Mass range, resolution and accuracy: Understanding the strengths and boundaries of mass photometry

Updated: 3 days ago


Mass photometry is an analytical method that measures molecular mass by quantifying light scattering from individual biomolecules in solution [1]. When considering mass photometry as a new technology for your lab, it is important to understand whether it is suitable for the types of samples you need to analyse.

Here, we describe mass photometry’s mass range, resolution and experimental error, the concentration ranges that can be analysed, and other information you will find useful as you explore mass photometry.


Mass range in mass photometry

Mass photometry has a wide working range and has been used to study diverse types of biomolecules, including proteins [2, 3], DNA [4], RNA, large macromolecular complexes [5], nanostructures [6] and even small viruses such as AAVs [7]. With the TwoMP mass photometer, you can reliably measure molecular mass in the range from 30 kDa to 5 MDa (Fig. 1). For complexes with a compact shape, the upper mass limit can be stretched to even more than 10 MDa.


Mass range in mass photometry, a bioanalytical method for characterisation of biomolecules

Figure 1 Diagram illustrating the mass range and examples of particles that can be analysed with mass photometry. *For indicative purposes only.


The resolution of mass photometry

What is resolution in mass photometry? It is the smallest difference in molecular mass that you can detect in a mass photometry measurement. In other words, mass photometry resolution is the smallest difference in molecular mass that resolves as two distinguishable peaks. There is no single value that defines the resolution of mass photometry because it depends on several factors, including the mass range of the particles of interest, the purity of the sample, and the relative concentrations of species in the sample.


For the TwoMP mass photometer, at the lower end of the mass range, the resolution is ± 25 kDa for a measurement of a 66 kDa biomolecule (defined as the Full Width of the peak at its Half Maximum value, FWHM). This means that you will be able to identify other species present in the sample if they are smaller than 41 kDa or larger than 91 kDa (Fig. 2, top panel). The different species will be visible as distinguishable peaks in the mass histogram obtained from a mass photometry measurement. On the other hand, if all species in the sample were within the range 41 – 66 kDa (or 66 – 91 kDa), only one broad peak would be observed, and it would be made up of counts from all different species.

At the higher end of the mass range, for example, 660 kDa, the resolution is ± 60 kDa FWHM. This means that you will be able to distinguish the 660 kDa particle from others if their mass is ≤ 600 kDa or ≥ 720 kDa (Fig. 2, bottom panel). If you are in doubt about whether mass photometry will allow you to resolve your species of interest and have purified samples of those species available, you can easily validate this experimentally by mixing the species and observing whether the number of peaks on the mass photometry histogram matches what you expect.


Graph explaining the concept of resolution in mass photometry

Figure 2 Resolution in mass photometry. Top: the peaks of two proteins in the lower mass range are resolved. Bottom: a mass histogram for the protein thyroglobulin is used to illustrate the resolution and FWHM in the 500 – 800 kDa mass range.


If a sample is significantly heterogeneous or has contaminants within a narrow mass window of interest, these factors will negatively impact the resolution of the mass photometry measurement. So, if you are performing a mass photometry experiment on a sample containing multiple species that are close in molecular mass, it is important to have the samples as clean as possible. On the other hand, if the contaminants or molecular species that are not of interest are much smaller or larger than your target biomolecules, you can use the sample for a mass photometry experiment without the risk of resolution loss.

In summary, mass photometry resolution varies across the mass range and can be affected by the composition and quality of a sample.


Experimental error in mass photometry

Mass photometry measures molecular mass with high accuracy. However, as with all the analytical methods, you must be aware of the possible experimental error.


A single mass photometry measurement comes with a measurement error of up to ± 5%, meaning that the molecular mass measured by mass photometry might deviate from the expected molecular mass by ± 5% (Fig. 3). This experimental error arises from a combination of sources, including sample measurement error, calibrant measurement error and error in fitting a Gaussian curve to the raw data. The error can be reduced by taking the average of repeated measurements.


Graph showing accuracy of mass photometry

Figure 3 Accuracy of mass photometry. Top: mass photometry measurements on multiple proteins across the 60 – 1000 kDa mass range show that the mass photometry signal scales linearly with mass. Bottom: experimental error across the studied mass range.


Concentration range in mass photometry

In mass photometry, we measure the mass of single molecules as they land on the measurement surface. To ensure that the landing events are well separated in space and time, it is essential to prepare samples to the appropriate concentration. Mass photometry can be performed with sample concentrations ranging from 100 pM to 100 nM, and the optimal concentration range for biomolecules is 5 – 20 nM.

Being able to run mass photometry experiments at such low sample concentrations is a great advantage if you have limited sample available. Another advantage of the working concentration range in mass photometry is that it matches the physiological concentrations of many proteins, which means the information you obtain will have greater biological relevance.

If you are studying weak biomolecular interactions which require high concentrations of molecular species, a method other than mass photometry might be more suitable. In fact, combining mass photometry data from samples at low concentrations with high-concentration data from other techniques can provide a more complete biomolecule characterisation.



Further resources

Live remote demo of TwoMP mass photometer

If you are exploring mass photometry and would like to see the instrument or ask some questions, register for one of our live remote demos. During these demos, one of our mass photometry experts will show you how to use the TwoMP mass photometer to analyse a few example samples and will be happy to answer your questions about the technology.

Technical note: Mass photometry basics

Learn more about resolution, FWHM, single-molecule detection, detection range and noise sources in mass photometry.

Blog: How does mass photometry work?

Read our technical blog explaining the principle behind mass photometry and why mass photometry is useful.

References

[1] G. Young et al., ‘Quantitative mass imaging of single biological macromolecules’, Science, vol. 360, no. 6387, pp. 423–427, Apr. 2018, doi: 10.1126/science.aar5839.


[2] Y. Higuchi et al., ‘Engineered ACE2 receptor therapy overcomes mutational escape of SARS-CoV-2’, Nat Commun, vol. 12, no. 1, p. 3802, Jun. 2021, doi: 10.1038/s41467-021-24013-y.


[3] A. Naftaly, R. Izgilov, E. Omari, and D. Benayahu, ‘Revealing Advanced Glycation End Products Associated Structural Changes in Serum Albumin’, ACS Biomaterials Science & Engineering, Jun. 2021, doi: 10.1021/acsbiomaterials.1c00387.


[4] Y. Li, W. B. Struwe, and P. Kukura, ‘Single molecule mass photometry of nucleic acids’, Nucleic Acids Research, vol. 48, no. 17, pp. e97–e97, Sep. 2020, doi: 10.1093/nar/gkaa632.


[5] A. P. Torres-Ocampo et al., ‘Characterization of CaMKIIα holoenzyme stability’, Protein Sci, vol. 29, no. 6, pp. 1524–1534, Jun. 2020, doi: 10.1002/pro.3869.


[6] E. Bertosin, P. Stömmer, E. Feigl, M. Wenig, M. N. Honemann, and H. Dietz, ‘Cryo-Electron Microscopy and Mass Analysis of Oligolysine-Coated DNA Nanostructures’, ACS Nano, vol. 15, no. 6, pp. 9391–9403, Jun. 2021, doi: 10.1021/acsnano.0c10137.

[7] D. Wu, P. Hwang, T. Li, and G. Piszczek, ‘Rapid Characterization of AAV gene therapy vectors by Mass Photometry’, Feb. 2021. doi: 10.1101/2021.02.18.431916.