When can site-specific glycoform compositions resolve biosynthetic rates?
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Mass spectrometry measures site-specific glycoform compositions, but when these measurements can resolve upstream biosynthetic rates remains unclear. We assess whether small changes in effective rates, each representing the processing capacity of a group of biosynthetic reactions, can be distinguished near specified baseline rates with secretion held fixed. Because proportions sum to one, m jointly normalised glycoform classes provide at most m − 1 independent quantities. Distinguishing changes in k rates therefore requires at least k + 1 classes, although this count alone does not ensure identifiability. In a canonical N-glycan network with eight rates, exhaustive evaluation of nine-class panels identified panels that could locally distinguish all eight rates. Among these panels, class choice changed the allowable measurement error by approximately 18-fold for the same target uncertainty in inferred rates. A separate simulation within the fixed network showed that estimating rate-change combinations with weaker composition responses reduced bias but amplified measurement noise. We applied the framework to plasma data from 40 controls and 70 patients across 14 inherited glycosylation-disorder groups. A prespecified composition score for the expected pathway disturbance ranked among the top two in 13 of 14 groups. Network responses linked observed composition shifts to biosynthetic reaction classes. Expanding site models from five to eight reaction classes improved control-composition fit but reduced the number of sites at which all modelled rates were locally distinguishable and increased noise sensitivity. Rate inference thus requires sufficient panel size, separable rate responses, adequate measurement precision and a model that fits the composition. These requirements guide measurement design and help determine whether compositions support pathway-level interpretation or individual-rate inference.
Author summary
Mass spectrometry measures the relative amounts of glycan forms attached to a protein site. We asked when these proportions can distinguish changes in the biosynthetic reactions that produce them. Because proportions sum to 100%, a panel contains one fewer independent quantity than its number of glycoform classes. Our eight-rate model therefore required at least nine classes. Which classes were measured strongly affected the measurement precision needed to distinguish the rates. We applied the framework to plasma data from inherited glycosylation disorders. The expected composition change ranked among the two strongest signals in 13 of 14 disorder groups. Network responses linked these changes to reaction groups. Most site models could distinguish small rate changes near a fitted control reference, but this did not establish recovery of patients’ true rates. A more detailed model reproduced compositions better while making individual rates harder to distinguish. The framework helps researchers select informative glycoforms, calculate measurement-precision requirements and assess which biosynthetic changes the data can support. Its conclusions depend on the assumed network, reference rates and measurement-error model.
