Development of an Automated, High-Throughput Methodology for Native Mass Spectrometry and Collision-Induced Unfolding

Abstract

Native ion mobility mass spectrometry (nIM-MS) has emerged as a useful technology for the rapid evaluation of biomolecular structures. When combined with collisional activation in a collision-induced unfolding (CIU) experiment, nIM-MS experimentation can be leveraged to gain greater insight into biomolecular conformation and stability. However, nIM-MS and CIU remain throughput limited due to nonautomated sample preparation and introduction. Here, we explore the use of a RapidFire robotic sample handling system to develop an automated, high-throughput methodology for nMS and CIU. We describe native RapidFire-MS (nRapidFire-MS) capable of performing online desalting and sample introduction in as little as 10 s per sample. When combined with CIU, our nRapidFire-MS approach can be used to collect CIU fingerprints in 30 s following desalting by using size exclusion chromatography cartridges. When compared to nMS and CIU data collected using standard approaches, ion signals recorded by nRapidFire-MS exhibit identical ion collision cross sections, indicating that the same conformational populations are tracked by the two approaches. Our data further suggest that nRapidFire-MS can be extended to study a variety of biomolecular classes, including proteins and protein complexes ranging from 5 to 300 kDa and oligonucleotides. Furthermore, nRapidFire-MS data acquired for biotherapeutics suggest that nRapidFire-MS has the potential to enable high-throughput nMS analyses of biopharmaceutical samples. We conclude by discussing the potential of nRapidFire-MS for enabling the development of future CIU assays capable of catalyzing breakthroughs in protein engineering, inhibitor discovery, and formulation development for biotherapeutics.

Graphical Abstract

INTRODUCTION

Native mass spectrometry (nMS) has emerged as a transformative technique for structural biology. In an nMS experiment, conditions in solution and in the gas phase are carefully tuned such that the native-like biomolecular ions are preserved for the duration of the measurement. Typically, this is carried out by preparing samples in aqueous solutions containing volatile salts prepared at neutral pH, before gently ionizing the biomolecules such that transient, noncovalent interactions may be preserved throughout the ionization process.¹ Such nMS methods have been widely deployed to gain structural insights into many diverse systems of interest including: oligonucleotides, membrane proteins, and monoclonal antibodies (mAbs).^2–8 In order to provide structural information, nMS is often combined with ion mobility (IM) spectrometry to perform native IM-MS (nIM-MS) experiments that allow for biomolecular ions to be separated by their size, shape, and charge.^9–11 The measured drift times can then be converted to collision cross section (CCS) values that describe the 3D rotationally averaged size of the ion, which can be validated against measurements from other biophysical techniques through calibration.^12–14

However, since biomolecules typically adopt an ensemble of conformational states, CCS measurements of native-like ions alone are often insufficient to detect subtle structural differences between samples.^15,16 Accordingly, biomolecules can be collisionally activated and unfolded to sample different conformational states that can be used to resolve iso-CCS ions and evaluate biomolecular stability via collision-induced unfolding (CIU). CIU data are typically treated as fingerprints, where changes in CCS produced during activation can be mapped and quantified in order to produce multivariate classifiers capable of identifying and evaluating subtly different protein states.¹⁷ For example, CIU data have been deployed to study a variety of protein systems including biotherapeutics and membrane proteins.^6,18,19 CIU features are generally reproducible between laboratories when collected using a drift tube instrument, enabling future databasing efforts for CIU data.²⁰

While nMS and CIU have been widely deployed, they largely remain throughput limited due to bottlenecks associated with preanalysis desalting and sample introduction using nanoelectrospray ionization (nESI) at low flow rates. Typically, samples must be desalted prior to analysis by MS, a process that can take up to 25 min²¹ Beyond this, the nESI emitters often used in nMS experiments are typically of single use and are prone to clogging and generating unstable signal.²² Multiple prior reports have described methods to improve the throughput of nMS. Examples include, the Advion Nanomate^23–27 and standard autosamplers coupled to fast desalting or separation technologies.^28–31 In addition to nMS, recent efforts have been made to increase the throughput of CIU measurements, including droplet microfluidics for sample introduction and online size exclusion chromatography (SEC) that requires several minutes per sample.^29,30,32 In addition, recent advances in acoustic ejection-MS have allowed for MS experiments of significantly improved throughput targeting intact proteins; however, this technology has yet to be leveraged for nMS.³³

The RapidFire (RF) robotic system enables the automated, high-throughput analysis of samples from a well-plate format and performs online sample cleanup, with standard RapidFire-MS workflows utilizing solid phase extraction (SPE) with a reversed phase (RP) cartridge before eluting samples onto the MS instrument.²³ RapidFire-MS has been widely deployed to perform high-throughput analysis of small molecules including peptides and lipids.^34–38 Experiments have also been performed with RapidFire-MS wherein denatured biomolecules were analyzed in as little as 20 s per sample.^39–41 Here, we present modifications to the standard RapidFire layout to accommodate nMS and CIU experiments, by using a SEC cartridge for online desalting and nondenaturing solvents for nMS. Furthermore, we characterize the ability of the RapidFire ion source to enable nMS and CIU data collection.^18,20,42 While other studies have integrated the Rapid Fire with an IM-q-TOFs, our study is the first to explore its application to nIM-MS.⁴³ We find that nMS experiments on the RapidFire require as little as 10 s per sample, CIU data can be collected in an automated fashion in 30 s per fingerprint, and we present CIU data for a variety of standard proteins and protein complexes. In addition, we collected native RapidFire-MS (nRapidFire-MS) and CIU data for biotherapeutics, including mAbs, as well as several oligonucleotides, suggesting the potential of nRapidFire-MS for enabling high-throughput CIU screens for biopharma applications. Overall, we find that nRapidFire-MS data produce ion CCSs without significant difference to infusion-based values, indicating that the ions produced by nRapidFire-MS share the same conformational states with those produced using standard nESI-MS sources. We conclude by discussing the future use of nRapidFire-MS for enabling high-throughput CIU screens of biotherapeutic targets as well as enabling the rapid collection of structural measurements, such as CCSs and CIU fingerprints in service of integrative structural biology campaigns.

MATERIALS AND METHODS

RapidFire Operation.

Samples were run using a RapidFire 400 instrument (Agilent Technologies, Santa Clara, CA). RapidFire pumps 1, 2, and 3 supplied 200 mM ammonium acetate. Experiments with streptavidin used 160 mM ammonium acetate and 40 mM triethylammonium acetate on pumps 1, 2, and 3 to accomplish charge reduction. The peristaltic pump supplied acetonitrile and water to the RapidFire. All solvents were of LC–MS grade and degassed prior to being loaded into the RapidFire. Protein and oligonucleotide stocks were pipetted directly onto a 96-well plate. Samples were drawn into the 35 μL sample loop and then loaded onto a cartridge packed with Sepharose 6 Fast Flow resin (Optimize Technologies, Oregon City, OR), before being analyzed by MS. Pump 1 was operated at 0.5 mL/min, and pumps 2 and 3 were set to 0.42 mL/min. Lower flow rates than typical were deployed to be compatible with a microelectrospray ionization source. The aspiration step was programmed to take 1.8 s with the cartridge wash taking 4.5 s, and the re-equilibration step was completed in 3 s, with the whole cycle completing in less than 10 s (Figure 1a). The sipper was washed with organic and aqueous solvent immediately before and after each sample run, and aqueous washes were conducted between each sip within a run, with discrete peaks in the chromatogram corresponding to solvent and sample injections (Figure S1). The plumbing was altered from the standard configuration with valve 2 ports 2 and 5 being reversed to allow for analytes to be introduced to the MS after being desalted on the SEC cartridge (Figures S2 and 1b).

Figure 1.

Overview of the RapidFire methodology for nMS (a). A schematic of the modified plumbing employed for nRapidFire-MS for online desalting with the SEC cartridge during the wash step (b). nRapidFire-MS data for insulin samples spiked into complex matrices were as follows: bovine serum (c) and 1 M NaCl (d).

nIM-MS and CIU.

Samples were eluted directly onto an Agilent 6560c using the micronebulizer (Agilent Technologies) source, which is more compatible with RapidFire flow rates than nESI. All nMS data in this manuscript were collected with the micronebulizer source. The micronebulizer source has been previously used to collect nMS data and has been demonstrated to be comparable to nESI-MS for nMS applications.²⁰ The following positive polarity ESI settings were used based on previous studies on the micronebulizer: transfer capillary voltage, 3 kV; fragmentor, 450 V; nozzle voltage, 2 kV; drying gas flow 5 L/min; drying gas temperature, 140–300 °C; sheath gas flow 11 L/min; and sheath gas temperature, 140 °C.²⁰ Additional tuning parameters for positive and negative polarity may be viewed in Tables S1 and S2. The drying gas temperature was adjusted largely based on the size of the biomolecules for effective desolvation. Proteins less than 65 kDa were sprayed at 140 °C drying gas temperature, while larger proteins were sprayed at 250 °C. RNA species were sprayed between 250 and 300 °C. The drift tube was operated under ambient temperature with a 18.5 V/cm gradient. The high-pressure funnel, ion trap funnel, and drift tube were operated with high purity N₂ and under pressures of 4.5 3.95, and 3.8 mbar, respectively. ^DTCCS_N2d were measured based on a single-field calibration with tune mix (Agilent Technologies), which is derived from the Mason-Schamp equation as described previously.⁴⁴ Mass spectra were visualized using MassHunter (Agilent Technologies) and mMass.^45–47

CIU has been extensively characterized on the 6560c.^18,20,42 Ions are unfolded by increasing the potential difference between the fragmentor lens and the capillary exit. When performed in N₂, protein and oligonucleotide ions can be successfully unfolded in the front funnel prior to IM separation. CIU voltage ramps were programmed using the time segment feature in MassHunter (Agilent Technologies), with the voltage ramp timed to run as the molecules eluted off the RapidFire. For mAb CIU, sulfur hexafluoride was doped into the drying gas at a 10% v/v concentration. CIU data were generated by plotting the ^DTCCS_N2d of the molecule as a function of the capillary exit voltage, referred to hereafter as the collision voltage. CIU data were plotted and analyzed using CIUSuite 2, which allows for the detection of features and CIU50s, which are the transitions between the features, in the data.¹⁷ Sample CIU plotting parameters are listed in Table S3. All CIU data were collected in triplicate and averaged in CIUSuite 2. Additional information regarding sample preparation, direct infusion procedures, and mAb stress experiments is available in the Supporting Information.

RESULTS AND DISCUSSION

Online Desalting by RapidFire-MS.

To evaluate the efficiency of SEC cartridges for online desalting in the context of nRapidFire-MS, we utilized insulin samples prepared by using a variety of different matrices containing a range of chemical interferents. Control insulin samples prepared in 200 mM ammonium acetate when analyzed using nRapidFire-MS produce insulin spectra exhibiting the same charge states detected by standard infusion nESI experiments⁴⁸ (Figure S3a). When insulin was prepared in bovine serum, desalted, and analyzed by nRapidFire-MS, we again detected a native-like charge state distribution, albeit detected with some residual noise from the serum sample matrix (Figure 1c). The same sample was then analyzed by direct infusion MS, and we observed no clear insulin signals (Figure S3b). Similar effects were observed for insulin prepared in 1 M NaCl (Figures 1d and S3c). When IM is employed to select only the drift time regions where insulin signal is observed, nRapidFire-MS data acquired from 1 M NaCl-containing buffer result in a mass spectrum with much reduced signal from the background matrix (Figure S3d). Finally, data acquired using nRapidFire-MS for insulin samples prepared using lower amounts of NaCl (5 mM) resulted in no observable salt cluster related noise, whereas direct injection of the same sample produced significant chemical noise signals related to NaCl cluster ions (Figures S3c,e,f). Taken together, our data illustrate the effectiveness and efficiency of SEC cartridge-based desalting, enabling nRapidFire-MS analysis of protein samples housed within a wide range of challenging matrices.

nRapidFire-MS of Standard Proteins.

To evaluate the performance of the nRapidFire-MS, we investigated CCSs and charge state distributions for protein standards using the ESI source conditions and flow rates used for our modified instrument platform. For example, nRapidFire-MS data collected for samples of myoglobin and bovine serum albumin (BSA) exhibit similar charge state distributions and CCSs when compared to data collected using standard nMS methods (Figure 2a–h). Notably, nRapidFire-MS data for myoglobin contain more prominent signal from salt clusters than the direct infusion data, while the nRapidFire-MS BSA data contain more signal from dimeric species than the direct infusion data. We also observed native-like charge state distributions for nRapidFire-MS data collected for proteins ranging from 5 to 150 kDa, including streptavidin, ADH, beta-lactoglobulin, and ConA tetramers (Figure S4) that are similar to other studies using standard nMS approaches.³³ Furthermore, the preservation of protein complexes, such as abovementioned tetramers, also demonstrate that the protein ions produced and analyzed by nRapidFire-MS adopt native-like structures in the gas phase.⁴⁹

Figure 2.

IM data for myoglobin collected by direct infusion (a) and nRapidFire-MS (b). Mass spectra for myoglobin collected by direct infusion (c) and nRapidFire-MS (d). IM data for bovine serum albumin (BSA) were collected by direct infusion (e) and nRapidFire-MS (f). Mass spectra for BSA were collected by direct infusion (g) and nRapidFire-MS (h). A bar chart depicting the relative standard deviation (RSD) (%) differences in ^DTCCS_N2d values between proteins collected with standard direct infusion approaches with proteins collected by nRapidFire-MS(i).

Despite the wide array of molecular weights surveyed in this report, we did not observe any molecular-weight-based differences in retention times for the biomolecules subjected to SEC cartridge-based desalting. We extended our nRapidFire-MS data set to include guanidinium transporter, an integral membrane protein, demonstrating that nRapidFire-MS is tolerant of the detergents commonly used for nMS of membrane proteins (Figure S4d). To further validate the native-like status of the ions produced by nRapidFire-MS, we recorded ^DTCCS_N2d values for all the model protein ions across all charge states observed. In all cases, when the native RapidFire ^DTCCS_N2 values were compared to published ^DTCCS_N2d values collected by standard nMS using nESI on the same instrument, these values were reproducible within 3% RSD in all cases (Table S4, Figure 2i).^18,42 However, we note that a comprehensive analysis of our current nRapidFire data set reveals that a greater degree of activation is observed for larger biomolecular ions than is detected for those that are smaller (Table S4). Altogether, these data strongly suggest that nRapidFire-MS is capable of producing native-like ions in a manner similar to standard nMS approaches (Figure 2i).

Automated CIU Using nRapidFire-MS.

In order to collect CIU data using nRapidFire-MS, voltage ramps were programmed to run as proteins eluted from native RapidFire. Complete voltage ramps were completed in 30 s, using 3 s per voltage step, representing a substantial increase in CIU throughput for drift tube-based methodologies described previously.^18,20,42 We collected CIU data for several standard proteins and protein complexes in this high-throughput mode, with three replicates per protein taken in a total of 1.5 min, including streptavidin, BSA, and myoglobin, and these data were then compared to CIU data collected by the standard direct infusion μESI source. For CIU data recorded for 16+ BSA, we observe four features in both our direct infusion and nRapidFire-CIU fingerprints, similar to prior CIU data reported for these ions (Figure 3a,b). Despite the higher flow rates employed by nRapidFire-MS, we found an overall RSD of 3% for the CIU features recorded. Likewise, CIU50s values extracted from nRapidFire-MS are similar to CIU data collected by standard nMS, except for the third transition being slightly destabilized in the nRapidFire-CIU data (Figures S5a and S6a, Tables S5 and S6). Similar trends were observed for nRapidFire-CIU data collected for 11+ streptavidin tetramer ions. CIU features recorded using native RapidFire and direct infusion for the tetramer were highly similar, exhibiting an RSD within 1%, including a transient intermediate feature observed at 2300 Ų, while the CIU50 values were all within standard deviation (Figures 3c,d, S5b, S6b, and Tables S5 and S6). Similarly, we observe strong correlation between CIU data collected in nRapidFire and standard infusion mode for myoglobin 8+ ions, again producing an interfingerprint RSD of 1% RSD (Figure 3,e,f, S5c and S6c, Tables S4 and S6). Our nRapidFire-CIU data set includes proteins with molecular weights ranging from 8 to 150 kDa (Figure S7). The similarity of the unfolding trajectories between our fast nRapidFire-CIU and standard infusion CIU data further underscores that nRapidFire-MS produces native-like ions in a manner similar to standard nMS workflows while simultaneously enabling high-throughput nMS and CIU data acquisition.

Figure 3.

CIU data collected with direct infusion for BSA 16+ (a), myoglobin 8+ (c), and streptavidin 11+ (e). RapidFire-CIU data collected with BSA 16+ (b), myoglobin 8+ (d), and streptavidin 11+ (f).

nRapidFire-MS of Protein Biotherapeutics.

Given the ability of nRapidFire-MS to perform automated, rapid nMS experiments with proteins and protein complexes, we then moved to extend nRapidFire-MS to mAbs. As discussed above for other model proteins, our nRapidFire-MS data for mAbs include similar charge state distributions to those observed in data acquired using standard nMS approaches, while also resolving same mAb glycoform populations (Figure 4a–d). Some evidence of charge stripping is present in both data sets, as is common for highly charged analytes, such as mAbs.¹⁸ Overall, our nRapidFire-MS data set includes six mAbs, including both model antibodies and FDA-approved biotherapeutics, all of which produce similar nRapidFire-MS data (Figure S8).

Figure 4.

IM data for NIST mAB collected by direct infusion (a) and nRapidFire-MS (b). Mass spectra for NIST mAb collected by direct infusion (c) and nRapidFire-MS (d) with insets depicting the glycoform populations observed. IM data for an siRNA duplex were collected by direct infusion (d) and nRapidFire-MS (e). Mass spectra for the siRNA duplex were collected by direct infusion (f) and nRapidFire-MS (g). RapidFire-CIU data for 27+ NIST mAb (i) and the 7+ siRNA duplex (j).

In order to generate nRapidFire-CIU for mAbs, we introduced SF₆ to the front funnel region of the 6560c platform to impart sufficient ion activation for CIU. Our data reveal a complete CIU fingerprint for NIST mAb across several charge states (Figures 4i and S9). The same features can be observed in direct infusion CIU data, of which the feature at 9500 Ų appears with lower intensity, suggesting that nRapidFire-CIU produces marginally increased activation (Figure S10). When comparing the CCSs of the CIU features captured in our 27+ NIST mAb data acquired through nRapidFire-MS and standard nMS conditions, we note that all features are within 3% RSD (Figure S10). High-throughput nRapidFire-CIU data were also collected on 39+ NIST mAb dimer ions, suggesting that nRapidFire-MS operation can extend to 300 kDa, and be utilized to evaluate mAb degradation in process development.⁵⁰ (Figure S11a). A broader data set including mAb fragments (Figures S11b,c and S12), biotherapeutic mAbs (Figure S13), and deglycosylated mAbs^51,52 (Figure S8,S9d–g and S12d–f) all indicate the strong similarities between nRapidFire-CIU and standard infusion-mode CIU data. An exception to this statement is the CIU50 of deglycosylated and intact mAbs, which reveal statistically significant differences (p < 0.05) for the 26+ of Sigma mAb, wherein the deglycosylated form, it was destabilized when compared to intact NIST mAb (Figure S14a). Additional nRapidFire-MS studies targeting pH stressed mAbs were able to capture statistically significant differences (p < 0.05) for CIU50s between acidic pH stressed conditions and standard conditions, which was consistent with direct infusion data for the same samples (Figure S14b and Figure S15).

nRapidFire-MS of Oligonucleotides.

Prior reports have demonstrated the utility of nMS for the study of oligonucleotide structure, sequence, and modification state.^2,8 Here, we collected nRapidFire-MS data for a 16 kDa siRNA duplex and a 25 kDa mitochondrial ^LEU(UUR)tRNA (mt-tRNA) (Figures 4f,h and S16). Notably, RNA samples required greater drying gas temperatures when compared to protein samples of similar molecular weight with the RNA samples requiring 250–300 °C drying gas temperatures. As observed in our protein nRapidFire-MS data, when compared to direct infusion data, nRapidFire-MS for the siRNA duplex exhibits similar charge state distributions and IM drift times, suggesting that native RapidFire can be used for the nMS analysis of oligonucleotide samples (Figure 4e–h). In fact, the nRapidFire-MS data are of slightly higher mass resolution (measured at FWHM) than the direct infusion data, with values of ~2400 measured for nRapidFire-MS data and ~1800 for direct infusion data, each recorded for the 7+ charge state. Additionally, we collected high-throughput nRapidFire-CIU data, observing a compaction of approximately 115 Ų for 7+ siRNA, a value within 3% of the direct infusion CIU data (Figures 4j and S17). When we extended our comparisons of nRapidFire-MS and direct infusion CIU data for other oligonucleotide ions, similar trends were observed for 8+ and 9+ siRNA and 9+ mt-tRNA ions (Figure S18).

Negative polarity data were also collected as it is more typical for RNA molecules to be analyzed in this polarity due to their negative charge in solution.⁵³ Negative polarity nRapidFire-MS data for the siRNA duplex exhibit a similar charge state distribution to the positive polarity data (Figure S18a). Likewise, RapidFire-CIU data for the 7– charge state of that system also demonstrate a compaction of 60 Ų upon collisional activation, similar to what was observed for the RapidFire-CIU data of 7+ charge state. Taken together, our nRapidFire-MS data rapidly collected over multiple oligonucleotides highlight the versatility of this platform for automated, high-throughput nMS, and CIU assay development in both polarity modes.

CONCLUSIONS

In this study, we demonstrate that nRapidFire-MS can be deployed to collect automated nIM-MS and CIU data on a subminute time scale, with full CIU fingerprints collected in 30 s. Online desalting using nRapidFire-MS significantly reduces the time required for sample preparation procedures from nearly half an hour to seconds. The flow rates used in our nRapidFire-MS experiments are low enough to be compatible with a fixed micronebulizer source, allowing sample introduction to be automated and reducing inefficiencies caused by single use nESI emitters. The nRapidFire-MS approach described here can be paired with any MS system as long as the ion source used is compatible with the flow rates evaluated in this report. Our nRapidFire-MS data of nearly identical charge states and CCS values indicate that the ions produced in our experiments are highly similar to those produced using conventional nESI nMS. The ^DTCCS_N2d values recorded were highly reproducible for biomolecules surveyed across all RapidFire injections, suggesting that the biomolecules analyzed were not denatured during SEC-based desalting. Furthermore, our data demonstrate that nRapidFire-MS can be employed to conduct high-throughput nMS and CIU analyses of diverse biomolecules of interest. Given the ability to store multiple plates under temperature-controlled conditions within the RapidFire platform, our nRapidFire-MS methods could be leveraged in the future to perform extensive nMS screens, with the potential to complete a 96-well plate in as little as 15 min under optimal conditions.

We envision that nRapidFire-MS could become a transformative tool in the pharmaceutical sciences more generally as the methodology described herein can be used to collect high-throughput CIU data for a variety of therapeutic biomolecules such as mAbs and siRNA. RapidFire-CIU could also be leveraged in biopharma to conduct high-throughput drug-binding assays, wherein CIU could be deployed to quickly identify potential drug candidates and characterize them based on their mechanism of action.^17,32 Beyond biopharma, nRapidFire-MS could be of wide interest in structural biology research more generally by improving the throughput and efficiency of routine nMS analyses. nRapidFire-MS could even be deployed to facilitate the creation of a CIU database of the standard systems of interest. In removing some of the bottlenecks around nMS experimentation, nRapidFire-MS also makes it easier for nonexpert groups to perform nMS experimentation.

Our current nRapidFire-MS method does present some limitations; for example, each analysis requires 35 μL of the sample. However, adjustments to the connective tubing used in the RapidFire can conceivably reduce the per-sample volume requirements to 10 μL. Additionally, CIU on the 6560c instrument is currently limited by the scan speeds of 3 s per voltage step, but this could be surmounted by changes in instrument control software. Overall, our evidence suggests that nRapidFire-MS results in a larger degree of ion activation when compared with more standard nMS approaches in some cases. Such differences are likely related to challenges that we encountered in the optimization of ESI source conditions capable of accommodating the higher flow rates employed for nRapidFire-MS. It is important to note that these differences in ^DTCCS_N2d are of a similar magnitude to other studies using higher flow rates with native MS,^29,54 suggesting a linked mechanism. Future work in this space should examine how higher flow rates in solution may influence the gas phase activation of biomolecules in nMS experiments. In addition, the resolution observed for MS data acquired by nRapidFire-MS is somewhat lower overall when compared to data acquired by conventional nMS for large protein complexes. Further optimization may be required to balance the production of protein ions exhibiting both native-like sizes and more well-resolved MS features. Overall, nRapidFire-MS is a promising methodology that can be deployed to collect nMS and CIU data in an automated, high-throughput compatible manner for a variety of biomolecules. The use of the nRapidFire-MS as a bona fide high-throughput and automated technology for nMS research has the potential for transformative impacts in the deployment of nMS research across the biosciences.