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Trends Glycosci Glycotechnol,
2004]
Blood-group-ABH antigens have been attributed no physiological roles. While studying Ca2+ dependent cell-cell adhesion of Xenopus laevis, we found that blood-group-B active GPI-anchored lectin and blood-group-B active glycoconjugates are mediating cell adhesion of early embryonic cells. In mouse embryonic cells, not the blood-group-B antigens but the Lewis x blood-group-active molecules are playing similar roles in compaction. How did the surface glycomes playing roles in cell-cell adhesion evolve in these two species? In the nematode Caenorhabditis elegans, sugar chains of chondroitin proteoglycan play indispensable roles in completion of cell division. A decrease of chondroitin on the embryonic cell surfaces results in apparent reversion of cell division. Cytokinesis and chromosome partition becomes abnormal, and the embryonic cells die. Are chondroitin in the higher organisms playing similar roles in cell division, or are the roles of chondroitin replaced with different sugar chains? As seen in the two examples, comparison of glycomes between various organisms could be very powerful hypothesis generating tools in glycobiology. With the completion of genome DNA sequencing, it seems to be high time to study the evolution of glycomes with bioinformatics and functional glycomics.
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Biol Direct,
2016]
The presence of only small amounts of misfolded protein is an indication of a healthy proteome. Maintaining proteome health, or more specifically, "proteostasis," is the purview of the "proteostasis network." This network must respond to constant fluctuations in the amount of destabilized proteins caused by errors in protein synthesis and exposure to acute proteotoxic conditions. Aging is associated with a gradual increase in damaged and misfolded protein, which places additional stress on the machinery of the proteostasis network. In fact, despite the ability of the proteostasis machinery to readjust its stoichiometry in an attempt to maintain homeostasis, the capacity of cells to buffer against misfolding is strikingly limited. Therefore, subtle changes in the folding environment that occur during aging can significantly impact the health of the proteome. This decline and eventual collapse in proteostasis is most pronounced in individuals with neurodegenerative disorders such as Alzheimer's Disease, Parkinson's Disease, and Huntington's Disease that are caused by the misfolding, aggregation, and toxicity of certain proteins. This review discusses how C. elegans models of protein misfolding have contributed to our current understanding of the proteostasis network, its buffering capacity, and its regulation. REVIEWERS: This article was reviewed by Luigi Bubacco, Patrick Lewis and Xavier Roucou.
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Biochim Biophys Acta,
2017]
The development of new microscopy techniques for super-resolved, long-term monitoring of cellular and subcellular dynamics in living organisms is revealing new fundamental aspects of tissue development and repair. However, new microscopy approaches present several challenges. In addition to unprecedented requirements for data storage, the analysis of high resolution, time-lapse images is too complex to be done manually. Machine learning techniques are ideally suited for the (semi-)automated analysis of multidimensional image data. In particular, support vector machines (SVMs), have emerged as an efficient method to analyze microscopy images obtained from animals. Here, we discuss the use of SVMs to analyze in vivo microscopy data. We introduce the mathematical framework behind SVMs, and we describe the metrics used by SVMs and other machine learning approaches to classify image data. We discuss the influence of different SVM parameters in the context of an algorithm for cell segmentation and tracking. Finally, we describe how the application of SVMs has been critical to study protein localization in yeast screens, for lineage tracing in C. elegans, or to determine the developmental stage of Drosophila embryos to investigate gene expression dynamics. We propose that SVMs will become central tools in the analysis of the complex image data that novel microscopy modalities have made possible. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.