https://orcid.org/0000-0002-8158-9616
Figures & data
Figure 1. ExPEC reservoir and infection sites.
Like commensal E. coli, ExPEC inhabits the human gastrointestinal tract as its long-term reservoir without causing gastroenteritis. However, when translocated to other body sites, ExPEC causes infections that may lead to fatal diseases. ExPEC pathotypes are divided according to the types of disease that they cause: uropathogenic E. coli (UPEC), sepsis-causing E. coli (SEPEC), and neonatal meningitis-associated E. coli (NMEC).
Figure 2. Considerations for antigen and vaccine type selection.
Selecting the right targets for vaccination and delivering them in an appropriate formulation is essential for designing an effective vaccine. Commonly, vaccine developers use epidemiological observations about what pathogen strains and serogroups are most prevalent to determine vaccine targets (e.g. by including them in whole cell formulations or purifying their polysaccharide antigens). With the emergence of multi-omics technologies, bioinformatics approaches have been applied to screen databases for antigens that are enriched among pathogenic isolates. These antigens are often targeted directly with recombinant protein or nucleic acid vaccines.
Figure 3. ExPEC vaccine antigen targets.
In early ExPEC vaccine studies, whole cell inactivated formulations were widely utilized. As antigen discovery methods evolve, polysaccharide conjugate vaccines and protein subunit vaccines that target one or multiple ExPEC antigens become more popular. Here is a scheme of an ExPEC cell with its virulence factors and respective antigens highlighted, which have been used as vaccine targets in previous studies.
Figure 4. Considerations for adjuvant selection and delivery method.
The immunologic response to vaccination can be optimized with the addition of immunomodulatory adjuvants or by route of administration. For example, vaccine delivery to mucosal membranes (e.g. nose, mouth, and vagina) increases protection at these important immunologic barriers.
Figure 5. Pan-Virulome of Escherichia coli.
1,348 Escherichia coli strains were cross-referenced against 396 Escherichia coli virulence factor references (described previously in https://pubmed.ncbi.nlm.nih.gov/33941580/) using BLAST. Hits were limited to a single best hit for each virulence factor using -culling_limit 1 and -max_hsps 1 and hits under 100 base pairs were filtered out of the results. Heatmap was generated using ComplexHeatmap suite in R studio using the Percent Identity results from the BLAST search. Yellow represents high identity compared to reference, while magenta represents low identity compared to reference. Grey indicates no hit was found. The heatmap was split vertically by phylogroup (A, B1, B2, C, D, E, F, G) and horizontally by virulence factor class. Hierarchical clustering was performed on both columns and rows separately using Euclidean distance method. Clustering was performed first within group (i.e. by phylogroup and virulence class) and then between groups. The following acronyms were used in this figure: LEE: Locus of Enterocyte Effacement; Non-LEE T3SS: Non-Locus of Enterocyte Effacement Encoded Type 3 Secretion System Dependent Effectors; Misc: Miscellaneous Virulence Factors; T6SS: Type 6 Secretion System.
Data availability statement
Data sharing is not applicable to this manuscript because no new data was created.