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This article reviews large-scale techniques for accelerating progress in glycobiology.
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Biology Articles » Biochemistry » Carbohydrate Biochemistry » Large-scale approaches for glycobiology » Figures
Figures - Large-scale approaches for glycobiology
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Figure 1
Systems and molecular complexity in glycobiology. (a) The
glycosylation machinery consists of an intricate network of metabolic
pathways that interconvert monosaccharides and produce high-energy
sugar nucleotides (full details of the pathways are available in [9]).
The hexosamine pathway [46] that converts glucosamine (1) to UDP-N-acetylglucosamine
(UDP-GlcNAc) (2) is highlighted in blue. The versatility of the
glycosylation machinery is epitomized by the conversion of UDP-GlcNAc
into N-acetylmannosamine (ManNAc) (3), a sugar that is
metabolically converted to CMP-sialic acid (CMP-Sia; 4) by the pathway
highlighted in red. UDP-GlcNAc and CMP-Sia, together with seven other
sugar nucleotides, are transported into the endoplasmic reticulum (ER)
and Golgi apparatus (5), where they are used for the production of
complex oligosaccharides (6) that comprise the glycosylation profile of
the cell surface. This profile is made up of proteins (such as the
prion protein and CD34, shown here) and glycolipids such as ganglioside
GM3, a glycosphingolipid. Sialic acid (Sia) is a ubiquitous terminal
modification. (b) The chemical structures of glucosamine, UDP-GlcNAc, UDP-ManNAc, and CMP-Sia. (c) As
well as being used to build complex oligosaccharides, UDP-GlcNAc is a
high-energy building block that provides the GlcNAc residue required
for O-GlcNAc protein modification in the cytosol [13]. (d) Slight
modifications to the chemical structure of CMP-Sia elicit profound
changes in biological activity. The membrane glycosphingolipid
ganglioside GM3 (center) is converted to pro-apoptotic gangliosides GD3
by addition of Sia (top), whereas deacetylation of GM3 yields de-N-acetyl GM3, which has a growth stimulatory effect.
(Click image to enlarge)
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Figure 2
Conventional low-throughput glycoconjugate characterization and steps
that will improve throughput. Current strategies for oligosaccharide
identification include multiple time-consuming steps including, but not
limited to, (1) isolation of individual glycoconjugates, such as prions
or CD34 (see Figure 1), from a cell or tissue; (2) the detachment and
purification of each oligosaccharide from a particular glycoconjugate;
and (3) a one-at-a-time structural characterization and identification.
Each of these steps currently requires multiple procedures and method
of analysis [21], as illustrated in the boxes for steps (1) and (3).
Streamlined methods now under development, such as (4) the coupling of
isolation by glycoblotting with identification by mass spectrometry
(MS) [35], and automated interpretation of spectra [30], are also
shown. These methods, along with array-based technologies (see Figure
3), offer hope for high-throughput glycan characterization in the near
future.
(Click image to enlarge)
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Figure 3
Oligosaccharide and carbohydrate-binding protein arrays. (a) Oligosaccharide
microarrays are used to detect and characterize carbohydrate-binding
proteins. They are constructed by (1) spotting known oligosaccharides
(either synthetic or naturally isolated) onto a solid surface such as a
treated glass slide in a predetermined array. Whole cells can be bound
to the array (2), but it is more common to first fractionate cells or
tissues to isolate (3) putative carbohydrate-binding proteins. (b) Arrays
of known carbohydrate-binding proteins (either lectins or monoclonal
antibodies) are used to detect and characterize oligosaccharides. They
are produced by printing spots of the proteins onto a suitable surface
(1). Again, whole cells (2) can be bound to the array, but more usually
(3) their cell-surface oligosaccharides will be isolated and used. Both
types of array can be used for a variety of purposes.
(Click image to enlarge)
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