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A Bittersweet Computational Journey among Glycosaminoglycans.

ABSTRACT: Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the "bitter" and "sweet" aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

SUBMITTER: Paiardi G

PROVIDER: S-EPMC8156566 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:High-risk clone types in Pseudomonas aeruginosa are problematic global multidrug-resistant clones. However, apart from their ability to resist antimicrobial treatment, not much is known about what sets these clones apart from the multitude of other clones. In high-risk clone ST111, it has previously been shown that replacement of the native serotype biosynthetic gene cluster (O4) by a different gene cluster (O12) by horizontal gene transfer and recombination may have contributed to the global success of this clone. However, the extent to which isolates undergo this type of serotype switching has not been adequately explored in P. aeruginosa. In the present study, a bioinformatics tool has been developed and utilized to provide a first estimate of serotype switching in groups of multidrug resistant (MDR) clinical isolates. The tool detects serotype switching by analysis of core-genome phylogeny and in silico serotype. Analysis of a national survey of MDR isolates found a prevalence of 3.9 % of serotype-switched isolates in high-risk clone types ST111, ST244 and ST253. A global survey of MDR isolates was additionally analysed, and it was found that 2.3 % of isolates had undergone a serotype switch. To further understand this process, we determined the exact boundaries of the horizontally transferred serotype O12 island. We found that the size of the serotype island correlates with the clone type of the receiving isolate and additionally we found intra-clone type variations in size and boundaries. This suggests multiple serotype switch events. Moreover, we found that the housekeeping gene gyrA is co-transferred with the O12 serotype island, which prompted us to analyse this allele for all serotype O12 isolates. We found that 95 % of ST111 O12 isolates had a resistant gyrA allele and 86 % of all O12 isolates had a resistant gyrA allele. The rates of resistant gyrA alleles in isolates with other prevalent serotypes are all lower. Together, these results show that the transfer and acquisition of serotype O12 in high-risk clone ST111 has happened multiple times and may be facilitated by multiple donors, which clearly suggests a strong selection pressure for this process. However, gyrA-mediated antibiotic resistance may not be the only evolutionary driver.

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A Bittersweet Computational Journey among Glycosaminoglycans.

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