focused on Escherichia coli, a model organism of excellence with some relevance for industrial scale processing, while for the biotechnological workhorse Bacillus subtilis, the available genetic toolbox is far from comprehensive.
Bacteria live in fluctuating environments and are required to interact with other organisms with which they share space or resources. In order to adjust their behaviour accordingly to current situations, they need to continuously monitor their surroundings, integrate and process the information they just collected and initiate an appropriate response. This response is usually initiated at the level of control of gene expression, i.e. by turning on or off the expression of a specific subset of genes. Bacteria employ diverse mechanisms to control gene expression and one of the most widespread is the use of alternative sigma factors. These constitute a pool of alternative subunits of the DNA-directed RNA polymerase, the enzyme responsible for the transcription of DNA into RNA that is present in all bacteria. While the core of the RNA polymerase is invariable, the sigma factors can be exchanged. This results in an alteration of RNA polymerase specificity, which becomes then able to recognize different promoters and so, transcribe different genes.
All bacteria have one housekeeping sigma factor, which is responsible for transcription of all genes necessary for growth under regular conditions. Additionally, most bacteria possess alternative sigma factors that come into play at more specific situations, e.g. stress conditions and differentiation processes. Up to now, four groups of sigma factors have been defined: group 1 contains the essential housekeeping sigma factors; group 2 contains the non essential homologs of the housekeeping sigma factors; group 3 contains sigma factors involved in specific behaviours such as differentiation and motility; and group 4 contains the extracytoplasmic function sigma factors (ECFs) that are most frequently involved in resistance to stress conditions. These four groups not only differ in their specific functions but also by the architecture of the proteins. While sigma factors of groups 1 and 2 contain four conserved regions or domains, sigma factors of group 3 only contain three of those regions while ECFs represent the most minimalistic set, containing only two of those regions that are sufficient to mediate both DNA binding and interaction with the RNA polymerase core enzyme.
The main objective of this project was to apply ECFs to implement novel genetic tools, and in this way actively contribute to the expansion of the available genetic toolbox for manipulation of B. subtilis. The advantage of using ECFs as tools to control gene expression is three-fold: first, the sigma factor concept is present in all bacteria supporting their general applicability; second, they are highly diverse in terms of how they are activated and the promoter sequences they recognize, which greatly increases the possibilities of implementation of orthogonal genetic switches, i.e. non native elements that can turn transcription on and off and have minimal influence in the metabolism of the host cell; and third, the fact that they are the smallest sigma factors makes them (potentially) easier to engineer.
During the course of this project we have been able to expand the already established ECF classification by systematically analysing genomes of Actinobacteria, a phylogenetic group of bacteria that is particularly rich in ECFs and include important antibiotic producers. We have defined 21 new ECF groups that diverge from the ones already described in their putative functions, the mechanisms by which they are activated and the promoter sequences they recognize. Based on this and previous work, we have generated a desk reference that summarizes the function, mechanism of activation and target promoter sequences of each of the currently defined 94 ECF groups, which is now publically available as a book chapter. Together, these analyses not only expand our fundamental knowledge on ECFs but also provide the scientific community with hypotheses that can be experimentally investigated and new sigma factor groups to explore as genetic switches for synthetic biology purposes.
Building on the vast wealth of information collected through the bioinformatics analysis, we have selected ECF-encoding genes and cognate target promoters and attempted their implementation as novel genetic switches in B. subtilis. These ECFs are derived from three distinct phylogenetic groups: Firmicutes, the group to which B. subtilis belongs; Actinobacteria; and Proteobacteria. The data we collected unravelled a previously unknown limitation: only ECFs from closely related organisms, in our case only those from Firmicutes, can be implemented into B. subtilis without further manipulation. This information highlights that there are still unknown organism specific traits that prevent implementation of ECFs coming from phylogenetically distant organisms. The reason behind this discrimination will require further investigations.
Once ECF-based switches were implemented into B. subtilis, we moved into the characterization of their behaviour as well as how such behaviour could be altered. We studied the effect of: (i) increasing the copy number of the ECF-coding genes as well as of their target promoters; (ii) changing the inducible promoter (i.e. a promoter from which transcription is only possible in the presence of a given inducer compound) driving the expression of the ECF; (iii) making truncations of the ECF protein; (iv) altering the ECF protein stability; (v) altering the size of the DNA fragment containing the ECF target promoter; and (vi) introducing counter-transcriptional control elements. Through this comprehensive study we were able to generate a collection of ECF-based switches that show different dynamic ranges (i.e. that allow for distinct degrees of variation between the off and on states) and that allow for a gradual increase in transcription that correlates with the concentration of the inducer or that, alternatively, show a sharp change from the off to the on state at a given inducer concentration. Additionally, we have generated switches that upon removal of the inducer turn off transcription at different speed. Altogether, this collection of switches can be readily applied to B. subtilis, by the scientific community or by the industry, to implement different gene expression behaviours that might be necessary for successful integration in more or less complex networks.
Finally, in order to demonstrate that these ECF based genetic switches can be used to build more complex behaviours and that they can be integrated into more complex devices, we used three of them to develop genetic timers that would generate an adjustable time delay between addition of inducer to a bacterial culture and the expression of the protein of interest. To meet this goal, we built ECF cascades with one, two or three ECFs and were able to generate time delays that varied from 20 minutes to 1 hour.
In summary, the results obtained through the development of the Synthetic ECFdevices project provided the scientific community with state of the art knowledge on ECF groups, showed that ECF-based genetic switches can be implemented into B. subtilis only if originating from closely related organisms, generated a collection of ECF-based switches with different dynamic behaviour, and benchmarked their potential to establish more complex devices. Altogether, we highlighted the usefulness of ECFs in synthetic biology and push them to a prominent position as tools for the control of gene expression.