Team:MADRID UCM/Aptamer Characterization

Jorge-Aptamer Characterization – iGem Madrid

APTAMER CHARACTERIZATION

In this section, we explain how we have developed and adapted a cell-ELONA experiment to automatization in OT-2. This method allow us to know if aptamers selected by cell-SELEX has high affinity for its target and work correctly.

1 Why ELONA?

This year we have been working on developing aptamers that can detect whole cells in vivo. To face this challenge, taking advantage of our experience working with the ELONA characterization methodology from last year, we decided to automate a cell-ELONA using OT-2.

ELONA (Enzyme-Linked Oligonucleotide Assay), is a biochemical method based on an enzyme-linked immunosorbent assay (ELISA) that allows us to tell whether aptamers selected by SELEX can be effective and useful as biorecognition molecules and laboratory tools [1]. Many papers describe different ELONA formats for aptamer-based protein detection, but only a few have described a complete cell-ELONA characterization protocol [2].

We have developed and automated this methodology with OT-2, which allows us to minimize human error, increase replicability and scale the process up if we want to characterize multiple different aptamers at the same time.

2 Characterization Assays

As we aim to develop aptamers for in vivo applications, we decided to complete the cell-SELEX process by adding a powerful tool to determine the binding capacity of aptamers against their targets, also called affinity. Affinity refers to the strength of the interaction between a molecule and its target. The dissociation constant (Kd) is the key variable for assessing the binding capacity of a molecule against its target. Aptamers showing low dissociation constants have strong interactions with their targets.

3 Developing an ELONA Assay

ELONA Assay

To carry out this work, we first chose a standard ELONA format, which uses an anti-digoxigenin antibody to recognize an aptamer previously labelled with digoxigenin. This antibody is joined with a peroxidase enzyme, and once it is mixed with ABTS solution, it will be responsible for colorimetric reaction that will be detected.

Figure 1. Schematic representation of our standard ELONA format (Enzyme-Linked Oligo Nucleotide Assay) used for aptamer-based cell detection. a) Horseradish peroxidase conjugated Anti-Digoxigenin antibody b) Digoxigenin tag c) Aptamer d) Adhered bacteria.

ELONA Optimization: Experimental Sequence

One of the problems to solve before developing the characterization protocol was how to standardize the target volume (in our case, number of bacteria) coated into the Nunc MaxiSorp 96-well plate. For this, we decided to dye different dilutions of bacteria with crystal violet, then we visualized them under a microscope and estimated the number of cells per well by direct cell counting.

Once we had defined the working dilution factor and were able to control the amount of target in the experiment, we developed a standard cell-ELONA based on the protocol described by González et al. in 2015 [3] with modifications and adaptations for the automation process.

We decided to test the method with an aptamer previously selected and described by Cardoso et al. in 2016 [4], which we renamed AptaEco, to be used subsequently in LFA. As we knew the Kd of the aptamer, we carried out the assay measuring the absorbance at 405nm using concentration ranges of AptaEco labelled with digoxigenin, similar to the values described in the paper, looking for a Michaelis-Menten-like affinity behavior.

In addition, due to the problems found during the development of our aptamer-based sensor, we performed an additional ELONA for affinity characterization of a second aptamer (AntiBac). That aptamer was selected from bibliographic sources [5], as a peptidoglycan-specific aptamer for general bacteria recognition.

The results of the above-mentioned experiments can be found in the Experimental Results section below.

In addition, due to the problems found during the development of our aptamer-based sensor, we performed an additional ELONA assay for affinity characterization of a second aptamer (AntiBac). That aptamer was selected from bibliographic sources [5], as an peptidoglycan specific aptamer for general bacteria recognition.

Dyeing Protocol

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ELONA Protocol

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4 ELONA Automation

Once we established the protocols for optimal ELONA performance, the next step was to automate them, avoiding human intervention and increasing assay reproducibility. For ELONA automation, as well as other automated protocols, we designed and built different OT-2 modules.

The modules used for ELONA automation are the ones depicted below. For further details, designs and additional information about them, check out our Hardware page and GitHub repository.

3D Printed Modules

Once we established the protocols for optimal ELONA performance, the next step was to automate them, avoiding human intervention and increasing assay reproducibility. For ELONA automation, as well as other automated protocols, we designed and built different OT-2 modules.

The modules used for ELONA automation are composed by three different 3D-printed auxiliary supports for labware, and two hardware modules: thermal and shaker modules. For further details about any of them, designs and additional information about them, check out our Hardware page and GitHub repository. Links can be found at the bottom of this section.

Eppendorf Module

The eppendorf module consist on a support for 32 1.5-2 mL eppendorf tubes. Its designed as a grid of 4x8 holes, elevated from the OT-2 floor level using four legs. It helps during the ELONA as a platform for storing buffers, samples and reactives. That module also allows to perform operations in medium-volumes, like dilutions.

Falcon Module

The falcon module consist on a support for 4x15 mL and 1x50 mL falcon centrifugue tubes. Its designed as apltaform with a single hole for a 50 mL falcon tube, and a grid of 2x2 smaller holes for 15 mL falcons. The platform is elevated from the OT-2 floor level using four legs. It helps during the pre-coating step as a platform for storing large volume of buffers.

Liquids Container Module

Liquid container module consists on a compartimented hollow box, which fits exactly on one OT-2 platforms. That module allows for storing very large volumes of different liquids, like washing buffers. It's used in all of the ELONA washing steps, and for storing staining reactives during the tinction protocols.

Automated Shaker Module

To automatize the ELONA process, we created a shaker module and adapted it to the Opentrons to maintain the plate shaking during a certain period.

We could achieve this using a stepper motor controlled with a driver, with which we could input pulses. We also included magnets and Hall sensors to know exactly where the plate is in the movement, and hence know that when you pass once through the three magnets, that is your point of origin and end.

To program it we use the open-source Arduino software and a driver to switch from USB to UART. As a futher improvement, we are thinking about implementing resistors or peltier modules in the plate horder. That will allow for shaking under controlled hot / cold thermal conditions.

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3D Printed Modules

Eppendorf Module

Falcon Module

Liquids Container Module

GITHUB

Check thermal module documentation in our GitHub repository.

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GITHUB

Check shaker module documentation in our GitHub repository.

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Automated Protocols

Automated OT-2 protocols area available at our github.

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Hardware

Check our Hardware page for details.

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5 Experimental Results

Bacteria Fixation: 96-Well Coating

We used the protocol described above to stain E. coli cells automatically using OT-2. This experiment helped us to standardize the precise amount of target we had to use so that our characterization experiment would work correctly.
Figure 2 shows the 96-well bottom under microscopic magnification for the different E. coli dilutions assayed. Cells are visualized by tinction with crystal violet.

Figure 2. On the top, E.Coli under x40 magnification. A, B, C, D, and E show different dilutions (1:5, 1:10, 1:30, 1:50 and 1:100) of E.Coli dyed with crystal violet. Below, representation by ImageJ of the area coated with individuals bacteria corresponding to the different dilutions

Direct E. Coli coating has also been assayed offering results very similar to 1:5 dilutions of the bacterial suspension. Figure 3 depics the results of cell counting.

Figure 3. Representation of the number of individual bacteria coated per well into Nunc-96 MaxiSorp.

We can see how the number of cells coated into the well decrease while the dilution factor is increased. We decided to use 1:5 working dilution factor because to carry out a cell-ELONA, it is recommendable to saturate the well.

We have also perfomed different fittings of the experimental data to a obtain an useful correlation between dilution factor and number of E. Coli DH5-alpha cells coated. The fitting model which offered the best results was the following one:

N = X + (Y-X)/(1+10^(Z-Df)*(-W))

Where "N" is the number of coated cells, "Df" is the cell suspension dilution factor, and "X","Y","Z","W" are empirical parameters.

Performing a non-linear fit of the obtained data, we can finally reach the following correlation

N = 294092 + (993215-294092)/(1+10^(31.37-D)*(-0.03560)) (R² = 0.99)

That correlation is plotted as a blue line in figure 3.

ELONA Characterization

To test the automatized assay we developed, we used it to characterize the affinity of an aptamer (AptaEco) with an already-known dissociation constant. Each experimental point was replicated five times, to account for the typical signal deviations of the technique.

For evaluation of the binding capacity, we used different concentrations of AptaEco (0,5 ng/µL, 2ng/ µL, 3ng/µL and 4ng/µL.)

Figures 4 and 5 show the results for AptaEco characterization through automated ELONA.

Figure 4. Picture of the Nunc-96 MaxiSorp after assay.

Figure 5. Average Assessment of binding affinity of AptaEco to bacterial cells of E.Coli DH5-alpha by cell-ELONA. 40 minutes reaction time. C1) Control without aptamer, C2) Control without anti-digoxigenin antibody and C3) Control without cells.

After measurement of the absorbance evolution for 1 hour, the obtained absorbance at the maximum difference between each concentration was used for affinity constant determination. In our case we chose the measures after 40 minutes.

To determine the affinity constant, we adjusted the experimental data to a Michaelis-Mente- like affinity equation, obtaining a dissociation constant of Kd = 220 nM (R² = 0.997). It is worth noting that the measured affinity constant is near the previously calculated value. [4]

We also noticed that the control without addition of an aptamer offered a high signal value, as the graphic shows. However, the standard deviation of the depicted results is much higher for control 1 (± 0.2 a.u) compared to the experimental point (± 0.004 a.u).

Finally, we performed a second ELONA for characterizing another aptamer (AntiBac) used for the construction of our sensing device. AntiBac characterization results are shown in Figure 6.

Figure 6. Average Assessment of binding affinity of AntiBAC to bacterial cells of E.Coli DH5-alpha by cell-ELONA. 60 minutes reaction time C1) Control without aptamer, C2) Control without anti-digoxigenin antibody and C3) Control without cells.

As Figure 6 shows, the affinity for E. coli is low, and the signal increases faintly along the different tested concentrations, resulting in an experimental signal even lower than the negative controls.

6 Conclusions and Future improvements

Achievements

We have successfully optimized a whole-cell ELONA assay for aptamers affinity characterization. In addtion, we have adapted the protocol for a complete automation on Opentrons-2. We have also been able to characterize the affinity of two different aptamers, obtaining useful results for other project areas.

Future Steps

We hope our work to be furtherly used as a standard block for more complex automatized protocols, such in the way ELONA fits in our designed automated aptamer discovery SELEX protocol.

References

[1] Drolet, D.W., Moon-McDermott, L. and Romig, T.S. An enzyme-linked oligonucleotide assay. Nat Biotechnol. 14, 1021-1025 (1996).
[2] Stoltenburg, R., Krafčiková, P., Víglaský, V. and Strehlitz, B. G-quadruplex aptamer targeting Protein A and its capability to detect Staphylococcus aureus demonstrated by ELONA. Scientific Reports. 6, 1-12 (2016).
[3] Guerra-Pérez, N., Ramos, E., García-Hernández, M., Pinto, C., Soto, M., González, V.M. Molecular and functional characterization of ssDNA aptamers that specifically bind leishmania infantum pabp. PLos ONE (2015). doi: 10.1371/journal.pone.0140048.
[4] Marton, S., Cleto, F., Krieger, M. A., Cardoso, J. Isolation of anaptamer that Binds Specifically to E.Coli. PLoS ONE. (2016). doi:10.1371/journal.pone.0153637.
[5] I. M. Ferreira, C. M. de Souza Lacerda, L. S. de Faria, C. R. Corrêa, and A. S. R. de Andrade, “Selection of Peptidoglycan-Specific Aptamers for Bacterial Cells Identification,” Appl Biochem Biotechnol, vol. 174, no. 7, pp. 2548–2556, Dec. 2014.
[6] Leth-Larsen, R., Garred, P., Jensenius, H., Meschi, J., Hartshorn, K., Madsen, J., Tornoe, I., Madsen, H., Sørensen, G., Crouch, E., and Holmskov, U. A common Polymorphism in the SFTPD Gene Influences Assembly, Function, and Concentration of Surfactant Protein D. The Journal of Immunology. 174, 1532-1538 (2005).