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Record W7111624796

Development of Assays for the Identification of Virulent Enterohemorrhagic Escherichia Coli Strains

2024· dissertation· en· W7111624796 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2024
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsnot available
Fundersnot available
KeywordsEscherichia coliIntiminVirulenceEnteropathogenic Escherichia coliPathogenic Escherichia coliEnterotoxigenic Escherichia coliShiga toxinEnterobacteriaceaeEscherichia
DOInot available

Abstract

fetched live from OpenAlex

Escherichia coli (E. coli) is a diverse Gram-negative, rod-shaped, facultatively anaerobic, and non-sporing bacterium belonging to the family Enterobacteriaceae. Strains of E. coli can be found in the environment and the intestinal microflora of mammals. While many E. coli strains have developed an essential mutualism relationship in our colonized gastrointestinal tract, some have evolved with the ability to cause diarrheal disease in humans. Diarrheal disease-causing strains are categorized as intestinal pathogenic Escherichia coli (IPEC). IPEC can be further classified into five phenotypes: enterotoxigenic Escherichia coli (ETEC), enteroinvasive Escherichia coli (EIEC), enteropathogenic Escherichia coli (EPEC), enteroaggregative Escherichia coli (EAEC), Shiga toxin-producing Escherichia coli (STEC), and Enterohemorrhagic Escherichia coli (EHEC). While Shiga toxin-producing Escherichia coli (STEC) and enterohemorrhagic Escherichia coli (EHEC) are interchangeably in scientific literature. However, based on the Food and Agriculture Organization (FAO), STEC is defined as strains that harbor the stx gene that produces Shiga toxins but may not carry other virulent genes. Similarly, EHEC is defined as strains that harbor the stx and intimin (eae) genes (FAO, WHO, 2018). Strains that have both these genes are considered virulent, while strains that have only one or neither are considered potentially avirulent. Virulent strains with stx and eae are responsible for significant foodborne outbreaks, are a major foodborne pathogen implicated in red meat outbreaks, and are considered adulterants in beef products. On the contrary, potentially avirulent strains are not considered a significant concern for the red meat industry. Currently, MLG 5.03 is the standard method for the detection of virulent strains. However, this method suffers from high false-positive rates. The false-positive test results arise from this method as it uses separate primer pairs to detect stx and eae independently within a sample. The presence of multiple avirulent strains or other background genera that may also contain stx or eae found in meat samples result in the false detection of strain(s) containing both of these genes. The purpose of this study will be to initially standardize and validate four high-resolution melt (HRM) assays, followed by a conversation of these assays to industry-friendly hydrolysis probe (HP) assays for the differentiation of potentially virulent strains of EHEC serogroups belonging to O26, O103, O111, and O121. The designed primers and probes will target a conserved single nucleotide polymorphism (SNP) located on the serogroup-specific fnl1, wbdK, wbtD, and vioA genes of O26, O111, O103, and O121, respectively. The assays will be validated using pure cultures strains from Canada, France, Switzerland, and the United States, laboratory-inoculated beef and spinach samples, laboratory fractionally inoculated ground beef samples, and DNA samples from the federal red meat surveillance program. This study will provide significant insight into the accurate identification of E. coli strains present in tested samples. The work will allow the food industry to continue preventing foodborne outbreaks while increasing the volume of raw food products brought to the market.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.145
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.258
Teacher spread0.242 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

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