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Structure of <i>Enterohemorrhagic</i> <i>Escherichia coli</i> O157:H7 Intimin Virulence Factor Bound to Nanobodies

2021· article· he· W3166059959 on OpenAlexaboutno aff
Angham Ahmed, Cory L. Brooks

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languagehe
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntiminMicrobiologyBiologyVirulence factorEscherichia coliVirulenceBacterial adhesinVirologyAntibodyPathogenicity islandEnterobacteriaceaeImmunologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Enterohemorrhagic E. coli O157:H7 (EHEC) is a food and water‐born pathogen that presents a significant risk to human health worldwide. EHEC naturally resides in the intestinal tract of cattle as normal flora but can be transmitted to humans when contaminated food is ingested. Once EHEC invades and colonizes the human intestinal tract, it secretes Shiga‐like toxins causing serious and potentially fatal gastrointestinal diseases. Unlike most foodborne bacterial diseases, antibiotics are not recommended for treatment of EHEC as antibiotics can induce enterotoxin release, increasing the risk of hemolytic uremic syndrome. There is currently no effective treatment or vaccine against enterohemorrhagic E. coli . EHEC pathogenicity involves intimin, a virulence factor which mediates bacterial colonization of the host GI tract. Due to its critical role in EHEC pathogenesis, intimin has attracted attention as an antibacterial drug target. Inhibiting the interaction of intimin with its cognate bacterial secreted receptor Tir could neutralize bacterial colonization of the gastrointestinal tract. One novel solution for treating EHEC infection comes from a unique class of antibodies known as nanobodies. Nanobodies are the antigen binding domain of heavy chain antibodies produced by the Camelid family. Intimin specific nanobodies were generated by immunizing a llama followed by phage display and selection for high affinity intimin binding nanobodies. The resultant intimin‐specific nanobodies neutralized EHEC in vitro . We hypothesize that nanobodies specifically bind the Tir‐binding domain of intimin in order to neutralizing EHEC infection. The goal of this research project is to determine the complex crystal structure of the nanobodies bound to intimin. The structure of nanobodies‐intimin would show their protein‐protein interaction binding site revealing key amino acids involved in binding. These residues could also be involved in the binding of intimin to its natural ligand, Tir. Thus, revealing such residues could form the bases for identifying and developing novel therapeutics and biosensors for treating and preventing EHEC pathogenesis.We show through size exclusion chromatography that nanobodies bind intimin and form stable complexes. We have set up crystal trails of five nanobodies (Int1, Int2, Int3, Int4, and IntN1) complexed to intimin. Two of the five complexed proteins, Int2‐intimin and Int3‐intimn formed crystals. The crystal condition for the two protein complexes Int2 and Int3 bound to intimin were optimized by varying the concentration of precipitants and pH range. Crystals of the protein complexes were sent to the Canadian Light Source for X‐ray diffraction data collection. Diffraction measurements of Int2‐intimin and Int3‐intimin complexes were collected and processed in space groups P1 and P222, respectively. Currently, we are analyzing the structure by molecular replacement.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.270
Teacher spread0.255 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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