Improving Analytical Characterization of Glycoconjugate Vaccines through Combined High-Resolution MS and NMR: Application to Neisseria meningitidis Serogroup B Oligosaccharide-Peptide Glycoconjugates

Conjugate vaccines are highly heterogeneous in terms of glycosylation sites and linked oligosaccharide length. Therefore, the characterization of conjugate vaccines’ glycosylation state is challenging. However, improved product characterization can lead to enhancements in product control and product quality. Here, we present a synergistic combination of high-resolution mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) for the analysis of glycoconjugates. We use the power of this strategy to characterize model polysaccharide conjugates and to demonstrate a detailed level of glycoproteomic analysis. These are first steps on model compounds that will help untangle the details of complex product characterization in conjugate vaccines. Ultimately, this strategy can be applied to enhance the characterization of polysaccharide conjugate vaccines. In this study, we lay the groundwork for the analysis of conjugate vaccines. To begin this effort, oligosaccharide–peptide conjugates were synthesized by periodate oxidation of an oligosaccharide of a defined length, α,2–8 sialic acid trimer, followed by a reductive amination, and linking the trimer to an immunogenic peptide from tetanus toxoid. Combined mass spectrometry and nuclear magnetic resonance were used to monitor each reaction and conjugation products. Complete NMR peak assignment and detailed MS information on oxidized oligosialic acid and conjugates are reported. These studies provide a deeper understanding of the conjugation chemistry process and products, which can lead to a better controlled production process

All seven aspects of HITS related to impact and transformativeness.

<p>The figure shows the partial correlations between the metrics for the aspects of transformative research and the overall metrics for transformativeness and impact across field-period pairs after eliminating variation across field and time (that is, time and field fixed effects).</p

High-impact and transformative science (HITS) metrics: Definition, exemplification, and comparison

<div><p>Countries, research institutions, and scholars are interested in identifying and promoting high-impact and transformative scientific research. This paper presents a novel set of text- and citation-based metrics that can be used to identify high-impact and transformative works. The 11 metrics can be grouped into seven types: Radical-Generative, Radical-Destructive, Risky, Multidisciplinary, Wide Impact, Growing Impact, and Impact (overall). The metrics are exemplified, validated, and compared using a set of 10,778,696 MEDLINE articles matched to the Science Citation Index Expanded^TM. Articles are grouped into six 5-year periods (spanning 1983–2012) using publication year and into 6,159 fields constructed using comparable MeSH terms, with which each article is tagged. The analysis is conducted at the level of a field-period pair, of which 15,051 have articles and are used in this study. A factor analysis shows that transformativeness and impact are positively related (<i>ρ =</i> .<i>402</i>), but represent distinct phenomena. Looking at the subcomponents of transformativeness, there is no evidence that transformative work is adopted slowly or that the generation of important new concepts coincides with the obsolescence of existing concepts. We also find that the generation of important new concepts and highly cited work is more risky. Finally, supporting the validity of our metrics, we show that work that draws on a wider range of research fields is used more widely.</p></div

FCiteN related to impact and transformativeness.

<p>The figure shows the partial correlation between the individual metrics for impact and the overall metrics for transformativeness and impact across field-period pairs after eliminating variation across field and time (that is, time and field fixed effects).</p

Ranking of fields in terms of impact and transformativeness across all periods (1982–2012).

<p>Field size determined by the number of (weighted) articles across all periods. Research on stem cells is shown in red.</p

Exemplary depiction of field-period pairs.

<p>Exemplary depiction of field-period pairs.</p

Classification of scientific work by radicalness and impact, with examples.

<p>Classification of scientific work by radicalness and impact, with examples.</p

Summary statistics for all metrics for time periods 1983–1987, …, 2008–2012 and all MESH4 fields in MEDLINE.

<p>Summary statistics for all metrics for time periods 1983–1987, …, 2008–2012 and all MESH4 fields in MEDLINE.</p

Results from a factor analysis of six aspects of HITS.

<p>The figure reports factor loadings on each aspect of transformative research from a factor analysis. The factor loadings indicate the extent to which the transformativeness metric loads on the (first) factor for each aspect of transformative research (excluding impact, which is treated separately).</p

Article counts.

<p>Article counts.</p