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Bioinformatic analysis of structures and encoding genes of Escherichia coli surface polysaccharides sheds light on the heterologous biosynthesis of glycans

Overview of attention for article published in BMC Genomics, April 2023
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Title
Bioinformatic analysis of structures and encoding genes of Escherichia coli surface polysaccharides sheds light on the heterologous biosynthesis of glycans
Published in
BMC Genomics, April 2023
DOI 10.1186/s12864-023-09269-6
Pubmed ID
Authors

Ao Dong, Chengzhi Liu, Xiaoting Hua, Yunsong Yu, Yan Guo, Dongshu Wang, Xiankai Liu, Huan Chen, Hengliang Wang, Li Zhu

Abstract

Surface polysaccharides (SPs), such as lipopolysaccharide (O antigen) and capsular polysaccharide (K antigen), play a key role in the pathogenicity of Escherichia coli (E. coli). Gene cluster for polysaccharide antigen biosynthesis encodes various glycosyltransferases (GTs), which drive the process of SP synthesis and determine the serotype. In this study, a total of 7,741 E. coli genomic sequences were chosen for systemic data mining. The monosaccharides in both O and K antigens were dominated by D-hexopyranose, and the SPs in 70-80% of the strains consisted of only the five most common hexoses (or some of them). The linkages between the two monosaccharides were mostly α-1,3 (23.15%) and β-1,3 (20.49%) bonds. Uridine diphosphate activated more than 50% of monosaccharides for glycosyltransferase reactions. These results suggest that the most common pathways could be integrated into chassis cells to promote glycan biosynthesis. We constructed a database (EcoSP, http://ecosp.dmicrobe.cn/ ) for browse this information, such as monosaccharide synthesis pathways. It can also be used for serotype analysis and GT annotation of known or novel E. coli sequences, thus facilitating the diagnosis and typing. Summarizing and analyzing the properties of these polysaccharide antigens and GTs are of great significance for designing glycan-based vaccines and the synthetic glycobiology.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Other 1 20%
Unknown 3 60%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 3 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 April 2023.
All research outputs
#15,831,100
of 23,524,722 outputs
Outputs from BMC Genomics
#6,807
of 10,786 outputs
Outputs of similar age
#130,631
of 241,953 outputs
Outputs of similar age from BMC Genomics
#38
of 79 outputs
Altmetric has tracked 23,524,722 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,786 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 241,953 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.