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Record W1893306363 · doi:10.1074/mcp.m114.046847

Novel Host Proteins and Signaling Pathways in Enteropathogenic E. coli Pathogenesis Identified by Global Phosphoproteome Analysis *

2015· article· en· W1893306363 on OpenAlexafffund
Roland W. Scholz, Koshi Imami, Nichollas E. Scott, William S. Trimble, Leonard J. Foster, B. Brett Finlay

Bibliographic record

VenueMolecular & Cellular Proteomics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsPathogenesisEnteropathogenic Escherichia coliHost (biology)Signal transductionBiologyComputational biologyMicrobiologyCell biologyGeneticsEscherichia coliGeneImmunology

Abstract

fetched live from OpenAlex

Enteropathogenic Escherichia coli (EPEC) uses a type III secretion system (T3SS) to directly translocate effector proteins into host cells where they play a pivotal role in subverting host cell signaling needed for disease. However, our knowledge of how EPEC affects host protein phosphorylation is limited to a few individual protein studies. We employed a quantitative proteomics approach to globally map alterations in the host phosphoproteome during EPEC infection. By characterizing host phosphorylation events at various time points throughout infection, we examined how EPEC dynamically impacts the host phosphoproteome over time. This experimental setup also enabled identification of T3SS-dependent and -independent changes in host phosphorylation. Specifically, T3SS-regulated events affected various cellular processes that are known EPEC targets, including cytoskeletal organization, immune signaling, and intracellular trafficking. However, the involvement of phosphorylation in these events has thus far been poorly studied. We confirmed the MAPK family as an established key host player, showed its central role in signal transduction during EPEC infection, and extended the repertoire of known signaling hubs with previously unrecognized proteins, including TPD52, CIN85, EPHA2, and HSP27. We identified altered phosphorylation of known EPEC targets, such as cofilin, where the involvement of phosphorylation has so far been undefined, thus providing novel mechanistic insights into the roles of these proteins in EPEC infection. An overlap of regulated proteins, especially those that are cytoskeleton-associated, was observed when compared with the phosphoproteome of Shigella-infected cells. We determined the biological relevance of the phosphorylation of a novel protein in EPEC pathogenesis, septin-9 (SEPT9). Both siRNA knockdown and a phosphorylation-impaired SEPT9 mutant decreased bacterial adherence and EPEC-mediated cell death. In contrast, a phosphorylation-mimicking SEPT9 mutant rescued these effects. Collectively, this study provides the first global analysis of phosphorylation-mediated processes during infection with an extracellular, diarrheagenic bacterial pathogen.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.241
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2015
Admission routes2
Has abstractyes

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