Evidence map›Paper›PMID 42399049›Full record

ArticleMethods in enzymology2026

Sialylation and fucosylation of mucin-type glycopeptides using recombinant glycosyltransferases.

Amanda M Wood, Jessica Kramer Stratton

Abstract read
In one paragraph

Article in Methods in enzymology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Amanda M WoodDepartment of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.
Jessica Kramer StrattonDepartment of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States. Electronic address: jessica.kramer@utah.edu.

Funding

Synthetic mucins in epithelial models to probe virus-mucin interactionsR35GM147262 · NIGMS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Jessica Kramer Stratton · 2022 to 2026
$2.0M
NIGMS NIH HHS R35 GM147262
6 · The paper itself

Abstract

Mucins are glycoproteins that play fundamental roles in mucus, saliva, and tears, and coat cell surfaces in the glycocalyx. The saccharide component of mucins is essential for their many biophysical and biochemical functions. The composition of mucin glycans is naturally heterogeneous, and precise control over this composition for structure-function studies has been extremely challenging using traditional genetic and biochemical methods. Thus, synthetically generated materials with defined glycosylation are essential for probing mucin biology. Sialic acid and fucose are two sugars typically found in terminal positions on mucin glycans and are implicated in regulating diverse processes, from immunity to cancer. Here, we describe detailed enzymatic methods to install fucose and sialic acids on mucin-type glycopeptides or glycoproteins. Microbe-derived recombinant enzymes can be used to install these sugars with regio- and stereoselectivity that would be extremely challenging to achieve using chemical methods. The methods described here encompass cloning and recombinant expression of the relevant enzymes, conditions for enzymatic glycosylation reactions, and analytical techniques to characterize the sialylated or fucosylated glycopeptide products. Overall, these methods enable researchers to probe mucin biology using glycan-defined materials.

Indexed as

FucoseGlycopeptidesGlycosyltransferasesMucinsN-Acetylneuraminic AcidAnimalsGlycosylationHumansRecombinant ProteinsSialyltransferasesFucoseGlycopeptidesGlycosyltransferasesMucinsN-Acetylneuraminic AcidRecombinant ProteinsSialyltransferasesFucoseFucosyltransferaseGlycopeptideMucinSialic acidSialyltransferase

Identifiers

PMID42399049
PMCPMC13336240

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.