Kawar ZS et al. (2002) J Biol Chem "Molecular cloning and enzymatic characterization of a UDP-GalNAc:GlcNAc(beta)-R beta1,4-N-acetylgalactosaminyltransferase from Caenorhabditis elegans."

Kawar ZS, Cummings RD, Van Die I

[J Biol Chem, 2002]

A common terminal structure in glycans from animal glycoproteins and glycolipids is the lactosamine sequence Galbeta4GlcNAc-R (LacNAc or LN). An alternative sequence that occurs in vertebrate as well as in invertebrate glycoconjugates is GalNAcbeta4GlcNAc-R (LacdiNAc or LDN). Whereas genes encoding beta4GalTs responsible for LN synthesis have been reported, the beta4GalNAcT(s) responsible for LDN synthesis has not been identified. Here we report the identification of a gene from Caenorhabditis elegans encoding a UDP-GalNAc:GlcNAcbeta-R beta1,4-N-acetylgalactosaminyltransferase (Cebeta4GalNAcT) that synthesizes the LDN structure. Cebeta4GalNAcT is a member of the beta4GalT family, and its cDNA is predicted to encode a 383-amino acid type 2 membrane glycoprotein. A soluble, epitope-tagged recombinant form of Cebeta4GalNAcT expressed in CHO-Lec8 cells was active using UDP-GalNAc, but not UDPGal, as a donor toward a variety of acceptor substrates containing terminal beta-linked GlcNAc in both N- and O-glycan type structures. The LDN structure of the product was verified by co-chromatography with authentic standards and H-1 NMR spectroscopy. Moreover, Chinese hamster ovary CHO-Lec8 and CHO-Lec2 cells expressing Cebeta4GalNAcT acquired LDN determinants on endogenous glycoprotein N-glycans, demonstrating that the enzyme is active in mammalian cells as an authentic beta4GalNAcT. The identification and availability of this novel enzyme should enhance our understanding of the structure and function of LDN-containing glycoconjugates.

Nguyen K et al. (2007) Glycobiology "Molecular cloning and characterization of the Caenorhabditis elegans alpha1,3-fucosyltransferase family."

Van Die I, Nguyen K, Cummings RD, Kawar ZS, Grundahl KM

[Glycobiology, 2007]

The genome of Caenorhabditis elegans encodes five genes with homology to known alpha1,3 fucosyltransferases (alpha1,3FTs), but their expression and functions are poorly understood. Here we report the molecular cloning and characterization of these alpha1,3FTs (CEFT-1 through -5). The open reading frame for each enzyme predicts a type II transmembrane protein and multiple potential N-glycosylation sites. We prepared recombinant epitope-tagged forms of each CEFT and found that they had unusual acceptor specificity, cation requirements, and temperature sensitivity. CEFT-1 acted on the N-glycan pentasaccharide core acceptor to generate Manalpha1-3(Manalpha1-6)Manbeta1-4GlcNAcbeta1-4(Fucalpha1-3)GlcNAcbeta1-Asn. By contrast, CEFT-2 did not act on the pentasaccharide acceptor, but instead utilized a LacdiNAc acceptor to generate GalNAcbeta1-4(Fucalpha1-3)GlcNAcbeta1-3Galbeta1-4Glc, which is a novel activity. CEFT-3 utilized a LacNAc acceptor to generate Galbeta1-4(Fucalpha1-3)GlcNAcbeta1-3Galbeta1-4Glc without requiring cations. CEFT-4 was similar to CEFT-3, but its activity was enhanced by some divalent cations. Recombinant CEFT-5 was well-expressed, but did not act on available acceptors. Each CEFT was optimally active at room temperature and rapidly lost activity at 37 degrees C. Promoter analysis showed that CEFT-1 is expressed in C. elegans eggs and adults but its expression was restricted to a few neuronal cells at the head and tail. We prepared deletion mutants for each enzyme for phenotypic analysis. While loss of CEFT-1 correlated with loss of pentasaccharide core activity and core alpha1-3-fucosylated glycans in worms, loss of other enzymes did not correlate with any phenotypic changes. These results suggest that each of the alpha1,3FTs in C. elegans has unique specificity and expression patterns.

Qiao C et al. (2024) Nat Commun "Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy."

Dai Q, Meng Q, Jiang T, Qiao H, Wei R, Fu W, Chen X, Chen H, Wang Y, Qiao C, Zeng Y, Lu H, Li D, Wu J, Guo J

[Nat Commun, 2024]

Computational super-resolution methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary super-resolution imaging conditions, in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional wide-field microscopy, confocal microscopy, two-photon microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy, which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans.