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Recombinant adeno-associated virus (rAAV) vectors are often produced in HEK293 or Spodoptera frugiperda (Sf)-based cell lines. We compared expression profiles of "oversized" (∼5,000 bp) and "standard-sized" (4,600 bp) rAAV5-human α1-antitrypsin (rAAV5-hA1AT) vectors manufactured in HEK293 or Sf cells and investigated molecular mechanisms mediating expression decline. C57BL/6 mice received 6 × 10 13 vg/kg of vector, and blood and liver samples were collected through week 57. For all vectors, peak expression (weeks 12-24) declined by 50% to week 57. For Sf- and HEK293-produced oversized vectors, serum hA1AT was initially comparable, but in weeks 12-57, Sf vectors provided significantly higher expression. For HEK293 oversized vectors, liver genomes decreased continuously through week 57 and significantly correlated with A1AT protein. In RNA-sequencing analysis, HEK293 vector-treated mice had significantly higher inflammatory responses in liver at 12 weeks compared with Sf vector- and vehicle-treated mice. Thus, HEK293 vector genome loss led to decreased transgene protein. For Sf-produced vectors, genomes did not decrease from peak expression. Instead, vector genome accessibility significantly decreased from peak to week 57 and correlated with transgene RNA. Vector DNA interactions with active histone marks (H3K27ac/H3K4me3) were significantly reduced from peak to week 57, suggesting that epigenetic regulation impacts transgene expression of Sf-produced vectors., Competing Interests: Declaration of interests B.H., A.M.I., L.Z., B.Y., C.K.K., L.X., C.-R.S., R.M., T.B., N.L.M., M.X.D., E.P., V.S.B., S. Bullens, S. Bunting, and S.F. are employees and stockholders of BioMarin Pharmaceutical Inc. S.S. and R.D.A. are former employees of BioMarin Pharmaceutical Inc. and may hold stock., (Copyright © 2022 BioMarin Pharmaceutical Inc. Published by Elsevier Inc. All rights reserved.)

Quantifying the composition of viral vectors used in vaccine development and gene therapy is critical for assessing their functionality. Adeno-associated virus (AAV) vectors, which are the most widely used viral vectors for in vivo gene therapy, are typically characterized using PCR, ELISA, and analytical ultracentrifugation which require laborious protocols or hours of turnaround time. Emerging methods such as charge-detection mass spectroscopy, static light scattering, and mass photometry offer turnaround times of minutes for measuring AAV mass using optical or charge properties of AAV. Here, we demonstrate an orthogonal method where suspended nanomechanical resonators (SNR) are used to directly measure both AAV mass and aggregation from a few microliters of sample within minutes. We achieve a precision near 10 zeptograms which corresponds to 1% of the genome holding capacity of the AAV capsid. Our results show the potential of our method for providing real-time quality control of viral vectors during biomanufacturing.

Adeno associated virus (AAV) capsids are a leading modality for in vivo gene delivery. Complete and precise characterization of capsid particles, including capsid and vector genome concentration, is necessary to safely and efficaciously dose patients. Size exclusion chromatography (SEC) coupled to multiangle light scattering (MALS) offers a straightforward approach to comprehensively characterize AAV capsids. The current study demonstrates that this method provides detailed AAV characterization information, including but not limited to aggregation profile, size-distribution, capsid content, capsid molar mass, encapsidated DNA molar mass, and total capsid and vector genome titer. Currently, multiple techniques are required to generate this information, with varying accuracy and precision. In the current study, a new series of equations for SEC-MALS are used in tandem with intrinsic properties of the capsids and encapsidated DNA to quantify multiple physical AAV attributes in one 20-min run with minimal sample manipulation, high accuracy, and high precision. These novel applications designate this well-established method as a powerful tool for product development and process analytics in future gene therapy programs.

We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R (2)), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events.