Glycopeptide characterization of Sf9-derived SARS-CoV-2 spike protein recombinant vaccine candidates expedited by the use of glycopeptide libraries.

RATIONALE: We report the N-glycosylation pattern of Sf9 insect cell-derived recombinant spike proteins being developed as candidate vaccine antigens for SARS-CoV-2 (COVID-19) (Sanofi). The method has been optimised to produce peptides with single, isolated glycosylation sites using multiple protease digests. The development and use of glycopeptide libraries from previous developmental phases allowed for faster analysis than processing datasets from individual batches from first principles. METHODS: Purified spike proteins were reduced, alkylated, and digested with proteolytic enzymes. Three different protease digests were utilised to generate peptides with isolated glycosylation sites. The glycopeptides were then analysed using a Waters Q-TOF while using a data-dependent acquisition mass spectrometry experiment. Glycopeptide mapping data processing and glycan classification were performed using Genedata Expressionist via a specialised workflow that used libraries of previously detected glycopeptides to greatly reduce processing time. RESULTS: Two different spike proteins from six manufacturers were analysed. There was a strong similarity at each site across batches and manufacturers. The majority of the glycans present were of the truncated class, although at sites N61, N234, and N717/714 high mannose structures were dominant and at N1173/1170 aglycosylation was dominant for both variant proteins. A comparison was performed on a commercially available spike protein and our results were found to be similar to those of earlier reports. CONCLUSIONS: Our data clearly show that the overall glycosylation pattern of both spike protein variants was highly similar from batch to batch, and between materials produced at different manufacturing facilities. The use of our glycopeptide libraries greatly expedited the generation of site-specific glycan occupancy data for a large glycoprotein. We compared our method with previously obtained data from a commercially available insect cell-derived spike protein and the results were comparable to published findings.

Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome.

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.