2 mounted membranes in NNi flow cells
1mL NNi Conditioning Buffer
Access to a 100uL pipette
Access to NNi Nanopore Fabrication Software
For most applications, the best signal is obtained when the pore is similar in size to but slightly larger than the target molecule, since this is the point that allows molecule passage while blocking as much of the current as possible with each translocation. However, very small pores have lower capture rates, meaning that while the signals will be clearer, statistics will be a bit sparser . The optimal pore size for your application is therefore not something that can be predicted generally, though, since it depends on what information you are trying to extract. In the discussion below we give some guidelines to help in choosing a pore size for your application.
There are occasions where a pore the same size or even slightly smaller than your target can be beneficial [2,3]. For example, when you need to force a protein to unfold or change conformation while translocating the pore, one way this can be done is to force it through a pore too small to accept it in its native state.
In short, the best pore size depends on the application. If you are unsure what is needed, get in touch. We will be happy to assist you with your experimental planning and to suggest ways to maximize your experimental success.
Once you have a pore that passes quality control on size and noise, it is usually simple to detect your target molecule. We strongly suggest adding the positive sample to the male half of the flow cell (i.e. the small half, with a lower volume) and establishing a voltage, positive or negative, to drive the target through the nanopore starting from that point. This is simply because the male half-cell is easily disposable in case your molecule is sticky and can simply be replaced instead of cleaned, leaving no chance of cross-contamination that can otherwise confuse interpretation of an experimental result. While it is true that some molecules will translocate during your experiment, they are sufficiently dilute that they will have no effect on subsequent measurements with the female half-cell. Going forward, we assume this convention is followed and designate the male half-cell the cis reservoir and the female half-cell the trans reservoir.
While there are some cases (sticky molecules) where a half cell should only be used for a single sample, in general NNi flow cells are designed and intended to be used multiple times, and with multiple samples per mounted chip. For this reason, we have designed a laminar flow-through system that enables you to exchange buffers and samples using standard pipette tips quickly and easily.
In all NNi sensing adapters, the trans reservoir is ground while the cis reservoir is live with respect to the voltage. The choice of voltage polarity used will then depend on the charge of your target molecule for electrophoretic capture (most cases), or on the surface charge of your pore if you are using electroosmotic flow.
Optimizing for DNA
DNA in aqueous solution stays overall negatively charged in any pH and monovalent salts. This is useful to drive DNA through a nanopore by electrophoresis, and so the applied voltage used should be negative. DNA is an excellent learning tool for nanopores because it is easily measurable in many electrolyte conditions, being soluble even in extremely high salt concentrations and across a wide range of pH values. Because you can use high salt concentrations and therefore high currents through the pore, the signal from DNA is very strong and consistent.
While double-stranded DNA is well-studied in the field at this point, it is an excellent molecule for calibration of your experiments, in two ways. First, knowledge of the blockage caused by DNA can be used to estimate the effective thickness of the pore [4,5], as discussed in the section on electrical characterization of the nanopore. Secondly, because the capture rate statistics of DNA are reasonably well-understood, one can use it as an internal standard in a mixture of other molecules as a way to normalize out the effects of pore geometry on capture rate and thereby improve DNA concentration measurements . This is elaborated upon in a later section on data analysis.
Optimal pore size varies depending on the information being extracted. Double-stranded DNA will fold readily through a nanopore under typical applied voltages of 200 mV across a 10 nm thick pore if the pore is wide enough. Because DNA has an effective diameter of approximately 2.2 nm in solution, if folding suppression is desired then the pore should be smaller than 5 nm. However, note that as pore size approaches the size of DNA you may start to see the effects of friction and interaction between the DNA and the pore wall, which can manifest as slowing down of the average molecule speed during translocation, stretching of the molecule, or pore clogging [2,3].
Optimizing for proteins and other molecules
Proteins [6,7], synthetic polymers , glycogens , hyaluronic acid  and other small biomolecules  are highly varied molecules and are much more sensitive to buffer conditions than DNA, putting far greater restrictions on their measurement with nanopores. In general, they are less charged, can have positive and negative charge residues, being sensitive to pH, and are often unstable structurally or will agglomerate and crash out of solution in very high salt concentrations or pH values that are far from the conditions in which they are found natively. They also tend to be much stickier to synthetic surfaces (given the presence of uncharged/hydrophobic residues), resulting in more frequent pore clogs, and in general are just more difficult to work with since they also can translocate very rapidly .
That being said, fascinating work is being carried out studying proteins with solid-state nanopores, and with careful experimentation on the buffer conditions it is perfectly possible to detect and characterize proteins. Tricks can also be played with surface coatings designed to avoid (or promote) sticking of the protein to the membrane itself [13,14].
If you are finding it difficult to detect your targets, the following process may be helpful in generally guiding your optimization efforts. First, what net charge do you expect the protein to carry in your buffer? The membrane will be negative, so generally speaking negatively charged targets will be less prone to sticking. Can you increase the pH of the buffer to the point that the protein will be negatively charged without destabilizing it? If not, consider using electroosmotic flow to translocate your molecule rather than electrophoresis . Second, what is the maximal salt concentration that the protein can handle? Due to the shielding of charges in high salt proteins will tend to aggregate at high salt and precipitate, so sometimes reducing the salt concentration can help with this, though it will come at the cost of nanopore signal strength. Finally, what is the geometry of your protein, and can its shape be exploited to improve the signal with the nanopore? For example, if a protein is predominantly cylindrical, tuning the pore size to allow passage only in the axial direction can improve the consistency and clarity of your signals. Or, if you wish to disrupt the protein secondary structure using the pore, tuning the pore size to only allow passage in an unfolded or partially unfolded state can help achieve this.
Optimal conditions for protein sensing are as varied as the proteins themselves. If you are having a hard time finding yours, reach out for a discussion and we'll be happy to help.
 M. Charron, K. Briggs, S. King, M. Waugh, and V. Tabard-Cossa, “Precise DNA Concentration Measurements with Nanopores by Controlled Counting,” Anal. Chem., vol. 91, no. 19, pp. 12228–12237, 2019, https://doi.org/10.1021/acs.analchem.9b01900.
 S. Carson, J. Wilson, A. Aksimentiev, and M. Wanunu, “Smooth DNA Transport through a Narrowed Pore Geometry,” Biophys. J., vol. 107, no. 10, pp. 2381–2393, 2014, https://doi.org/10.1016/j.bpj.2014.10.017.
 K. Briggs, H. Kwok, and V. Tabard-Cossa, “Automated Fabrication of 2-nm Solid-State Nanopores for Nucleic Acid Analysis,” Small, vol. 10, no. 10, pp. 2077–2086, 2014, https://doi.org/10.1002/smll.201303602.
 M. Waugh et al., “Solid-state nanopore fabrication by automated controlled breakdown,” Nat. Protoc., vol. 15, pp. 122–143, 2019, https://doi.org/10.1038/s41596-019-0255-2.
 K. Briggs et al., “DNA Translocations through Nanopores under Nanoscale Preconfinement,” Nano Lett., vol. 18, no. 2, pp. 660–668, 2018, https://doi.org/10.1021/acs.nanolett.7b03987.
 E. C. Yusko et al., “Real-time shape approximation and fingerprinting of single proteins using a nanopore,” Nat. Nanotechnol., vol. 12, no. 4, pp. 360–367, 2017, https://doi.org/10.1038/nnano.2016.267.
 P. Tripathi et al., “Electrical unfolding of cytochrome c during translocation through a nanopore constriction,” Proc. Natl. Acad. Sci., vol. 118, no. 17, 2021, https://doi.org/10.1073/pnas.2016262118.
 M. Boukhet, N. F. König, A. Al Ouahabi, G. Baaken, J. F. Lutz, and J. C. Behrends, “Translocation of Precision Polymers through Biological Nanopores,” Macromol. Rapid Commun., vol. 38, no. 24, pp. 1–6, 2017, https://doi.org/10.1002/marc.201700680.
 B. I. Karawdeniya, Y. M. N. D. Y. Bandara, J. W. Nichols, R. B. Chevalier, and J. R. Dwyer, “Surveying silicon nitride nanopores for glycomics and heparin quality assurance,” Nat. Commun., vol. 9, no. 1, pp. 1–8, 2018, https://doi.org/10.1038/s41467-018-05751-y.
 F. Rivas et al., “Label-free analysis of physiological hyaluronan size distribution with a solid-state nanopore sensor,” Nat. Commun., vol. 9, no. 1, p. 1037, 2018, https://doi.org/10.1038/s41467-018-03439-x.
 E. Beamish, V. Tabard-Cossa, and M. Godin, “Identifying Structure in Short DNA Scaffolds Using Solid-State Nanopores,” ACS Sensors, vol. 2, no. 12, pp. 1814–1820, 2017, https://doi.org/10.1021/acssensors.7b00628.
 C. Plesa, S. W. Kowalczyk, R. Zinsmeester, A. Y. Grosberg, Y. Rabin, and C. Dekker, “Fast Translocation of Proteins through Solid State Nanopores.,” Nano Lett., vol. 13, no. 2, pp. 658–63, Feb. 2013, https://doi.org/10.1021/nl3042678.
 O. M. Eggenberger, C. Ying, and M. Mayer, “Surface coatings for solid-state nanopores,” Nanoscale, vol. 11, no. 42, pp. 19636–19657, 2019, https://doi.org/10.1039/c9nr05367k.
 Y. M. N. D. Y. Bandara, B. I. Karawdeniya, J. Hagan, R. Chevalier, and J. R. Dwyer, “Chemically Functionalizing Controlled Dielectric Breakdown Silicon Nitride Nanopores by Direct Photohydrosilylation,” ACS Appl. Mater. Interfaces, p. acsami.9b08004, 2019, https://doi.org/10.1021/acsami.9b08004.
 S. Schmid, P. Stömmer, H. Dietz, and C. Dekker, “Nanopore electro-osmotic trap for the label-free study of single proteins and their conformations,” bioRxiv, 2021, https://doi.org/10.1101/2021.03.09.434634.
Last Updated: 2021-05-11