Charge detection mass spectrometry (CDMS) was used to analyze recombinant adeno-associated virus serotype 8 (rAAV8) vectors after incubation at elevated temperatures. rAAV8 vectors with a range of genomes of interest (GOIs) from 2.22 to 4.84 kb were investigated. For the shorter GOIs, GOI release occurred at surprisingly low temperatures (15 min at 45°C for cytomegalovirus [CMV]-GFP). The released DNA and intermediates with the GOI extruded from the capsid were detected. The temperature required to release the short GOIs is well below the 65°C incubation temperature required to disassemble the empty rAAV8 capsid. The temperature for GOI release increased with its GOI length. With the longer GOIs, the GOI stabilized the capsid so that it remained intact under conditions that would disassemble the empty particle. After incubation at 65°C, the main species in the CDMS mass distributions for the longer GOIs was the vector with the GOI. However, for GOIs longer than the wild-type genome (∼4.7 kb), the stability diminished, and genome release occurred at a lower temperature. Heterogeneous DNA fragments from the host cells or plasmids is released at a lower temperature than the longer GOIs, suggesting that the GOIs have a feature that resists early release.

Heterogeneity usually restricts conventional mass spectrometry to molecular weights less than around a megadalton. As a single-particle technique, charge detection mass spectrometry (CDMS) overcomes this limitation. In CDMS, the mass-to-charge (m/z) ratio and charge are measured simultaneously for individual ions, giving a direct mass measurement for each ion. Recent applications include the analysis of viruses, virus-like particles, vaccines, heavily glycosylated proteins, and gene therapy vectors.

Information systems used by platform trials should handle changes that are not predefined. Unfortunately, the technical architecture of most existing clinical data management systems (CDMS) do not support changes to be incorporated into an ongoing trial. Adaptive clinical trials need advanced architectural solutions setup to enable biomarker stratification and enrichment strategy necessary for the adaptive clinical trial operation. This short paper presents the microservices-based architecture solution that is used to run and support the adaptive RECORDS-Trial.

Recombinant adeno-associated virus (rAAV) has emerged as an important gene therapy vector with many clinical trials currently in progress. Analytical characterization and quantitation of particle content remain challenges in both the development and production of rAAV vectors. In this study, charge detection mass spectrometry (CDMS) and gel electrophoresis are used to characterize the DNA content of recombinant AAV8 (rAAV8) vectors with a wide range of target genome sizes. We show that the differences between the masses of empty particles and particles with the genome of interest (GOI) are correlated with the expected genome mass. A small systematic deviation (around 2%) is attributed to the packaging of counterions along with the DNA. In addition to the GOI, a broad distribution of heterogeneous DNA is packaged. The distribution peaks are close to the packaging capacity of the rAAV8 vectors. There is also evidence for the co-packaging of small DNA fragments along with the GOI. Finally, we present evidence that incubation at an elevated temperature can reduce the heterogeneity of the packaged DNA. Taken together, these results show that CDMS is a viable tool for characterization of the packaged genome.

Noroviruses cause immense sporadic gastroenteritis outbreaks worldwide. Emerging genotypes, which are divided based on the sequence of the major capsid protein VP1, further enhance this public threat. Self-assembling properties of the human norovirus major capsid protein VP1 are crucial for using virus-like particles (VLPs) for vaccine development. However, there is no vaccine available yet. Here, VLPs from different variants produced in insect cells were characterized in detail using a set of biophysical and structural tools. We used native mass spectrometry, gas-phase electrophoretic mobility molecular analysis, and proteomics to get clear insights into particle size, structure, and composition, as well as stability. Generally, noroviruses have been known to form mainly T = 3 particles. Importantly, we identified a major truncation in the capsid proteins as a likely cause for the formation of T = 1 particles. For vaccine development, particle production needs to be a reproducible, reliable process. Understanding the underlying processes in capsid size variation will help to produce particles of a defined capsid size presenting antigens consistent with intact virions. Next to vaccine production itself, this would be immensely beneficial for bio-/nano-technological approaches using viral particles as carriers or triggers for immunological reactions.

In this paper, the slice-within-Gibbs sampler has been introduced as a method for estimating cognitive diagnosis models (CDMs). Compared with other Bayesian methods, the slice-within-Gibbs sampler can employ a wide-range of prior specifications; moreover, it can also be applied to complex CDMs with the aid of auxiliary variables, especially when applying different identifiability constraints. To evaluate its performances, two simulation studies were conducted. The first study confirmed the viability of the slice-within-Gibbs sampler in estimating CDMs, mainly including G-DINA and DINA models. The second study compared the slice-within-Gibbs sampler with other commonly used Markov Chain Monte Carlo algorithms, and the results showed that the slice-within-Gibbs sampler converged much faster than the Metropolis-Hastings algorithm and more flexible than the Gibbs sampling in choosing the distributions of priors. Finally, a fraction subtraction dataset was analyzed to illustrate the use of the slice-within-Gibbs sampler in the context of CDMs.

Weighing single ions with charge detection mass spectrometry (CDMS) makes it possible to obtain the masses of molecules of essentially unlimited size even in highly heterogeneous samples, but producing a mass histogram that is representative of all of the components in a mixture requires substantial measurement time. Multiple ions can be trapped to reduce analysis time but ion signals can overlap. To determine the maximum gains in analysis speed possible with current instrumentation with multiple ion trapping, simulations calculating the frequency and overlap rate of ions with different mass, charge, and energy ranges were performed. For an analyte with a broad mass distribution, such as long chain polyethylene glycol (PEG, 8 MDa), gains in analysis speed of up to 160 times that of prior CDMS experiments are possible. For signals from homogeneous samples, ions with the same m/z have frequencies that overlap and interfere, reducing the effectiveness of multiplexing in experiments where ions have the same energy per charge. We show that by maximizing the decoupling of ion m/z from frequency using a broad range of ion energies, the rate of signal overlap is significantly reduced making it possible to trap more ions. Under optimum decoupling conditions, a measurement speed nearly 50 times greater than that of prior CDMS experiments is possible for RuBisCO (517 kDa). The reduction in overlap due to decoupling also results in more accurate quantitation in samples that contain multiple analytes with different concentrations.

Charge detection mass spectrometry (CDMS) is a single-particle technique where the masses of individual ions are determined by simultaneously measuring their mass-to-charge ratio (m/z) and charge. Ions are usually trapped inside an electrostatic linear ion trap (ELIT) where they oscillate back and forth through a detection cylinder, generating a periodic signal that is analyzed by fast Fourier transforms. The oscillation frequency is related to the ion\'s m/z, and the magnitude is related to the ion\'s charge. In early work, multiple ion trapping events were discarded because there was a question about whether ion-ion interactions affected the results. Here, we report trajectory calculations performed to assess the influence of ion-ion interactions when multiple highly charged ions are simultaneously trapped in an ELIT. Ion-ion interactions cause trajectory and energy fluctuations that lead to variations in the oscillation frequencies that in turn degrade the precision and accuracy of the m/z measurements. The peak shapes acquire substantial high and low m/z tails, and the average m/z shifts to a higher value as the number of trapped ions increases. The effects of the ion-ion interactions are proportional to the product of the charges and the square root of the number of trapped ions and depend on the ions\' m/z distribution. For the ELIT design examined here, ion-ion interactions limit the m/z resolving power to several hundred for a typical homogeneous ion population.

Charge detection mass spectrometry (CDMS) is an important tool for measuring mass distributions for high mass samples and heterogeneous mixtures. In CDMS, single ions are trapped and their m/z and charge are measured simultaneously. As a single particle technique, the average signal must be optimized to maximize the number of single ion trapping events. If the average signal is too small, most of the trapping events will be empty, and if the average signal is too large, most of the trapping events will contain multiple ions. In recent embodiments, the time domain signal from the trapped ion is analyzed by fast Fourier transforms. The analysis time is much longer that the data collection time which precludes real-time optimization of the experimental conditions. In this paper, we describe the implementation of CDMS with real-time analysis. Processing the data in real time allows the average signal intensities to be dynamically optimized to maximize the number of single ion trapping events. Real-time analysis also allows the experimental settings to be optimized in a timely manner to target specific mass regimes to maximize the useful information content of the measurements. Graphical Abstract .

A method to correct for the effect of ion energy on charge measurements of individual ions trapped and weighed with charge detection mass spectrometry (CDMS) is demonstrated. Ions with different energies induce different signal patterns inside an electrostatic ion trap. The sum of the amplitudes of the fundamental and second harmonic frequencies in the Fourier transform of the induced signal, which has been used to obtain the ion charge, depends on both ion energy and charge. The amplitudes of the fundamental frequencies of ions increase over time as ions lose energy by collisions with background gas and solvent loss from larger ions. Model ion signals are simulated with the same time-domain amplitude at different energies and frequencies and the resulting fundamental frequency amplitudes are used to normalize real ion signals for energy and frequency effects. The fundamental frequency amplitude decreases dramatically below 20 kHz and increases by ~ 17% from the highest energy to lowest energy that is stable with a given trap potential at all frequencies. Normalizing the fundamental frequency amplitude with the modeled amplitudes removes the systematic changes in the charge measurement of polyethylene glycol (PEG) and other ions and makes it possible to signal average the amplitude over long times, which reduces the charge uncertainty to 0.04% for a PEG ion for a 500-ms measurement. This method improves charge measurement accuracy and uncertainty, which are important for high-accuracy mass measurement with CDMS. Graphical abstract ᅟ.