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Computational Analysis of Host–Pathogen Protein Interactions between Humans and Different Strains of Enterohemorrhagic Escherichia coli

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, April 2017
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Title
Computational Analysis of Host–Pathogen Protein Interactions between Humans and Different Strains of Enterohemorrhagic Escherichia coli
Published in
Frontiers in Cellular and Infection Microbiology, April 2017
DOI 10.3389/fcimb.2017.00128
Pubmed ID
Authors

Tungadri Bose, K. V. Venkatesh, Sharmila S. Mande

Abstract

Serotype O157:H7, an enterohemorrhagic Escherichia coli (EHEC), is known to cause gastrointestinal and systemic illnesses ranging from diarrhea and hemorrhagic colitis to potentially fatal hemolytic uremic syndrome. Specific genetic factors like ompA, nsrR, and LEE genes are known to play roles in EHEC pathogenesis. However, these factors are not specific to EHEC and their presence in several non-pathogenic strains indicates that additional factors are involved in pathogenicity. We propose a comprehensive effort to screen for such potential genetic elements, through investigation of biomolecular interactions between E. coli and their host. In this work, an in silico investigation of the protein-protein interactions (PPIs) between human cells and four EHEC strains (viz., EDL933, Sakai, EC4115, and TW14359) was performed in order to understand the virulence and host-colonization strategies of these strains. Potential host-pathogen interactions (HPIs) between human cells and the "non-pathogenic" E. coli strain MG1655 were also probed to evaluate whether and how the variations in the genomes could translate into altered virulence and host-colonization capabilities of the studied bacterial strains. Results indicate that a small subset of HPIs are unique to the studied pathogens and can be implicated in virulence. This subset of interactions involved E. coli proteins like YhdW, ChuT, EivG, and HlyA. These proteins have previously been reported to be involved in bacterial virulence. In addition, clear differences in lineage and clade-specific HPI profiles could be identified. Furthermore, available gene expression profiles of the HPI-proteins were utilized to estimate the proportion of proteins which may be involved in interactions. We hypothesized that a cumulative score of the ratios of bound:unbound proteins (involved in HPIs) would indicate the extent of colonization. Thus, we designed the Host Colonization Index (HCI) measure to determine the host colonization potential of the E. coli strains. Pathogenic strains of E. coli were observed to have higher HCIs as compared to a non-pathogenic laboratory strain. However, no significant differences among the HCIs of the two pathogenic groups were observed. Overall, our findings are expected to provide additional insights into EHEC pathogenesis and are likely to aid in designing alternate preventive and therapeutic strategies.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 26%
Researcher 9 19%
Student > Bachelor 4 9%
Student > Postgraduate 3 6%
Professor 2 4%
Other 7 15%
Unknown 10 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 26%
Biochemistry, Genetics and Molecular Biology 10 21%
Computer Science 4 9%
Nursing and Health Professions 2 4%
Veterinary Science and Veterinary Medicine 2 4%
Other 5 11%
Unknown 12 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 February 2021.
All research outputs
#13,312,402
of 22,965,074 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#2,060
of 6,467 outputs
Outputs of similar age
#153,881
of 310,317 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#61
of 165 outputs
Altmetric has tracked 22,965,074 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,467 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 66% of its peers.
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 310,317 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.