Team:TU Dresden/Measurement
Abstract
In bacteria, protein secretion is mainly orchestrated by the Sec Pathway via Signal Peptides (SP), which are located at the N-terminus of secreted proteins. The secretion efficiency is not determined by the sequence of the SP alone, but instead is the combined result of an SP with its specific target protein. This necessitates establishing efficient screening procedures to evaluate all possible SP/target protein combinations. We developed such an approach for our Signal Peptide Toolbox, which contains 74 Sec-dependent SPs. It combines combinatorial construction with highly reproducible, quantitative measurements. By applying this procedure, we demonstrate the secretion of three different proteins and succeeded in identifying the most potent SP-protein combination for each of them. This thoroughly evaluated measurement tool, in combination with our SP toolbox (fully available via the partsregistry) enables an organism-independent, straightforward approach to identifying the best combination of SP with any protein of interest.
Background
Over the course of the last decades the quality, amount and spectrum of heterologous (and recombinant) proteins has drastically increased and therefore the need for techniques to easily express and purify these proteins has emerged. We find such proteins as ingredients of detergents (proteases), medical treatments (insulin) or food and beverage products (amylases). Simply put, heterologous proteins are ubiquitously present. [1]
In order to tackle this demand we chose to apply the genetic tools of the model organism Bacillus subtilis. It is already one of the most frequently used hosts for overproduction of proteins throughout academia and industry because of its tremendous capacity to secret proteins, which can be exploited to increase the overall yields.
B. subtilis has four different secretion pathways, however the majority of proteins are being secreted via the general Sec pathway (Figure 1). This pathway has been identified playing a crucial role in protein secretion as common element among all domains of life [2]. In the Sec pathway, the secretion of proteins into the surrounding supernatant is orchestrated by signal peptides (SP). These SPs are composed of approximately 60 to 180 nucleotides and they are located upstream of the protein to be secreted. Intracellularly, the SP is translationally fused to the specific protein but cut off during the membrane translocation process releasing the protein into the supernatant without the signal peptide attached to it. [3]
Up to date, approximately 170 SPs belonging to the Sec pathway of B. subtilis have been annotated but unfortunately, no correlations on sequence levels have been identified that link efficient protein secretion with a distinct SP. [4]
As part of our project EncaBcillus, we aimed at creating a platform for heterologous protein overexpression combined with their efficient secretion without releasing any cells into the environment. Hereby, we encapsulated our model organism B. subtilis in the Peptidosomes which serve as a new innovative method to keep the producing bacteria separated from the desired compounds. (For more details see Peptidosomes.)
To address the vision of creating this new platform, we first wanted to establish a fast and easy screening procedure to evaluate all combinational possibilities of each SP with a protein of interest (POI) – The Signal Peptide Toolbox.
As SPs of B. subtilis have been successfully adapted to GRAM-positive [5] and GRAM-negative bacteria [6], the Signal Peptide Toolbox, as an organism-independent genetic measurement tool, can be applied to any bacterial host. Every future iGEM team will be able to use this fully partsregistry availabe tool to increase their protein secretion.
Design
Bacillus subtilis contains approximately 170 Sec Signal Peptides (SPs) that re-direct proteins for secretion via the Sec pathway. For our toolbox we were able to clone 74 Sex SPs (Table 1). Each SP was amplified from genomic DNA of B. subtilis wild type with the primers found in the primer collection table at the end of the Design section. After amplification, each SP was digested using the restriction enzymes EcoRI and PstI, stored into the pSB1C3 backbone and submitted to the partsregistry.
This powerful collection of SPs can now be combined with our Evaluation Vector and any protein of interest (POI) for a shotgun cloning approach to identify the best combination of SP and POI.
Though having access to these SPs via the registry, does not solve the problem of having to create one clone for each single SP and POI. This also means, sufficient amounts of each SP are necessary tu guarantee efficient cloning. Thus, we followed up on the idea of multi-template PCR: since all SPs are stored in the pSB1C3 vector and flanked by the same pre- and suffix sequences, we should be able to amplify all SPs via PCR an easy, quick and cheap method while using the BioBrick pre- and suffix as primers.
To cope with this issue of having 74 SPs, we decided to break down the 74 SP into Signal Peptide Mixes (SPM), each consisting of maximal 20 SP (Table 2). We have carefully evaluated the maximal number of SPs within each mix to increase the robustness of the PCR (see the Results section for more details). Followed by the amplification of all SPM subsets, they can be easily purified and applied in a shotgun ligation approach with your protein of interest and the EV.
Detailed methods can be found in our protocol collection section. All primers used can be found in our primer collection table down below.
Results
Amplification of the Signal Peptide Mixes via optimized multi-template PCR
So far, no direct correlation between the perfect combination of signal peptide and downstream sequence to gain optimal secretion levels is known. Thus, the problem of having to create one clone per combination of SP and protein of interest remains. Therefore, we created the so-called Signal Peptide Mixes (SPMs), a set of libraries with each containing equal concentrations of up to twenty distinct SPs which can be easily enriched via multi-template PCR. The amplified SPs can then be combined with our Signal Peptide Evaluation Vector (SP-EV) and the gene of interest (For more details see the protocol in the end of the Results section).
In a first approach, we evaluated the multi-template PCR by varying the number of different SPs in one mix. Our aim was to amplify all SPs equally for the downstream cloning procedures. To test this, a SPM subset containing 53 SPs, was amplified using the RFC10 prefix and suffix as primers, we expected a band at around 100-200 Bp (size range of the SPs). Unfortunately, we also observed a second dominant band (at about 250 Bp) (Figure 2, A), leading to the conclusion that a subset of 53 SPs was not suitable for our purposes.
Form this we decided to reduce the number of different SPs to 20 and also to increase the primer concentrations. These improvements lead to a specific amplification of our SPs (Figure 2, B). To evaluate, if all 20 SPs were indeed amplified, we conducted a second PCR using the first PCR as template with specific primers for each SP of the original SPM. We could show that all 20 distinct SPs of the SPM subset were amplified during the first PCR (Figure 3). Therefore, we decided to split up all provided SPs into subset-mixes of each containing up to 20 SPs max.
All 74 SPs which we do provide were therefore aliquoted to 0.5 ng/μL and assigned to four distinct SPM subsets. The table below gives an overview about the assignment of the SPs.
Cloning with the Signal Peptide-Evaluation Vector
Following the evaluation of the multi-template PCR amplification of the SPs, we established a Standard Operating Procedure (SOP) protocol for cloning with the Signal Peptide-Evaluation Vector (SP-EV). This SOP was tailored to explain the random integration of the SPs using the cloning host E. coli as the EV was evaluated in the course of our Signal Peptide Toolbox.
First, as we did not exchange the xylose-inducible promoter PxylA, we inserted the gene amyE for our protein of interest alpha-Amylase via cutting both, the EV and the amyE using the restriction enzymes NgoMIV and PstI. Next, we amplified all SPM subsets (Table 2) via standard PCR using the RFC10 prefix as forward primer (TM4487) and RFC10 suffix as reverse primer (iG17P039). (Both primers can be found in the primer collection table in the Design section.) The PCR products were then digested using the restriction enzymes XbaI and AgeI. Following that, we digested the new EVamyE using the restriction enzymes BsaI leaving an XbaI overhang and NgoMIV. In a last step, we fused the digested EVamyE with the digested SPM subsets, thus setting up four ligation reactions called EVSP-amyE a, b, c and d. These, we used for transformation into B. subtilis.
The detailed SOP protocols for working with the Evaluation Vector and the Signal Peptide Toolbox can be found down below at the end of the Results section "High throughput screening procedure for B. subtilis". The Gif (Figure 4) above summarizes graphically the steps neccessary to set up your individual SP-EV.
High throughput screening procedure for B. subtilis
After various adjustments to improve the applicability of the Signal Peptide Toolbox, we developed a high throughput screening procedure tailored to fit our model organism B. subtilis and proceeded to identify the most potent SPs for highest secretion of B. subtilis' alpha-Amylase.
As we performed our transformation into a starch degradation-deficient B. subtilis strain (TMB3547) where the gene amyE was disrupted by the insertion of Pveg-LacZ. This strain, still contains the necessary flanking regions for homologues recombination of the pBS1C vector. Thus, positive integration of the pBS1C-SPM-amyE construct lead to white colonies. (Figure 5, A)
We picked 92 colonies from each transformation, EVSP-amyE a, b, c and d and transfered each pick to both, a starch containing screening agar plate and a second backup agar plate which was spiked with cloramphenicol. Though, as we chose to carry along a negative control (TMB3547) and a positive control (W168) on each screening and backup agar plate, we used a screening agar plate containing no antibiotics.
Following incubation, we poured Lugol’s Iodine solution over the screening agar plates. Usually, as the EV and SP-EV integrate both into the amyE locus of B. subtilis, the resulting disruption of the native gene would lead to a loss of the enzymatic activity. Therefore, successfully transformed colonies would not be able to degrade starch and would thereby show no brightened zone of degradation. But as we performed our transformation into a starch degradation-deficient B. subtilis strain, successfully transformed colonies were again able to degrade starch. Thereby, a brightened zone of degradation on the screening agar plate indicated promising colonies (Figure 5, B). The position of successfully transformed colonies was then marked on the backup agar plates (Figure 5, C).
Sparing the outer lines of two 96 well plates which we filled with water to prevent evaporation, we charged the remaining 60 wells with 100 μl of 2xYT medium. As we chose to carry along two negative controls (TMB3547), three positive controls (W168) and three blanks on both 96 well plates, we could pick 114 colonies from the backup plates in total. We transferred them to the 96 well plates and incubated the B. subtilis cultures for 8 hours at 37°C with 220 rpm using the plate reader.
After the first 8 hours of incubation, we set up two new 96 well plates filled acordingly to the previous two 96 well plates but instead of 100 μl of 2xYT medium we poured 200 μl of 2xYT medium with a final concentration of 1% xylose into the 60 inner wells of the two new 96 well plates to induce the promoter PxylA. Then, we transfered 4 μl of bacteria culture from the previous two 96 well plates to the new plates and incubated the B. subtilis cultures for 16 hours at 37°C with 220 rpm using the plate reader, too.
Before separating the supernatant from the cells via centrifuging the 96 well plates, we measured the OD600 to normalize our data in the end. Following that, we applied a microplate reader based starch hydrolysis assay [8] and normalized the generated data over the OD600 values to identify the most potent combinations of SPs and B. subtilis’ alpha-Amylase of each SPM subset (Figure 6).
Finally, we set up liquid cultures of a range of promising colonies from the backup plate and amplified the genetic region of interest via standard PCR using the primers TM4487 and iG17P058. The resulting fragments were sequenced, thus identifying the most potent SPs for alpha-Amylase (Figure 7).
The shown data indicates that further experimentation would be neccessary to evaluate the role of the promoter PxylA in comparison to the native promoter of amyE. An amyE knockout strain where the native amyE had been replaced with PxylA‑SPAmyE‑amyE would be a suitable positive control. Nonetheless, we could clearly identify the most potent SP‑amyE combinations for our case.
The detailed SOP protocols for working with the Evaluation Vector and the Signal Peptide Toolbox can be found down below. The protocol selection explains the use of the Evaluation Vector, the Signal Peptide-Evaluation Vector and the high throughput screening procedure for B. subtilis. The latter two are provided with well documented examples, too.
However, we further proved the applicability of the Signal Peptide Toolbox by evaluating two more proteins accordingly: sfGFP and mCherry.
SOP protocols for working with the Evaluation Vector and the Signal Peptide Toolbox
Identification of the most potent Signal Peptides for sfGFP and mCherry
Both, the screening procedure for identifying the best SPs for highest secretion of sfGFP and the screening of mCherry were conducted as stated in the detailed SOP protocols for working with the Evaluation Vector and the Signal Peptide Toolbox above.
For sfGFP, we applied a microplate reader based fluorescence assay where we performed an endpoint measurement at wavelengths set to 480 nm for excitation and 510 nm emission and normalized the generated data via the clones' OD600 values to identify the most potent combinations of SPs and sfGFP. For mCherry, we performed a second microplate reader based fluorescence assay, an endpoint measurement at wavelengths set to 585 nm for excitation and 615 nm for emission. The data was normalized over the clones' OD600 values. In a final step, we identified the most potent SP‑sfGFP and SP‑mCherry combinations via sequencing (Figure 8, 9).
Conclusion
Our team developed and proved the applicability of a powerful toolbox to quickly screen via a high throughput procedure for improved secretion of proteins in bacteria - the Signal Peptide Toolbox. Although, we could not test the system in Peptidosomes yet, we are very much sure that the vision to facilitate Peptidosomes as protein production platform can be achieved. The promising combination of increased protein secretion and physical separation of production host and product should be studied further.
References
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