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Construction of a Lectin–Glycan Interaction Network from Enterohemorrhagic Escherichia coli Strains by Multi-omics Analysis
Enterohemorrhagic Escherichia coli (EHEC) causes hemorrhagic colitis and hemolytic uremic syndrome. EHEC infection begins with bacterial adherence to the host intestine via lectin-like adhesins that bind to the intestinal wall. However, EHEC-related lectin–glycan interactions (LGIs) remain unknown....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215717/ https://www.ncbi.nlm.nih.gov/pubmed/32290560 http://dx.doi.org/10.3390/ijms21082681 |
Sumario: | Enterohemorrhagic Escherichia coli (EHEC) causes hemorrhagic colitis and hemolytic uremic syndrome. EHEC infection begins with bacterial adherence to the host intestine via lectin-like adhesins that bind to the intestinal wall. However, EHEC-related lectin–glycan interactions (LGIs) remain unknown. Here, we conducted a genome-wide investigation of putative adhesins to construct an LGI network. We performed microarray-based transcriptomic and proteomic analyses with E. coli EDL933. Using PSORTb-based analysis, potential outer-membrane-embedded adhesins were predicted from the annotated genes of 318 strains. Predicted proteins were classified using TMHMM v2.0, SignalP v5.0, and LipoP v1.0. Functional and protein–protein interaction analyses were performed using InterProScan and String databases, respectively. Structural information of lectin candidate proteins was predicted using Iterative Threading ASSEmbly Refinement (I-TASSER) and Spatial Epitope Prediction of Protein Antigens (SEPPA) tools based on 3D structure and B-cell epitopes. Pathway analysis returned 42,227 Gene Ontology terms; we then selected 2585 lectin candidate proteins by multi-omics analysis and performed homology modeling and B-cell epitope analysis. We predicted a total of 24,400 outer-membrane-embedded proteins from the genome of 318 strains and integrated multi-omics information into the genomic information of the proteins. Our integrated multi-omics data will provide a useful resource for the construction of LGI networks of E. coli. |
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