Search

Your search keyword '"Boggio K"' showing total 4 results
Start Over Author "Boggio K" Publication Year Range Last 10 years
4 results on '"Boggio K"'

1. RNA sequencing and proteomics approaches reveal novel deficits in the cortex of Mecp2-deficient mice, a model for Rett syndrome.

Author

Pacheco, Natasha L., Heaven, M. R., Holt, Leanne M., Crossman, D. K., Boggio, K. J., Shaffer, S. A., Flint, D. L., Olsen, Michelle L., Pacheco, Natasha L., Heaven, M. R., Holt, Leanne M., Crossman, D. K., Boggio, K. J., Shaffer, S. A., Flint, D. L., and Olsen, Michelle L.

Abstract

BACKGROUND: Rett syndrome (RTT) is an X-linked neurodevelopmental disorder caused by mutations in the transcriptional regulator MeCP2. Much of our understanding of MeCP2 function is derived from transcriptomic studies with the general assumption that alterations in the transcriptome correlate with proteomic changes. Advances in mass spectrometry-based proteomics have facilitated recent interest in the examination of global protein expression to better understand the biology between transcriptional and translational regulation. METHODS: We therefore performed the first comprehensive transcriptome-proteome comparison in a RTT mouse model to elucidate RTT pathophysiology, identify potential therapeutic targets, and further our understanding of MeCP2 function. The whole cortex of wild-type and symptomatic RTT male littermates (n = 4 per genotype) were analyzed using RNA-sequencing and data-independent acquisition liquid chromatography tandem mass spectrometry. Ingenuity® Pathway Analysis was used to identify significantly affected pathways in the transcriptomic and proteomic data sets. RESULTS: Our results indicate these two "omics" data sets supplement one another. In addition to confirming previous works regarding mRNA expression inMecp2-deficient animals, the current study identified hundreds of novel protein targets. Several selected protein targets were validated by Western blot analysis. These data indicate RNA metabolism, proteostasis, monoamine metabolism, and cholesterol synthesis are disrupted in the RTT proteome. Hits common to both data sets indicate disrupted cellular metabolism, calcium signaling, protein stability, DNA binding, and cytoskeletal cell structure. Finally, in addition to confirming disrupted pathways and identifying novel hits in neuronal structure and synaptic transmission, our data indicate aberrant myelination, inflammation, and vascular disruption. Intriguingly, there is no evidence of reactive gliosis, but instead, gene, protein, and pat

Published
2017
Full Text
View/download PDF

3. Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.

Author

Mouchahoir T, Schiel JE, Rogers R, Heckert A, Place BJ, Ammerman A, Li X, Robinson T, Schmidt B, Chumsae CM, Li X, Manuilov AV, Yan B, Staples GO, Ren D, Veach AJ, Wang D, Yared W, Sosic Z, Wang Y, Zang L, Leone AM, Liu P, Ludwig R, Tao L, Wu W, Cansizoglu A, Hanneman A, Adams GW, Perdivara I, Walker H, Wilson M, Brandenburg A, DeGraan-Weber N, Gotta S, Shambaugh J, Alvarez M, Yu XC, Cao L, Shao C, Mahan A, Nanda H, Nields K, Nightlinger N, Niu B, Wang J, Xu W, Leo G, Sepe N, Liu YH, Patel BA, Richardson D, Wang Y, Tizabi D, Borisov OV, Lu Y, Maynard EL, Gruhler A, Haselmann KF, Krogh TN, Sönksen CP, Letarte S, Shen S, Boggio K, Johnson K, Ni W, Patel H, Ripley D, Rouse JC, Zhang Y, Daniels C, Dawdy A, Friese O, Powers TW, Sperry JB, Woods J, Carlson E, Sen KI, Skilton SJ, Busch M, Lund A, Stapels M, Guo X, Heidelberger S, Kaluarachchi H, McCarthy S, Kim J, Zhen J, Zhou Y, Rogstad S, Wang X, Fang J, Chen W, Yu YQ, Hoogerheide JG, Scott R, and Yuan H

Subjects
Mass Spectrometry methods, Peptide Mapping methods, Quality Control, Benchmarking, Proteins
Abstract

The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment.

Published
2022
Full Text
View/download PDF

4. New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study.

Author

Mouchahoir T, Schiel JE, Rogers R, Heckert A, Place BJ, Ammerman A, Li X, Robinson T, Schmidt B, Chumsae CM, Li X, Manuilov AV, Yan B, Staples GO, Ren D, Veach AJ, Wang D, Yared W, Sosic Z, Wang Y, Zang L, Leone AM, Liu P, Ludwig R, Tao L, Wu W, Cansizoglu A, Hanneman A, Adams GW, Perdivara I, Walker H, Wilson M, Brandenburg A, DeGraan-Weber N, Gotta S, Shambaugh J, Alvarez M, Yu XC, Cao L, Shao C, Mahan A, Nanda H, Nields K, Nightlinger N, Barysz HM, Jahn M, Niu B, Wang J, Leo G, Sepe N, Liu YH, Patel BA, Richardson D, Wang Y, Tizabi D, Borisov OV, Lu Y, Maynard EL, Gruhler A, Haselmann KF, Krogh TN, Sönksen CP, Letarte S, Shen S, Boggio K, Johnson K, Ni W, Patel H, Ripley D, Rouse JC, Zhang Y, Daniels C, Dawdy A, Friese O, Powers TW, Sperry JB, Woods J, Carlson E, Sen KI, Skilton SJ, Busch M, Lund A, Stapels M, Guo X, Heidelberger S, Kaluarachchi H, McCarthy S, Kim J, Zhen J, Zhou Y, Rogstad S, Wang X, Fang J, Chen W, Yu YQ, Hoogerheide JG, Scott R, and Yuan H

Abstract

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results