Epithelial-Mesenchymal Transition in Cells Expanded In Vitro from Lineage-Traced Adult Human Pancreatic Beta Cells

BACKGROUND: In-vitro expansion of functional beta cells from adult human islets is an attractive approach for generating an abundant source of cells for beta-cell replacement therapy of diabetes. Using genetic cell-lineage tracing we have recently shown that beta cells cultured from adult human islets undergo rapid dedifferentiation and proliferate for up to 16 population doublings. These cells have raised interest as potential candidates for redifferentiation into functional insulin-producing cells. Previous work has associated dedifferentiation of cultured epithelial cells with epithelial-mesenchymal transition (EMT), and suggested that EMT generates cells with stem cell properties. Here we investigated the occurrence of EMT in these cultures and assessed their stem cell potential. METHODOLOGY/PRINCIPAL FINDINGS: Using cell-lineage tracing we provide direct evidence for occurrence of EMT in cells originating from beta cells in cultures of adult human islet cells. These cells express multiple mesenchymal markers, as well as markers associated with mesenchymal stem cells (MSC). However, we do not find evidence for the ability of such cells, nor of cells in these cultures derived from a non-beta-cell origin, to significantly differentiate into mesodermal cell types. CONCLUSIONS/SIGNIFICANCE: These findings constitute the first demonstration based on genetic lineage-tracing of EMT in cultured adult primary human cells, and show that EMT does not induce multipotency in cells derived from human beta cells

Glycans as receptors for influenza pathogenesis

Influenza A viruses, members of the Orthomyxoviridae family, are responsible for annual seasonal influenza epidemics and occasional global pandemics. The binding of viral coat glycoprotein hemagglutinin (HA) to sialylated glycan receptors on host epithelial cells is the critical initial step in the infection and transmission of these viruses. Scientists believe that a switch in the binding specificity of HA from Neu5Acα2-3Gal linked (α2-3) to Neu5Acα2-6Gal linked (α2-6) glycans is essential for the crossover of the viruses from avian to human hosts. However, studies have shown that the classification of glycan binding preference of HA based on sialic acid linkage alone is insufficient to establish a correlation between receptor specificity of HA and the efficient transmission of influenza A viruses. A recent study reported extensive diversity in the structure and composition of α2-6 glycans (which goes beyond the sialic acid linkage) in human upper respiratory epithelia and identified different glycan structural topologies. Biochemical examination of the multivalent HA binding to these diverse sialylated glycan structures also demonstrated that high affinity binding of HA to α2-6 glycans with a characteristic umbrella-like structural topology is critical for efficient human adaptation and human-human transmission of influenza A viruses. This review summarizes studies which suggest a new paradigm for understanding the role of the structure of sialylated glycan receptors in influenza virus pathogenesis.National Institute of General Medical Sciences (U.S.) (Glue Grant U54 GM62116)National Institutes of Health (U.S.) (Grant GM57073)Singapore-MIT Alliance for Research and Technolog

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed