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Powers, J. B.

Publications and source records attributed to Powers, J. B..

2 recordsLinked to original sources

Characterizing Adeno-Associated Virus Capsids with both Denaturing and Intact Analysis Methods

Adeno-associated virus (AAV) capsids are among the leading gene delivery platforms used to treat a vast array of human diseases and conditions. AAVs exist in a variety of serotypes due to differences in viral protein (VP) sequences, with distinct serotypes targeting specific cells and tissues. As the utility of AAVs in gene therapy increases, ensuring their specific composition is imperative for correct targeting and gene delivery. From a quality control perspective, current analytical tools are limited in their selectivity for viral protein (VP) subunits due to their sequence similiaries, instrumental difficulties in assessing the large molecular weights of intact capsids, and the uncertainity in distinguishing empty and filled capsids. To address these challenges, we combine two distinct analytical workflows that assess the intact capsids and VP subunits separately. First, charge detection-mass spectrometry (CD-MS) was applied for characterization of the intact capsids and then liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) separations were used for capsid denaturing measurements. This multi-method combination was applied to 3 AAV serotypes (AAV2, AAV6, and AAV8) to evaluate their intact empty and filled capsid ratios and then examine the distinct VP sequences and modifications present.

biochemistry↗

Rumen Bacteria and Serum Metabolites Predictive of Feed Efficiency Phenotypes in Beef Cattle

The rumen microbiome is critical in ruminant nutrition and contributes to nutrient utilization and feed efficiency in cattle. Therefore, the objective of this study was to interrogate microbial and biochemical factors affecting divergences in feed efficiency in Angus steers using 16S amplicon sequencing and untargeted metabolomics. Average residual feed intake (RFI) was calculated, and steers were divided into low- and high-RFI groups. Features were ranked in relation to RFI through supervised machine learning on microbial and metabolite compositions. Residual feed intake was associated with several attributes of the rumen bacterial community. Low-RFI steers were associated with decreased bacterial - (P=0.03) and {beta}-diversity (P<0.001). Several serum metabolites were associated with RFI. Based on fold change (high/low RFI), low-RFI steers had greater abundances of pantothenate (P=0.02). Machine learning on RFI was predictive of both serum metabolomic signature and rumen bacterial composition (AUC [&ge;]0.7). Log-ratio proportions of the bacterial classes Flavobacteriia over Fusobacteriia were enriched in low-RFI steers (F=6.8, P=.01). Greater proportions of pantothenate-producing bacteria, such as Flavobacteriia, and/or reductions in Fusobacteriia may result in improved nutrient utilization in low-RFI steers. Pantothenate and Flavobacteriia may serve as potentially novel biomarkers to assess or predict feed efficiency in Angus steers.

microbiology↗