Best Practices for Mass Photometry Analysis of mRNA

Mass photometry (MP) is a bioanalytical technology that accurately measures the mass of individual biomolecules and viral particles in solution. Already well established for protein and adeno-associated virus (AAV) analysis, MP is also emerging as a valuable tool for mRNA analysis. It can assess transcript intactness, detect double-stranded RNA contaminants, and identify aggregation – giving a comprehensive picture of mRNA integrity and purity with just a single measurement. Compared to other techniques, it has the advantages that it can assess mRNAs across a broad length range (200 – 10,000 bases) and supports analysis under native conditions. It is also signficantly faster and uses much less sample than methods such as capillary gel electrophoresis (CGE), high-performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA). While the use of MP for protein characterization is well established, applying MP to mRNA requires additional WHITEPAPER Best practices for mass photometry analysis of mRNAconsideration because mRNA and proteins have different physiochemical properties. mRNA has a strong negative charge, and tends to adopt complex secondary structures and oligomerize under native conditions. It is also highly flexible and subject to degradation. The conformational dynamics and ion dependence of mRNA mean that acquiring clean, reliable MP data can take more optimization for mRNA than for proteins. In this whitepaper, we present data showing how different aspects of experimental design can affect mRNA measurements with MP, and identify best practices based on that data. We cover experimental design considerations including: 1. Slide selection 2. Calibration 3. Detection range 4. Sample concentration 5. Buffer selection 6. Automation Mass photometry offers a powerful analytical solution for measuring mRNA purity and integrity. Here, we present a detailed investigation of the roles played by the slide surface, calibrant, sample concentration and buffer in mass photometry measurements of mRNA. We highlight best practices to ensure the most accurate and reliable results can be obtained. For a general introduction to mass photometry, Read our handbook, Understanding Mass Photometry To learn more about using mass photometry for mRNA analytics, Visit our mRNA Characterization webpage Read our handbook Accelerating mRNA Analytics with Mass Photometry 2 1. Slide selection The negative charge of the phosphate backbone influences how mRNA interacts with the surface of the glass slides used in MP measurements, which also carry a net negative charge. For MP, the molecules must interact with the slides, but this interaction is prevented by the negative charges of both the glass surface and the molecules. To enable that interaction and make it possible to measure mRNA with MP, the slide must be functionalized with a cationic coating. To illustrate this, we present an example of MP data for mRNA measured on either an uncoated or a cationic-coated slide (Fig. 1). The uncoated slides used were Refeyn’s MassGlass™ UC sample carrier slides; the cation-coated slide were Refeyn’s MassGlass NA slides. The strong negative charge of mRNA prevented its interaction with the uncoated glass, but the positive charge on the MassGlass NA surface made it possible to measure the molecular mass distribution – and hence the distribution of lengths (in bases). The ordinate (dotted line) denotes 0 bases; counts with ‘negative’ bases refer to events where a molecule unbinds from the glass and moves away. Almost no unbinding was seen for the cation-coated slides. By contrast, for the uncoated slides, small but roughly equal numbers of binding and unbinding counts were observed, indicating that the molecules did not interact with the glass as required for MP analysis. For MP measurements of mRNA, Refeyn produces MassGlass™ NA – ready-to-use slides with a cationic coating that are optimized to provide the best performance for mRNA analysis. Figure 1. A cationic coating is required to enable MP analysis of mRNA. (A) Commercially available eGFP mRNA (1,179 b) samples were prepared and measured using Refeyn’s uncoated (MassGIass UC, blue) and cation-coated (MassGIass NA, orange) slides. (B) Representative ratiometric images generated by MP show very few landing events (which appear as dark dots) when an uncoated slide was used, while the cation-coated slide image clearly shows many landing events. The mRNA sample was prepared at 5 ng/μL in 1x PBS and diluted 1:1 after droplet dilution buffer focusing of the instrument. Measured on a TwoMP mass photometer. Refeyn’s MassGlass NA Sample Preparation Kits contain everything needed for mass photometry measurements of mRNA samples, including the sample well cassettes (left) and MassGlass NA slides (middle and right) shown here. Pictured here is the kit for use with the TwoMP mass photometer. The MassGlass NA Auto Sample Preparation Kit, for use with the automated version of the TwoMP, the TwoMP Auto, is also available. For more details, please visit Refeyn’s eShop. 3 2. Calibration Mass photometry measures a signal known as the ‘contrast’, which is the interference of light reflected off the glass slide and light scattered by the molecules. The contrast is proportional to the molecule’s mass (or length, for mRNA). Converting contrast measurements to mass (or length) requires calibration with a standard of known mass(es) (or length(s)). The precise linear relationship between the contrast and mass may differ for each class of particle, due to differences in optical properties. A protein calibrant is therefore needed when measuring proteins, an RNA calibrant is needed for measuring RNA, etc. Small differences may also occur from day to day and in different buffers, so regular calibration is needed for maximum accuracy. For mRNA measurements, commercial RNA ladders can be used as calibration standards for MP experiments. In these ladders, larger species tend to have lower abundance, which is reflected in lower counts/peak and therefore smaller peaks. This is true for the ladder shown in Fig. 2A, for example, where the smallest species (500 b and 1000 b) have the tallest peaks. Stock solutions need to be diluted prior to measurement because if the solution is too concentrated, particle signals will overlap, reducing data quality. However, dilution may reduce the counts for the least abundant species to the extent that their peaks are unreliable for accurate calibration. Overall, Refeyn recommends that peaks only be selected for use in the calibration if they have >250 counts, and that the total counts (for all peaks together) should be less than ~12,000. Dilution factor, calibrant peak selection and choice of ladder should be adjusted to meet these requirements, in line with the size of the RNAs being measured (see below). Adjustments may also be needed to account for variability across batches. Based on internal testing, Refeyn recommends the Millenium RNA marker (Invitrogen, AM7150), which has a series of clear peaks from 500 – 6,000 bases (Figs. 2A, 5). The standard used should show good linearity (R2 = 1.00) and a low value for ‘Max. error’ in Refeyn’s DiscoverMP software interface for calibration (Fig. 2B-C). However, inclusion of the Millenium RNA marker’s 9,000-base species is not recommended, as it has relatively few counts and the standard deviation (sigma) is broad (Figs. 2A, 5). Testing showed that this peak is less reliable for calibration (data not shown). The example shown in Fig. 2A resulted in 12,098 binding counts and >250 counts for all RNA species except the 9,000-base RNA. Empirical testing has also shown that calibration is more reliable when the species lengths extend above and below the length range of the sample(s) being measured. Figure 2. Recommended calibration using the Millenium RNA marker. (A) MP data for the Millenium RNA marker, with Gaussian fits outlined in black. Labels indicate assumed peak identity, assigned based on relative contrast values and expected species in standard. (B-C) Screenshots from Refeyn’s DiscoverMP software show recommended peak selection for calibration of Gaussian fits to species of (B) 500 – 4,000 or (C) 1,000 – 6,000 bases. Sample preparation involved an initial 1:200 dilution in 1x PBS followed by a 1:1 dilution, after droplet dilution buffer focusing of the instrument. Measured on a TwoMP mass photometer. 4 Figure 3. MP accurately measures mRNA and saRNA length. (A) Samples of mRNA (EGFP, FLuc and eSpCas9) and saRNA (EGFP) varying in length from 980 bases to 10,200 b were analyzed by mass photometry. In every case, the mass photometry measurement returned a length (determined from the mean of the main peak in the measured distribution) in close agreement with the expected value. (B) Plotting the measured vs. expected mRNA length values shows that the mass photometry measurements are highly accurate. Triplicate measurements for the same samples as in A. are shown; error bars (±standard deviation, SD) are smaller than the markers. Each RNA was prepared in 1x PBS at 5 nM prior to collecting triplicate experiments for each sample and measured on a TwoMP mass photometer. 0 200 400 600 0 200 400 600 mRNA EGFP 0 2000 4000 6000 8000 10000 12000 Bases 0 200 400 600 0 200 400 600 Counts Expected length: 980 bases mRNA FLuc Expected length: 1,909 bases mRNA eSpCas9 Expected length: 4,471 bases 1,000 ± 10 b 1,970 ± 10 b 4,560 ± 20 b 10,160 ± 20 b saRNA EGFP Expected length: 10,110 bases y = 1.02x + 7.4 R = 1.00 0 3000 6000 9000 12000 0 3000 6000 9000 12000 Measured length (bases) Expected length (bases) A B Refeyn recommends using the Millenium RNA marker as follows: • Use the species of 500 – 4,000 bases for calibration to measure samples in that length range (Fig. 2B). • Use the species of 1,000 – 6,000 bases for calibration to measure samples up to 10 kb in length (Fig. 2C). Applying this approach to measure four IVT-generated mRNAs resulted in length measurements that were in excellent agreement with the expected lengths from the product literature (Fig. 3). Relative errors for the measured lengths were 2.0% for eGFP mRNA, 3.2% for FLuc mRNA, 2.0% for SpCas9 mRNA, and 0.5% for eGFP saRNA. Other standards used for calibrating MP measurements of mRNA samples in the literature include the RiboRuler High Range RNA ladder from Thermo Scientific (Cat# SM1821)3 and the Low Range ssRNA Ladder from New England Biolabs (N0364S), which has been used for shorter RNA targets.1 5 3. Detection range Among the mass photometers currently on the market, Refeyn’s TwoMP (and the automated version, the TwoMP Auto) have the most suitable specifications for mRNA analysis. The TwoMP, which has a detection range of 30 kDa to 5 MDa for protein analysis, has been qualified to measure mRNAs with lengths of 200 – 10,000 bases although the theoretical upper limit is around 15,000 bases. An mRNA therapeutic fits comfortably within these limits, with untranslated features comprising 300 – 500 bases that correlate to a mass range of 100 – 165 kDa. Estimated values for the untranslated features of mRNA consist of the 100 – 200 bases for the 5’ UTR, 100 – 200 bases for the 3’ untranslated region (UTR), and 100 – 250 bases for the poly(A) tail (Fig. 4). The coding region can be of variable length, depending on the encoded therapy, but is typically in the range 600 to 2,000 bases. As a single-molecule technique, where each count represents a single mRNA molecule, mass photometry makes it possible to obtain high-resolution, quantitative data about the composition of a sample and to do so using very little sample. In comparison to an agarose gel, for example, MP requires 50x less sample (4 μg of material for a 1% agarose gel vs. 70 ng of sample (total RNA) for MP). Mass photometry also reports a much more detailed quantitative result (Fig. 5). It is notable that, due to MP’s broad dynamic range, it is possible to detect even the very low-abundance populations, where only a few nanograms were present. Figure 4. mRNA molecule schematic. This representation shows the 5′ cap structure, 5′ UTR, coding sequence with modified nucleotides (Ψ), 3′ UTR, and the poly(A) tail. Figure 5. Visual comparison of the RNA species within the Millenium RNA ladder analyzed by agarose gel and MP. The values for the amount (ng), mol of RNA, and RNA copies were calculated from the counts in the MP data in Fig. 2A. The ladder image represents a 4 μg sample run on a 1% agarose gel that was stained with ethidium bromide. 6 4. Sample concentration A typical MP experiment only requires a few nanograms of material per experiment. Already well established for protein studies, this metric also holds true for mRNA, with recent publications reporting successful MP analysis of mRNA samples with concentrations of 0.5 – 10 ng/μL.1–5 Because RNA concentrations are conventionally determined using UV-Vis spectroscopy, it is recommended to begin an MP experiment by measuring the sample at a higher concentration, then titrating down the sample until an optimal number of counts is observed for the predominant species – typically ~500 – 3,000 counts per species (for regular field of view, FoV). Meanwhile, the sigma value† (which corresponds to the width of the peak) can be used as a reference for data quality. To illustrate how mRNA sample concentration affects MP analysis, we measured a 1.2 kb mRNA of eGFP at concentrations of 55, 27, and 14 ng/μL (Fig. 6). The data at 55 ng/μL showed that the sample was too concentrated based on several factors. First, there was a significant amount of unbinding – indicated by counts on the left side of the ordinate (i.e. left of the dotted line) – which suggests saturation of the slide surface. Next, the relative errors for the measured lengths were -4.2% for the monomer species and -11.7% for the dimer (Table 1) – high considering that the relative error typically achievable with MP analysis of mRNA is <5%. Lastly, the sigma values for the 55 ng/μL sample (165 bases for the monomer and 375 bases for the dimer) were also high, indicating that the peaks were very broad and corresponding to a standard deviation of ~32% for the monomer (Table 1). Dilution of the mRNA sample to 27 ng/μL eliminated most of the unbinding counts and improved the sigma value (98 bases; standard deviation = 8.3% for the monomer), but it did not improve the relative error of the monomer (-4.5%). Further dilution to 14 ng/μL further reduced the unbinding counts (they were equivalent to a buffer-only measurement), markedly reduced the relative errors of both the monomer and dimer species to +/-1.7% and decreased the sigma value slightly more, down to 75 for the monomer (standard deviation = 6.4%). From these data, we could determine that 14 ng/μL was the ideal sample concentration, and then went on to collect experimental replicates to measure the length of the mRNA product and relative populations of monomer (70%) and dimer (5%) species present in the sample in its native state. Figure 6. Optimizing sample concentration can improve the accuracy of MP measurements. MP data of a 1.2 kb mRNA for eGFP collected on a cation coated slide in 1x PBS at three concentrations: 55 (top), 27 (middle), 14 ng/μL (bottom). Measured on the TwoMP mass photometer. [mRNA] (ng/μL) Counts Bases Error (%length) Species (%) Sigma (bases) Monomer 55 10,995 1,130 -4.2 78 165 27 7,558 1,126 -4.5 77 98 14 4,040 1,159 -1.7 70 75 Dimer 55 2,377 2,081 -11.7 17 375 27 619 2,331 -1.1 6 169 14 241 2,397 1.7 5 113 Table 1. Statistics for the Gaussian fits of the monomeric (1,179 bases) and dimeric (2,358 bases) species in the three samples shown in Fig. 6. † The sigma value of a peak represents the standard deviation of the measured peak. It is conventionally calculated as a function of the Full Width Half Maximum (FWHM) equation by FWHM=2√2Ln2 σ, which can rearranged to an approximation of σ ≈ FWHM/2.355. 7 5. Buffer selection Buffers play a crucial role in MP experiments because they influence the physiochemical properties of the biomolecule being measured and can affect its ability to interact with the slide surface. That said, mass photometers generally tolerate a wide range of buffer, pH and salt conditions that support the structural integrity, stability, or native interactions of the biomolecule. A good buffer should minimize both the width of the peak (i.e. the sigma value, see preceding section) and the occurrence of unbinding events on the slide surface (provided that care is taken to also optimize the concentration of the sample). Examples of the many buffers that are compatible with MP can be found throughout the literature, and include basic buffers (e.g. HEPES, PBS) and monovalent salts (e.g., NaCl, KCl). It is preferable to avoid viscous stabilizers (e.g., glycerol, detergent) that can increase the background, compromising signal quality. A review of mRNA-focused publications identified 1x PBS1,2,4 and TE3 as the buffers used in MP measurements of mRNA. To demonstrate how the choice of buffer can impact MP measurements, we used MP to analyze samples of eGFP mRNA in either IDTE (IDT, Cat #11050109) with varying concentrations of NaCl or PBS (Gibco 14-190-250) buffer (Fig. 7). The data for mRNA in IDTE buffer showed a distribution with a good number of counts and low relative error of the measured length (1.6%). However, the sigma value (253 bases, Table 2) was relatively high (5% standard deviation would be ~60 bases), due to the need for a higher concentration of sample to achieve an appropriate number of counts. It should also be noted that there were significant amounts of counts at low mass (length), which were mirrored as unbinding events (counts to the left of the ordinate). The low-mass events likely represent some sort of buffer effects since there was no apparent unbinding of the intact mRNA monomer. When 50 – 250 mM salt (NaCl) was added to the IDTE buffer, it lowered the effective concentration of mRNA required to collect a good amount of counts of the mRNA monomer – with a low relative error (-0.4 – 2.8%) and low standard deviation (~6%) with sigma values of 71 – 77 bases (Table 2). For IDTE in absence of NaCl, an mRNA concentration of 55 ng/μL resulted in relatively low counts. By contrast, in the presence of NaCl, ~4,500 counts were achieved with a concentration of just 11 ng/μL. Adding salt to the IDTE buffer dramatically reduced the presence of both the counts at low mass (length) and the unbinding events observed in the 0 mM NaCl sample. Data collected in 1x PBS showed statistics comparable to those of the IDTE samples with added salt. This result indicates that mRNA requires a Figure 7. For MP analysis of mRNA, which requires interaction with the cation-coated slide surface, the buffer requires a basal ionic strength. Shown are data from MP analysis of eGFP mRNA (1,179 bases) in either IDTE buffer (10 mM Tris, 0.1 mM EDTA) with increasing levels of NaCl: 0 mM (light blue, top), 50 mM (mid blue), 150 mM (orange), 250 mM (red); or in 1x PBS (green, bottom). Sample concentrations are given in Table 2. Measured on a TwoMP mass photometer. Table 2. Statistics for the Gaussian fits of the monomeric species of mRNA eGFP (1,179 b) in the five samples shown in Fig. 7. Buffer NaCl (mM) [mRNA] (ng/μL) Counts Measured length (bases) Length error (%) Sigma (bases) IDTE 0 55 1,814 1,198 1.6 253 50 11 4,795 1,212 2.8 71 150 11 4,683 1,189 0.8 75 250 11 4,518 1,174 -0.4 77 1xPBS 140 14 4,180 1,159 -1.7 75wbuffer with a minimum ionic strength to interact effectively with the cation-coated surface used for MP. Another buffer parameter that can impact MP measurements is pH. To demonstrate its effects, we adjusted buffer pH while holding the NaCl concentration at 150 mM to bring the ionic strength near that of PBS (~170 mM). For these experiments, we chose citrate (pH 6.5), HEPES (pH 7.4), and Tris (pH 8.0) because these are common biological buffers in the range of most mRNA experiments. The effects of 8 adding 1 mM EDTA were also explored to assess the effects of divalent cations (e.g. Mg2+), which are known to promote higher-order RNA structures.6 These buffers were again used in MP measurements of eGFP mRNA (Fig. 8). EDTA reduced the presence of the low-mass counts observed in the citrate and HEPES experiments, but had little effect on the MP profiles for PBS and Tris buffers. PBS, in general, exhibited very few low-mass counts in both cases, which may explain why this buffer is widely used in the current literature. With respect to the measured mRNA length, all buffer conditions showed relatively good agreement (<4%) with the calculated value (Fig. 8C). Citrate showed the lowest relative error in measured length regardless of EDTA concentration. PBS showed a consistent 3-4% underestimation of the mRNA length. While within acceptable limits, both HEPES and Tris showed a reproducible EDTA-dependent change in the length estimation, where the length was slightly underestimated in absence of EDTA and overestimated in presence of EDTA. Considering dimerization, the relative amount of dimeric species was 7-8% across all citrate, HEPES, and Tris buffers and was only lower for PBS (5%). The observed difference in higher-order states may be a buffer-specific influence on the native mRNA structure that has not been explored. What can be concluded, however, is that EDTA did not influence the level of dimerization in any of the tested buffers, indicating that basal divalent ion concentrations do not meaningfully influence the mRNA oligomeric state. Analysis of the sigma values showed a significant difference between buffer conditions (Fig. 8D). Recall that the sigma value represents the peak’s broadness and can be considered as a diagnostic for buffer conditions in an MP experiment. The buffers citrate and PBS yielded data with the narrowest sigma values (4.9 – 5.5%) while HEPES and Tris showed larger sigma values (6.1 – 8.0%). This trend was also observed in the presence of EDTA. Another useful indicator of buffer suitability is the relative amount of unbinding (Fig. 8E). The monovalent HEPES and Tris buffers exhibited the most unbinding (>10% of all counts were unbinding events) in the presence or absence of EDTA and high variability between measurements. In contrast, the multivalent citrate (in presence of EDTA) and PBS buffers showed significantly lower levels of unbinding. While the mechanisms that drive these differences is unclear, these data underscore the importance of parameterizing buffer conditions to optimize the experiment. MP data were also collected for the Millenium RNA ladder to explore how buffer conditions influence a wider range of RNA lengths. (We focused on species of 1,000 – 9,000 bases in accordance with the species used for the calibration.) Table 3 presents a heat map of the relative error for the measured RNA lengths in the eight buffer conditions used in Fig. 8. Generally, the multivalent buffers (citrate and PBS) performed better than the monovalent HEPES and Tris buffers. In particular, citrate buffer without EDTA consistently showed <2% relative error. Citrate with EDTA and PBS with Figure 8. Buffer effects on MP data of eGFP mRNA. Representative MP data of eGFP mRNA (1,179 bases) in 10 mM buffer with 150 mM NaCl. In (A), there was no EDTA and 2.5 ng/μL mRNA. In (B), there was 1 mM EDTA and 5 ng/μL mRNA. (C) Relative error (%) for mRNA length by buffer condition (n=3). (D) Relative sigma (% length) for mRNA by buffer condition (n=3). (E) Percentage of total counts that correspond to unbinding events by buffer condition (n=3). 9 Table 3. Heat map of the relative error (%) of eGFP mRNA length measured by MP in various buffered solutions. The buffers consisted of 10 mM buffer and 150 mM NaCl with or without 1 mM EDTA, as indicated. The relative error was calculated as the difference of the measured and calculated (1,179 bases) mRNA length for 3 replicate experiments under each condition. Data from the same experiments is also shown in Fig. 8. Measured on a TwoMP mass photometer. Figure 9. For MP measurements for mRNA, results with PBS buffer were more reproducible than those with citrate. (A) Scatter plot of measured length for 10 replicate measurements of eGFP mRNA in 1x PBS (blue) or 10 mM Citrate (pH 6.5) with 150 mM NaCl (orange). The dotted line at 1,179 bases indicates the known mRNA length. (B) Relative length error and sigma of data in (A). or without EDTA showed comparable results for the RNA species. HEPES and Tris generally showed greater error, particularly in the presence of EDTA. They also showed more low-mass counts, consistent with the data in Fig. 8 (not shown), and made it difficult to achieve sufficient counts for accurate detection of the 9,000-base species (not shown), suggesting an upper length limit for these buffers. Next, we compared the reproducibility of MP measurements of mRNA in 1x PBS vs. citrate buffer (Fig. 9). Over the course of 10 measurements, 1x PBS consistently showed excellent precision and accuracy, with 2.5 ± 0.9% error in measured length. Citrate buffer, which showed very low error in Fig. 8, showed surprisingly variable performance over 10 measurements, with error of 3.3 ± 3.1%. While both buffers resulted in very narrow peak distributions, with sigma values ~5%, the large differences in measured length indicate that 1x PBS is the better choice for reliable MP measurements of RNAs. 10 6. Automation For automated measurement of multiple samples in one run, an automated mass photometer, the TwoMP Auto, is available. The TwoMP Auto measures up to 24 samples in as little as 90 min, providing user walkaway time. This approach returns consistent measurements and reproducible results through precision pipetting. It can be ideal for screening and titration assays. The automated mass photometer runs at ambient temperature, so it is important to ensure that mRNA remains stable for the duration of an automated run. To assess this, we used MP to measure eGFP, FLuc and SpCas9 samples in 1x PBS in triplicate at the start and end of an automated mass photometry run. The relative length error was <3% at both time points (Fig. 10A) and the percentages of full-length (monomeric) RNA in the samples remained consistent (Fig. 10B). The results indicate that mRNA is stable enough for analysis by automated mass photometry. Figure 10. mRNA monomers (%) remain stable for the duration of an automated mass photometry run. Samples of eGFP, FLuc and SpCas9 were measured in triplicate by automated MP immediately after dilution in 1x PBS, at the start (solid bars) and end (dotted bars) of a full run of automated measurements. (A) The relative error for both sets of measurements (based on the measured length vs. the expected length) was very low (<3%) at both time points. (B) The percentages of full-length (monomeric) RNA in the samples also remained consistent. Measured on a TwoMP Auto mass photometer. Visit Refeyn’s website to learn more about our mRNA analytics solutions, including: TwoMP Mass Photometer MassGlass NA Sample Preparation Kits TwoMP Auto Mass Photometer MassGlass NA Auto Sample Preparation Kits A B 11 References 1 Camperi et al., Anal. Chem. 2024a https://doi.org/10.1021/acs.analchem.3c05539 2 Deslignière et al., Ther. Methods Clin. 2025 https://doi.org/10.1016/j.omtm.2025.101454 3 Schmudlach et al., Biol. Methods Protoc. 2025 https://doi.org/10.1093/biomethods/bpaf021 4 Camperi et al., Anal. Chem. 2024b https://doi.org/10.1021/acs.analchem.4c04162 5 Li et al., Nucleic Acids Res. 2020 https://doi.org/10.1093/nar/gkaa632 6 Draper. RNA. 2004 https://doi.org/10.1261/rna.5205404 V1-Sep 25 ©2025 Refeyn Ltd Unit 9, Trade City, Sandy Lane West, Oxford OX4 6FF, United Kingdom For information on products, demos and ordering, write to orders@refeyn.com Refeyn and MassGlass are trademarks of Refeyn Ltd. orders@refeyn.com refeyn.com Refeyn @Refeyn 20Testimonials“Mass photometry provides a fast screening tool to investigate mRNA integrity and size.”De Vos et al. (2024), J Chromatogr A“The data confirm the great potential of [mass photometry] technology... as a fast and simple orthogonal method that provides insights into the homogeneity and stability of mRNA samples.”Camperi et al. (2024), Anal ChemUnit 9, Trade City, Sandy Lane West, Oxford OX4 6FF, United Kingdom©2024 Refeyn LtdFor information on products, demos and ordering, write to info@refeyn.comSamux and Refeyn are registered trademarks of Refeyn Ltd.refeyn.com @refeynitRefeynRefeynAbout RefeynRefeyn pioneers analytical instruments that put molecular mass measurement capabilities within easy reach for scientists. Refeyn’s unique products measure the mass of individual proteins, nucleic acids, complexes and viruses directly in solution – providing vital insights for scientific discovery, R&D and therapeutics production.Our instruments feature mass photometry technology, which uses light to quantify the mass of single particles in solution without labels, and macro mass photometry technology, which uses light to characterize large viral vectors. Providing intuitive data in minutes, mass photometry technologies help scientists solve their research questions, optimize R&D processes and focus on innovation.20Testimonials“Mass photometry provides a fast screening tool to investigate mRNA integrity and size.”De Vos et al. (2024), J Chromatogr A“The data confirm the great potential of [mass photometry] technology... as a fast and simple orthogonal method that provides insights into the homogeneity and stability of mRNA samples.”Camperi et al. (2024), Anal ChemUnit 9, Trade City, Sandy Lane West, Oxford OX4 6FF, United Kingdom©2024 Refeyn LtdFor information on products, demos and ordering, write to info@refeyn.comSamux and Refeyn are registered trademarks of Refeyn Ltd.refeyn.com @refeynitRefeynRefeynAbout RefeynRefeyn pioneers analytical instruments that put molecular mass measurement capabilities within easy reach for scientists. Refeyn’s unique products measure the mass of individual proteins, nucleic acids, complexes and viruses directly in solution – providing vital insights for scientific discovery, R&D and therapeutics production.Our instruments feature mass photometry technology, which uses light to quantify the mass of single particles in solution without labels, and macro mass photometry technology, which uses light to characterize large viral vectors. Providing intuitive data in minutes, mass photometry technologies help scientists solve their research questions, optimize R&D processes and focus on innovation. Summary MP is a powerful, next-generation bioanalytical tool for mRNA. Measuring molecules of up to 10 kb in their native state, a single MP measurement provides data for CQAs related to mRNA sample integrity and purity. Being ~20x faster and using 10 – 50x less sample, MP offers clear benefits compared with other mRNA analytical methods. MP could be a transformative addition to any mRNA workflow, helping to address the unmet need for faster analytics with low sample requirements. However, as with any analytical technology, it is essential to understand which variables can affect data quality and how to get the most out of your analysis. Here, we have demonstrated how MP measurements of mRNA can be affected by different aspects of experimental design, including slide coating, sample calibration, sample concentration, and buffer conditions. We have presented what needs to be taken into consideration to develop an MP workflow. If the outlined best practices are followed, that workflow should reliably determine the length of an mRNA sample within 5% of the calculated value, covering mRNA lengths of 200 to 10,000 bases, using as little as 2 ng of sample, and taking under five minutes (from sample prep to analysis). In brief, the following best practices should be adhered to when developing an MP experiment for an RNA sample: • Cation-coated slides – such as Refeyn’s MassGlass NA slides, optimized specifically for mRNA analysis – must be used. • Calibrate using an RNA standard with an appropriate range for the samples being measured, only using peaks with >250 counts (total counts for all species should be <12,000). We recommend the Millenium RNA marker (Invitrogen AM7150), using species of 500 – 4,000 b to measure RNAs in that range and species of 1 – 6 kb for RNAs up to 10 kb. Other options are New England Biolabs’ ssRNA ladder, N0362S (for measuring RNAs < 1 kb) and Thermo Scientific’s RiboRuler High Range, SM1821 (for RNAs up to 10 kb). • Set the acquisition settings to a Large FoV for samples >1 kb or Regular FoV for samples <1 kb (refer to Refeyn’s AcquireMP software manual for further details on acquisition settings). • To optimize your sample concentration, test a range of concentrations until the data show minimal unbinding events (ideally, only buffer effects near the origin), low sigma (sigma/length <10%), and sufficient counts (500 – 3,000 for Regular FoV or 1,500 – 8,000 counts in Large FoV) for statistical analysis of the measured species.† † • Minimize unbinding events by increasing the ionic strength of the buffer (>50 mM) or reducing the sample concentration to 1 – 10 ng/μL • Start experiments with 1x PBS as a benchmark, as it shows minimal low-mass counts, few unbinding events, and minimal error for measured length with excellent reproducibility. Refeyn’s extensive internal testing indicates that following these best practices should enable optimal mRNA measurements, in line with our specifications. However, if you encounter any issues, please contact us for support – our team is here to support and learn from you, and ensure that our instruments deliver the best possible performance. †† Note that the target counts are for the intended species and higher-order oligomers may have reduced counts based on their stability in the given sample conditions.